+ ## نظرة عامة
-تم بناء بنية Benzinga باستخدام **Go (Golang)** بفضل قدراته العالية على التزامن والسرعة، مما يمكّنها من التعامل بكفاءة مع أحجام كبيرة من حركة بيانات الأسواق المالية. تتم إدارة خطوط البيانات والبث في الوقت الفعلي بواسطة **Kafka**، الذي يتيح استيعاب البيانات ومعالجتها وتوزيعها بسرعة مع حد أدنى من زمن الاستجابة. تضمن هذه البنية قابلية التوسع والموثوقية عبر عمليات نشر عالمية، لتلبية متطلبات تقديم بيانات مالية في الوقت الفعلي.
+تم بناء منصتنا على بنية عصرية أصلية للسحابة تعتمد على خدمات AWS المُدارة، وأتمتة Kubernetes، وممارسات نشر GitOps. هذه **البنية التحتية الجاهزة للإنتاج** تُشغِّل ملايين طلبات واجهة برمجة التطبيقات API يوميًا مع الحفاظ على أزمنة استجابة أقل من 100 مللي ثانية، مع قابلية مراقبة شاملة وتوسّع آلي.
-
- 
-
+
- ## الوصول إلى البيانات بالوقت الفعلي عبر ويب سوكيت وواجهات برمجة التطبيقات REST
+
+
+---
+
+
+
+ نشر الخدمات عبر عدة مناطق توافر لضمان تحمّل الأعطال
+
+
+ شبكة سحابية افتراضية معزولة مع سياسات صارمة لمجموعات الأمان
+
+
+ نظام DNS عالمي مع فحوصات الصحة وتوجيه تلقائي في حال الفشل
+
+
+ مستوى تحكم Kubernetes مُدار من AWS مع اتفاقية مستوى خدمة (SLA) بنسبة 99.95%
+
+
+
+
+
+ التحقق من مفتاح واجهة برمجة التطبيقات API والتحقق من رمز JSON Web Token (JWT) على حافة الشبكة
+
+
+ تحديد معدل الطلبات لكل عميل لضمان تخصيص عادل للموارد
+
+
+ توزيع ذكي لحركة المرور عبر وحدات الخدمة (service pods) السليمة
+
+
+ تشفير كل حركة المرور باستخدام TLS 1.3 مع تجديد الشهادات تلقائيًا
+
+
+
+
+ ## البنية التحتية الأساسية
+
+
+
+ ### أساس البنية السحابية على AWS
+
+
+تعمل بنيتنا التحتية بالكامل على **Amazon Web Services (AWS)**، مستفيدة من:
+
+
+ ### البنية التحتية لـ Kubernetes
+
+
+نُشغِّل **عنقودين مخصصين من Kubernetes** لضمان عمليات نشر آمنة وعزل البيئات:
+
+| Environment | Purpose | Deployment Flow |
+|-------------|---------|-----------------|
+| **Staging Cluster** | اختبار المطورين، التحقق من ضمان الجودة (QA)، اختبارات التكامل | تُنشر تغييرات الشيفرة هنا أولًا لأغراض التحقق |
+| **Production Cluster** | حركة مرور عملاء فعلية مع ضمانات اتفاقيات مستوى الخدمة (SLA) | يتم ترقية الإصدارات التي تم التحقق منها فقط |
+
+
+ #### مكوّنات Kubernetes الرئيسية
+
+
+- **Karpenter** — أداة أصلية في AWS لتوسيع العُقد تلقائيًا، تقوم بتوفير سعة حوسبة بالحجم المناسب في ثوانٍ بدلًا من دقائق
+- **Horizontal Pod Autoscaler (HPA)** — مُوسِّع أفقي تلقائي للحاويات (Pods) يعتمد على وحدة المعالجة المركزية والذاكرة ومقاييس مخصّصة
+- **Kong Gateway** — بوابة مؤسسية لواجهة برمجة التطبيقات API تتولى إدارة حركة الدخول/الخروج، وتحديد معدّل الطلبات، والمصادقة
+- **ArgoCD** — متحكّم نشر يعتمد GitOps لإصدارات تصريحية وقابلة للتدقيق
+
+---
+
+
+ ## بوابة واجهة برمجة التطبيقات API وإدارة حركة البيانات
+
+
+
+ ### بوابة Kong
+
+
+تتدفق كل حركة مرور واجهة برمجة التطبيقات عبر **Kong Gateway**، ما يوفّر ما يلي:
+
+
+ ### Route 53 DNS
-تدعم واجهات برمجة التطبيقات API الخاصة بـ Benzinga كلًّا من بروتوكولي **ويب سوكيت** و**REST**، مما يتيح للعملاء الوصول إلى البيانات بالوقت الفعلي بالإضافة إلى تنفيذ الطلبات عند الحاجة. تُعدّ اتصالات ويب سوكيت مثاليةً للتطبيقات التي تتطلب تدفقات بيانات مستمرة، مثل أسعار السوق الحية وبيانات التداول، بينما تستجيب واجهات برمجة التطبيقات REST لمجموعة واسعة من الطلبات المتعلقة بالبيانات التاريخية، والأساسيات المالية للشركات، والأخبار، والتحليلات.
+يوفر AWS Route 53 ما يلي:
+
+- **توجيه عالمي يعتمد على زمن الوصول (latency-based routing)** — يتم توجيه المستخدمين تلقائيًا إلى أسرع نقطة نهاية
+- **فحوصات حالة (Health checks)** — مراقبة مستمرة مع انتقال تلقائي عند الفشل (failover)
+- **اتفاقية مستوى خدمة (SLA) بتوافرية 100%** — ضمان توافر مدعوم من AWS لحل أسماء نطاقات DNS
-
- ### أبرز مزايا واجهة برمجة التطبيقات API
+---
+
+
+ ## مسار CI/CD
-- **بيانات السوق اللحظية**: بث الأسعار الفورية، والصفقات، وغيرها من بيانات السوق الأساسية.
-- **البيانات التاريخية**: الوصول إلى البيانات التاريخية، بما في ذلك بيانات الشموع الزمنية (الـ bars)، والأسعار، وأداء السوق عبر الزمن.
-- **الأخبار والرؤى**: مواكبة أحدث الأخبار اللحظية والرؤى المؤثرة في حركة السوق.
-- **الأساسيات المالية للشركات**: استرجاع المقاييس المالية الأساسية، مثل الإيرادات، والأرباح، والنسب المالية الرئيسية.
+تفرض عملية النشر لدينا معايير جودة صارمة قبل أن تصل أي شيفرة إلى بيئة الإنتاج.
-
- ## كفاءة تخزين البيانات والبحث باستخدام Elasticsearch
+
- 
-
-
+ ### سير عمل التطوير
-لتحقيق استرجاع البيانات وتخزينها بكفاءة، تستخدم Benzinga **Elasticsearch** كمكوّن أساسي في نظام البحث والفهرسة لديها. يتيح Elasticsearch الوصول السريع إلى البيانات المهيكلة وغير المهيكلة، مما يضمن للمستخدمين إمكانية الاستعلام بسرعة عن مجموعات بيانات كبيرة، مثل البيانات التاريخية وأرشيف الأخبار، بزمن استجابة في حدود الملّي ثانية. يدعم هذا الإعداد أيضًا التحليلات، مما يتيح للعملاء تحليل البيانات واستخلاص رؤى قيّمة منها.
+```mermaid
+flowchart LR
+ A[Developer Commit] --> B[GitLab CI Pipeline]
+ B --> C{Linting & Tests}
+ C -->|Pass| D[Build Container Image]
+ C -->|Fail| E[Reject & Notify]
+ D --> F[Push to Registry]
+ F --> G[Peer Review Required]
+ G -->|2 Approvals| H[Update GitOps Repo]
+ H --> I[ArgoCD Sync]
+ I --> J[Deploy to Staging]
+ J -->|Validated| K[Promote to Production]
+```
-
-
-
-
-
- ## بنية تحتية قائمة على الخدمات المصغّرة من أجل القابلية للتوسّع
+
+ ### مراحل خطّ الأنابيب
-تعتمد بنية Benzinga على نهج **الخدمات المصغّرة**، حيث تتولى كل خدمة وظيفةً محددة — مثل إدخال البيانات أو معالجتها أو تخزينها أو توزيعها. يعزّز هذا النهج المعياري القابلية للتوسّع، إذ يتيح لكل مكوّن أن يتوسّع بشكل مستقل وفقًا للطلب. بالإضافة إلى ذلك، تتواصل الخدمات المصغّرة عبر بروتوكولات خفيفة الوزن، مما يضمن انخفاض زمن الاستجابة والمرونة على مستوى النظام بأكمله.
+| المرحلة | الوصف | بوابة الجودة |
+|--------|--------|--------------|
+| **Lint** | فحوصات نمط الشفرة والتحليل الساكن للشفرة | يجب أن تجتاز جميع القواعد |
+| **Unit Tests** | تنفيذ مجموعة الاختبارات الآلية | نجاح 100٪ من الاختبارات |
+| **Security Scan** | فحص الحاويات لاكتشاف الثغرات الأمنية | لا توجد ثغرات CVE حرجة/عالية |
+| **Build** | إنشاء صورة Docker مع وسم commit SHA | بناء ناجح |
+| **Peer Review** | مراجعة الشفرة يدويًا من قِبل مطوّرين اثنين | يتطلّب اعتمادًا مزدوجًا |
+| **GitOps Update** | تحديث وسم الصورة في مستودع ArgoCD | ترويج يدوي |
-
- ## توصيل مدعوم بشبكة CDN للصور والمحتوى الثابت
+
+ ### GitOps باستخدام ArgoCD
-لضمان توصيل الصور والشعارات وغيرها من الأصول الثابتة بسرعة، تستخدم Benzinga **CDN** (شبكة توصيل المحتوى). يعمل هذا التصميم على تقليل زمن التحميل وتقليل وقت الاستجابة عن طريق تخزين الموارد الثابتة مؤقتًا بالقرب من المستخدمين، مما يضمن تحميل الصور والملفات بشكل شبه فوري، بغض النظر عن الموقع الجغرافي.
+تُدار جميع عمليات النشر من خلال **ArgoCD** وفقًا لمبادئ GitOps:
+
+- **تعريفية (Declarative)** — الحالة المطلوبة مُعرَّفة في Git، وهو مصدر الحقيقة الوحيد
+- **مزامنة آلية** — يكتشف ArgoCD التغييرات ويطبقها تلقائيًا
+- **إمكانية التراجع (Rollback)** — تراجع فوري عن طريق إرجاع (revert) عمليات Git commit
+- **سجل تدقيق (Audit trail)** — سجل كامل لتاريخ عمليات النشر عبر سجلّات Git commit
-
- ## الفوائد الرئيسية للبنية المعمارية لدى Benzinga
+
+ يمكن تتبّع كل تغيير في بيئة الإنتاج إلى Git commit محدد، ومراجعة أقران، وموافقة مسؤول — مما يضمن قابلية تدقيق كاملة لتلبية متطلبات الامتثال.
+
+
+---
+
+
+ ## بنية التوسّع التلقائي
-- **القابلية للتوسع**: مُصمَّمة للتوسع أفقيًا، مع دعم ملايين الطلبات في الدقيقة وأعداد كبيرة من اتصالات ويب سوكيت المتزامنة.
-- **التوافرية العالية**: أنظمة احتياطية ومكوّنات موزَّعة جغرافيًا تضمن جهوزية عالية وتوافر البيانات.
-- **اتساق البيانات**: توفّر Kafka وElasticsearch معًا تدفّقًا متّسقًا للبيانات واسترجاعًا موثوقًا لها، مع آليات فعّالة لتجاوز الأعطال.
-- **انخفاض زمن الاستجابة**: مُحسَّنة لتسليم البيانات بأقل زمن استجابة ممكن، بالاستفادة من أداء Go، وبث Kafka، وإمكانات الوقت الفعلي في ويب سوكيت.
+تتوسع بنيتنا التحتية تلقائيًا على عدّة مستويات للتعامل مع الارتفاعات المفاجئة في حجم الحركة.
-
- ## مرونة النشر وتكامل البنية التحتية
+
+ ### التحجيم على مستوى الـ Pod (HPA)
-تدعم هندسة Benzinga خيارات نشر مرنة لتلبية الاحتياجات المتنوعة لعملائها:
+يتضمن كل نشر لخدمة تكوين `Horizontal Pod Autoscaler`:
+
+```yaml
+# مثال على تكوين HPA
+apiVersion: autoscaling/v2
+kind: HorizontalPodAutoscaler
+spec:
+ minReplicas: 3
+ maxReplicas: 50
+ metrics:
+ - type: Resource
+ resource:
+ name: cpu
+ target:
+ type: Utilization
+ averageUtilization: 70
+```
-- **خدمة سحابية مُدارة**: للعملاء الذين يبحثون عن تجربة سلسة، توفر Benzinga خدمة سحابية مُدارة بالكامل، بما في ذلك التوسّع التلقائي والصيانة الدورية.
-- **خيار الاستضافة الذاتية**: لمن يحتاجون إلى مزيد من التحكم، يمكن تكييف هندسة Benzinga للنشر في البيئات المحلية (on-premises) أو السحابات الخاصة، مع ضمان الملكية الكاملة للبيانات والامتثال للوائح المحلية.
+**محفّزات التحجيم:**
-
- ### وصول عالمي مع التخزين المؤقت على الحافة
+* استخدام وحدة المعالجة المركزية (CPU) > 70%
+* استخدام الذاكرة > 80%
+* مقاييس مخصّصة (عمق قائمة انتظار الطلبات، القيم المئوية لزمن الاستجابة)
+
+
+
+
+ **تتبّع موزّع وتسجيل السجلات**
+ - تجميع فوري للسجلات من جميع الخدمات
+ - تتبّع موزّع عبر الخدمات المصغّرة (Microservices)
+ - مراقبة أداء التطبيقات (APM)
+ - تتبّع الطلبات من البداية إلى النهاية باستخدام معرّفات الارتباط
+ - التعرّف على أنماط السجلات واكتشاف الشذوذ
+ - لوحات معلومات مخصّصة لمؤشرات الأعمال
+
+
+ **التنبيهات والمراقبة التركيبية**
+ - اختبار مستمر لنقاط نهاية واجهة برمجة التطبيقات API على مدار الساعة
+ - مراقبة تركيبية متعددة المناطق
+ - تتبّع زمن الاستجابة والتوفّر
+ - تنبيهات مؤتمتة مع توجيه ذكي
+ - تتبّع مؤشرات مستوى الخدمة (SLI)
+ - اكتشاف تراجع الأداء
+
+
+
+
+
+ يتم تجميع جميع سجلات التطبيقات من كل خدمة، وpod، وcontainer في الوقت الفعلي، ما يوفّر وصولًا فوريًا إلى معلومات تصحيح الأخطاء عبر البنية التحتية بالكامل.
+
+
+ يتم تتبّع كل طلب لواجهة برمجة التطبيقات API من البداية إلى النهاية عبر الخدمات المصغّرة، وموزّعات الحمل، وقواعد البيانات، والخدمات الخارجية. يتيح ذلك إجراء تحليل سريع للجذر الأساسي لمشكلات الأداء أو الأخطاء.
+
+
+ اكتشاف تلقائي للأخطاء مع تتبّعات المكدّس، والمعلومات السياقية، وأعداد المستخدمين المتأثرين. تُصنَّف الأخطاء حسب درجة الخطورة والتأثير.
+
+
+ مقاييس لحظية لأزمنة استجابة واجهة برمجة التطبيقات API، ومعدّل التدفق، ومعدّلات الأخطاء، واستخدام الموارد عبر جميع الخدمات.
+
+
+
+**ميزات Coralogix الأساسية في بيئة الإنتاج:**
+
+- **سياسة الاحتفاظ**: تخزين ساخن لمدة 30 يومًا للوصول الفوري، وأرشيف لمدة 90 يومًا لأغراض الامتثال
+- **أداء الاستعلام**: استعلامات بزمن استجابة أقل من ثانية عبر مليارات من إدخالات السجلات
+- **تكامل التنبيهات**: توجيه آلي إلى قنوات Slack والمهندسين المناوبين
+- **لوحات معلومات مخصّصة**: مقاييس خاصة بالأعمال مرئية لأصحاب المصلحة في الوقت الفعلي
+
+
+
+ تُشغَّل اختبارات مؤتمتة كل 60 ثانية من عدة مناطق جغرافية للتحقق من توفر واجهة برمجة التطبيقات API، وأزمنة الاستجابة، ودقة البيانات قبل أن يتأثر العملاء.
+
+
+ تحدد آليات اكتشاف الشذوذ المدعومة بالتعلم الآلي الأنماط غير الاعتيادية في المقاييس، مما يطلق التنبيهات قبل أن تؤثر المشكلات على العملاء.
+
+
+ تتبُّع لحظي لأهداف مستوى الخدمة (SLOs) مع تقارير مؤتمتة عن أهداف التوفر بنسبة 99.9%.
+
+
+ مراقبة مستمرة للقيم المئوية لزمن الاستجابة (الكمون) p50 وp95 وp99 لضمان أداء ثابت.
+
+
+
+**الاختبارات الاصطناعية في Datadog تتضمن:**
+
+| نوع الاختبار | التكرار | المناطق | المقاييس المُتابَعة |
+|-----------|-----------|---------|-----------------|
+| **فحوصات صحة واجهة برمجة التطبيقات API** | كل 60 ثانية | 5 مناطق عالمية | التوفر، زمن الاستجابة، رموز الحالة |
+| **اختبارات دقة البيانات** | كل 5 دقائق | 3 مناطق | حداثة البيانات، التحقق من المخطط، سلامة البيانات |
+| **اختبارات الأداء** | كل 60 ثانية | 5 مناطق | زمن الاستجابة (p50/p95/p99)، الإنتاجية، معدلات الأخطاء |
+| **اختبارات المصادقة** | كل 5 دقائق | منطقتان | التحقق من مفتاح واجهة برمجة التطبيقات API، تقييد المعدل، تدفقات OAuth |
+
+
+
+ **تنبيهات حرجة**
+
+ * حوادث P1/P2 تتطلب إجراءً فوريًا
+ * استدعاء آلي للمهندس المناوب
+ * مقاييس لحظية وروابط إلى runbook التشغيلي
+ * تعيين قائد للحادث
+
+
+
+ **رؤى الأداء**
+
+ * ملخصات يومية لحالة الأنظمة
+ * تنبيهات لتخطيط السعة
+ * إشعارات باتجاهات الأداء
+ * تحذيرات من اكتشاف الحالات الشاذة
+
+
+
+**سير عمل تنبيهات Slack:**
+
+```mermaid
+flowchart LR
+ A[تم تفعيل التنبيه] --> B{مستوى الخطورة}
+ B -->|P1/P2| C[#alerts-production]
+ B -->|P3/P4| D[#monitoring-insights]
+ C --> E[تم استدعاء المهندس المناوب]
+ C --> F[تم إنشاء قناة الحادث]
+ F --> G[تم تعيين المطور]
+ G --> H[التحقيق في السبب الجذري]
+ H --> I[تم نشر الإصلاح]
+ I --> J[تقرير ما بعد الحادث]
+```
+
+
+
+ جميع الحوادث من نوع P1/P2 تؤدي إلى **استدعاء فوري آلي** لمهندسي المناوبة مع تغطية 24/5.
+
+
+
+ أنظمة المراقبة لدينا اكتشفت وعالجت **95% من المشكلات المحتملة قبل أن تؤثر في العملاء** من خلال التنبيه الاستباقي والمعالجة الآلية.
+
+
+---
+
+
+
+ **إحصاءات بيئة الإنتاج**
+ - معالجة أكثر من 10 ملايين طلب لواجهة برمجة التطبيقات API يوميًا
+ - متوسط زمن استجابة أقل من 100 مللي ثانية
+ - تحقيق زمن جاهزية تاريخي بنسبة 99.9٪
+ - بدون أي فقدان للبيانات لأكثر من 3 سنوات
+
+
+ **تميز تشغيلي**
+ - تغطية هندسية للمناوبات على مدار 24 ساعة، 5 أيام في الأسبوع، طوال 365 يومًا في السنة
+ - تجاوز تلقائي للأعطال وآليات تعافٍ ذاتي
+ - تكرار متعدد المناطق
+
+
+
+
+
+ يتم تتبّع كل طلب، وكل سجل، وكل مقياس من البداية إلى النهاية باستخدام Coralogix للتتبّع الموزّع والتسجيل المركزي للسجلات
+
+
+ تقوم اختبارات المراقبة الاصطناعية في Datadog باختبار واجهات برمجة التطبيقات API كل 60 ثانية من عدّة مناطق جغرافية، مع إرسال تنبيهات عن المشكلات قبل تأثيرها في العملاء
+
+
+ يوجّه التكامل الآلي مع Slack التنبيهات إلى قنوات مخصّصة مع إسناد فوري إلى المطوّرين وتتبع مسار الحل
+
+
+ يضمن تحليل ما بعد كل حادثة عدم تكرار المشكلات مرة أخرى، من خلال تطبيق إجراءات وقائية آلية
+
+
+
+
+ **جاهز للإنتاج**: قامت بنيتنا التحتية بمعالجة أكثر من **مليار طلب إلى واجهة برمجة التطبيقات API** مع توافر بنسبة 99.9% والمحافظة على زمن استجابة أقل من 100 مللي ثانية لتسليم بيانات مالية في الوقت الفعلي.
+
+
+---
+
+
+
+ AWS EKS مع نشر عبر مناطق توافر متعددة (multi-AZ) ومستوى تحكم مُدار لضمان أعلى وقت تشغيل ممكن
+
+
+ إصدارات مُدارة بواسطة ArgoCD مع سجل تدقيق كامل وإمكانات تراجع فوري
+
+
+ Karpenter + HPA لإدارة السعة بسلاسة والتعامل تلقائيًا مع طفرات حركة المرور
+
+
+ تتبّع/تسجيل بواسطة Coralogix + تنبيهات/اختبارات اصطناعية عبر Datadog مع تكامل Slack للاستجابة السريعة للحوادث
+
+
+ مهندسون مخصصون للمناوبات (on-call)
+
+
+ دفاع متعمّق يعتمد على التشفير وRBAC وعزل الشبكة لحماية بياناتك
+
+
+
+
+ **نجاحك هو أولويتنا**: لأي أسئلة حول بنيتنا التحتية أو ضمانات اتفاقية مستوى الخدمة SLA أو لمناقشة متطلباتك المحددة للموثوقية، تواصل مع ممثل حسابك أو أرسل بريدًا إلكترونيًا إلى [support@benzinga.com](mailto:support@benzinga.com).
+
\ No newline at end of file
diff --git a/ar/openapi/calendar_api.spec.yml b/ar/openapi/calendar_api.spec.yml
index e87b059a..1f91dc43 100644
--- a/ar/openapi/calendar_api.spec.yml
+++ b/ar/openapi/calendar_api.spec.yml
@@ -2886,14 +2886,19 @@ components:
calendarapi.AggregateRating:
properties:
buy:
+ example: 10
type: integer
hold:
+ example: 3
type: integer
sell:
+ example: 1
type: integer
strong_buy:
+ example: 5
type: integer
strong_sell:
+ example: 0
type: integer
type: object
calendarapi.AnalystInsightsJSON:
@@ -2933,22 +2938,31 @@ components:
aggregate_ratings:
$ref: "#/components/schemas/calendarapi.AggregateRating"
aggregate_type:
+ example: 90D
type: string
consensus_price_target:
+ example: 195.5
type: number
consensus_rating:
+ example: Buy
type: string
consensus_rating_val:
+ example: 4.2
type: number
high_price_target:
+ example: 225
type: number
low_price_target:
+ example: 150
type: number
total_analyst_count:
+ example: 19
type: integer
unique_analyst_count:
+ example: 15
type: integer
updated_at:
+ example: 2024-01-09T16:00:00Z
type: string
type: object
calendarapi.DividendJSON:
@@ -3034,40 +3048,53 @@ components:
calendarapi.InsiderTransaction:
properties:
accession_number:
+ example: 0001127602-24-000123
type: string
company_cik:
+ example: 320193
type: string
company_name:
+ example: Apple Inc.
type: string
company_symbol:
+ example: AAPL
type: string
filing_date:
+ example: 2024-01-09T00:00:00Z
type: string
footnotes:
items:
$ref: "#/components/schemas/calendarapi.SECFootnotes"
type: array
form_type:
+ example: "4"
type: string
html_url:
+ example: https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000320193
type: string
id:
+ example: 64a1b2c3d4e5f6789012345
type: string
is_10b5:
+ example: true
type: boolean
owner:
$ref: "#/components/schemas/calendarapi.Owner"
remaining_shares:
+ example: "125000"
type: string
remaining_underlying_shares:
+ example: "50000"
type: string
traded_percentage:
+ example: "15.5"
type: string
transactions:
items:
$ref: "#/components/schemas/calendarapi.Transaction"
type: array
updated:
+ example: 1704758400
type: integer
type: object
calendarapi.InsiderTransactionFilingDoc:
@@ -3104,18 +3131,25 @@ components:
calendarapi.Owner:
properties:
insider_cik:
+ example: "0001234567"
type: string
insider_name:
+ example: Tim Cook
type: string
insider_title:
+ example: Chief Executive Officer
type: string
is_director:
+ example: true
type: boolean
is_officer:
+ example: true
type: boolean
is_ten_percent_owner:
+ example: false
type: boolean
raw_signature:
+ example: /s/ Tim Cook
type: string
type: object
calendarapi.RatingJSON:
@@ -3161,8 +3195,10 @@ components:
calendarapi.SECFootnotes:
properties:
id:
+ example: F1
type: string
text:
+ example: Shares were sold pursuant to a Rule 10b5-1 trading plan
type: string
type: object
calendarapi.SplitJSON:
@@ -3176,40 +3212,58 @@ components:
calendarapi.Transaction:
properties:
acquired_or_disposed:
+ example: D
type: string
conversion_exercise_price_derivative:
+ example: "150.25"
type: string
date_deemed_execution:
+ example: 2024-01-09T00:00:00Z
type: string
date_exercisable:
+ example: 2024-01-09T00:00:00Z
type: string
date_expiration:
+ example: 2025-01-09T00:00:00Z
type: string
date_transaction:
+ example: 2024-01-09T00:00:00Z
type: string
is_derivative:
+ example: false
type: boolean
ownership:
+ example: Direct
type: string
post_transaction_quantity:
+ example: "250000"
type: string
price_per_share:
+ example: "150.25"
type: string
remaining_underlying_shares:
+ example: "50000"
type: string
security_title:
+ example: Common Stock
type: string
shares:
+ example: "10000"
type: string
transaction_code:
+ example: S
type: string
transaction_id:
+ example: TXN-20240109-001
type: string
underlying_security_title:
+ example: Common Stock
type: string
underlying_shares:
+ example: "10000"
type: string
voluntarily_reported:
+ example: false
type: boolean
type: object
servers:
diff --git a/ar/openapi/data-api-proxy_api.spec.yml b/ar/openapi/data-api-proxy_api.spec.yml
index 6a6f73a1..884eb026 100644
--- a/ar/openapi/data-api-proxy_api.spec.yml
+++ b/ar/openapi/data-api-proxy_api.spec.yml
@@ -1450,6 +1450,8 @@ components:
type: object
bzhttp.ErrorCode:
enum:
+ - unsupported_message_type
+ - database_query_error
- json_unmarshaling_error
- no_data_found
- no_matching_endpoint
@@ -1461,10 +1463,10 @@ components:
- failed_dependency
- service_unavailable
- upstream_api_error
- - unsupported_message_type
- - database_query_error
type: string
x-enum-varnames:
+ - ErrorUnsupportedMessageType
+ - ErrorDBQueryError
- ErrorJSONUnmarshaling
- ErrorNoDataFound
- ErrorNoMatchingEndpoint
@@ -1476,8 +1478,6 @@ components:
- ErrorFailedDependency
- ErrorServiceUnavailable
- ErrorUpstreamAPIError
- - ErrorUnsupportedMessageType
- - ErrorDBQueryError
bzhttp.Resp:
properties:
data:
diff --git a/ar/openapi/logo-api_api.spec.yml b/ar/openapi/logo-api_api.spec.yml
index 5c0b5775..7d545777 100644
--- a/ar/openapi/logo-api_api.spec.yml
+++ b/ar/openapi/logo-api_api.spec.yml
@@ -151,6 +151,13 @@ paths:
name: max_width
schema:
type: string
+ - description: إذا كانت القيمة true، فسيُضاف معامل الاستعلام
+ flutter_compatible=true إلى عناوين URL لملفات SVG لضمان التوافق مع
+ مكتبة flutter_svg
+ in: query
+ name: flutter_compatible
+ schema:
+ type: boolean
responses:
"200":
description: استجابة ناجحة تتضمن مصفوفة من كائنات LogoClientResponse ضمن الحقل
diff --git a/ar/openapi/newsquantified-api_api.spec.yml b/ar/openapi/newsquantified-api_api.spec.yml
index 5f1360e6..95d121f3 100644
--- a/ar/openapi/newsquantified-api_api.spec.yml
+++ b/ar/openapi/newsquantified-api_api.spec.yml
@@ -116,8 +116,6 @@ components:
type: object
bzhttp.ErrorCode:
enum:
- - unsupported_message_type
- - database_query_error
- json_unmarshaling_error
- no_data_found
- no_matching_endpoint
@@ -129,10 +127,10 @@ components:
- failed_dependency
- service_unavailable
- upstream_api_error
+ - unsupported_message_type
+ - database_query_error
type: string
x-enum-varnames:
- - ErrorUnsupportedMessageType
- - ErrorDBQueryError
- ErrorJSONUnmarshaling
- ErrorNoDataFound
- ErrorNoMatchingEndpoint
@@ -144,6 +142,8 @@ components:
- ErrorFailedDependency
- ErrorServiceUnavailable
- ErrorUpstreamAPIError
+ - ErrorUnsupportedMessageType
+ - ErrorDBQueryError
bzhttp.Resp:
properties:
data:
diff --git a/ar/openapi/ticker-trends-api_api.spec.yml b/ar/openapi/ticker-trends-api_api.spec.yml
index bbeb116c..bc61590c 100644
--- a/ar/openapi/ticker-trends-api_api.spec.yml
+++ b/ar/openapi/ticker-trends-api_api.spec.yml
@@ -192,8 +192,6 @@ components:
type: object
bzhttp.ErrorCode:
enum:
- - unsupported_message_type
- - database_query_error
- json_unmarshaling_error
- no_data_found
- no_matching_endpoint
@@ -205,10 +203,10 @@ components:
- failed_dependency
- service_unavailable
- upstream_api_error
+ - unsupported_message_type
+ - database_query_error
type: string
x-enum-varnames:
- - ErrorUnsupportedMessageType
- - ErrorDBQueryError
- ErrorJSONUnmarshaling
- ErrorNoDataFound
- ErrorNoMatchingEndpoint
@@ -220,6 +218,8 @@ components:
- ErrorFailedDependency
- ErrorServiceUnavailable
- ErrorUpstreamAPIError
+ - ErrorUnsupportedMessageType
+ - ErrorDBQueryError
bzhttp.Resp:
properties:
data:
diff --git a/docs.json b/docs.json
index 7da547a0..0985026a 100644
--- a/docs.json
+++ b/docs.json
@@ -361,7 +361,7 @@
"tab": "التوثيق",
"groups": [
{
- "group": "مقدمة",
+ "group": "نظرة عامة",
"pages": [
"ar/introduction/welcome",
"ar/introduction/introduction",
@@ -388,6 +388,12 @@
"ar/api-reference/errors"
]
},
+ {
+ "group": "الأدلة",
+ "pages": [
+ "ar/api-reference/guides/consensus-ratings-explained"
+ ]
+ },
{
"group": "رؤى المحللين",
"pages": [
@@ -396,14 +402,14 @@
]
},
{
- "group": "الشموع السعرية",
+ "group": "بيانات الشريط",
"pages": [
"ar/api-reference/data-api-proxy_api/bars/overview",
"ar/api-reference/data-api-proxy_api/bars/get-bars-v2"
]
},
{
- "group": "ما يقوله المتفائلون (الثيران) وما يقوله المتشائمون (الدببة)",
+ "group": "تقييمات الثيران والدببة",
"pages": [
"ar/api-reference/calendar_api/bulls-say-bears-say/overview",
"ar/api-reference/calendar_api/bulls-say-bears-say/latest-bull-and-bear-cases-for-a-given-ticker-symbol"
@@ -436,7 +442,7 @@
]
},
{
- "group": "الأساسيات المالية للشركة",
+ "group": "الأساسيات المالية للشركات",
"pages": [
"ar/api-reference/data-api-proxy_api/fundamentals/overview",
"ar/api-reference/data-api-proxy_api/fundamentals/get-alpha-beta-v21",
@@ -467,7 +473,7 @@
]
},
{
- "group": "نصوص مكالمات المؤتمرات الهاتفية",
+ "group": "نصوص مكالمات الأرباح",
"pages": [
"ar/api-reference/delivery_api/overview",
"ar/api-reference/delivery_api/calls/fetch-all-calls",
@@ -477,7 +483,7 @@
]
},
{
- "group": "أسعار متأخرة",
+ "group": "عروض الأسعار المتأخرة",
"pages": [
"ar/api-reference/data-api-proxy_api/quotedelayed/overview",
"ar/api-reference/data-api-proxy_api/quotedelayed/get-delayed-quotes-for-a-list-of-symbols"
@@ -508,7 +514,7 @@
]
},
{
- "group": "تغذية الأخبار",
+ "group": "موجز الأخبار",
"pages": [
"ar/api-reference/news-api_api/news/overview",
"ar/api-reference/news-api_api/news/get-the-news-items",
@@ -531,7 +537,7 @@
]
},
{
- "group": "الأسعار (متأخرة)",
+ "group": "عروض الأسعار المتأخرة",
"pages": [
"ar/api-reference/data-api-proxy_api/quotedelayed/overview",
"ar/api-reference/data-api-proxy_api/quotedelayed/get-delayed-quotes-for-a-list-of-symbols"
@@ -567,7 +573,7 @@
]
},
{
- "group": "تحليلات المحللين",
+ "group": "رؤى المحللين",
"pages": [
"ar/ws-reference/data-websocket/get-analyst-insights-stream"
]
@@ -593,7 +599,7 @@
]
},
{
- "group": "التفريغات النصية (Transcripts)",
+ "group": "النصوص الحرفية",
"pages": [
"ar/ws-reference/data-websocket/get-transcripts-stream"
]
@@ -601,17 +607,17 @@
]
},
{
- "tab": "مرجع Webhook",
+ "tab": "مرجع الويب هوك",
"groups": [
{
- "group": "ويب هوكس",
+ "group": "خطافات الويب",
"pages": [
"ar/webhook-reference/overview",
"ar/webhook-reference/webhook-engine"
]
},
{
- "group": "واجهة برمجة التطبيقات API للويب هوك",
+ "group": "واجهة برمجة التطبيقات API لخطافات الويب",
"pages": [
"ar/api-reference/webhook_api/test-webhook-delivery"
]
@@ -622,7 +628,7 @@
"tab": "مرجع TCP",
"groups": [
{
- "group": "بث عبر TCP",
+ "group": "البث عبر بروتوكول TCP",
"pages": [
"ar/tcp-reference/introduction",
"ar/tcp-reference/connection",
@@ -630,7 +636,7 @@
]
},
{
- "group": "مكتبات العميل البرمجية",
+ "group": "مكتبات العميل",
"pages": [
"ar/tcp-reference/go-client",
"ar/tcp-reference/python-client"
@@ -639,10 +645,10 @@
]
},
{
- "tab": "الودجات",
+ "tab": "الويدجتات",
"groups": [
{
- "group": "الودجات",
+ "group": "الويدجات",
"pages": [
"ar/widgets/overview",
"ar/widgets/authorization"
@@ -654,13 +660,13 @@
"tab": "عدة تطوير البرمجيات SDK",
"groups": [
{
- "group": "حزم عِدّة تطوير البرمجيات SDK",
+ "group": "عدة تطوير البرمجيات SDK",
"pages": [
"ar/sdks/overview"
]
},
{
- "group": "حزم عِدّة تطوير البرمجيات SDK",
+ "group": "عدة تطوير البرمجيات SDK",
"pages": [
"ar/sdks/languages/java",
"ar/sdks/languages/node",
@@ -679,6 +685,17 @@
]
}
]
+ },
+ {
+ "tab": "خريطة الطريق",
+ "groups": [
+ {
+ "group": "خريطة الطريق",
+ "pages": [
+ "ar/changelog/roadmap"
+ ]
+ }
+ ]
}
],
"language": "ar"
@@ -717,7 +734,13 @@
]
},
{
- "group": "Información de analistas",
+ "group": "Guías",
+ "pages": [
+ "es/api-reference/guides/consensus-ratings-explained"
+ ]
+ },
+ {
+ "group": "Opiniones de analistas",
"pages": [
"es/api-reference/calendar_api/analyst-insights/overview",
"es/api-reference/calendar_api/analyst-insights/analyst-insights-v1"
@@ -731,7 +754,7 @@
]
},
{
- "group": "Bulls Say Bears Say",
+ "group": "Alcistas y bajistas",
"pages": [
"es/api-reference/calendar_api/bulls-say-bears-say/overview",
"es/api-reference/calendar_api/bulls-say-bears-say/latest-bull-and-bear-cases-for-a-given-ticker-symbol"
@@ -812,7 +835,7 @@
]
},
{
- "group": "Transacciones gubernamentales",
+ "group": "Operaciones del gobierno",
"pages": [
"es/api-reference/calendar_api/government-trades/overview",
"es/api-reference/calendar_api/government-trade-reports/government-trade-reports",
@@ -820,7 +843,7 @@
]
},
{
- "group": "Transacciones de iniciados",
+ "group": "Operaciones de insiders",
"pages": [
"es/api-reference/calendar_api/insider-transaction/overview",
"es/api-reference/calendar_api/insider-transaction/insider-transaction-filing",
@@ -836,7 +859,7 @@
]
},
{
- "group": "Newsfeed",
+ "group": "Feed de noticias",
"pages": [
"es/api-reference/news-api_api/news/overview",
"es/api-reference/news-api_api/news/get-the-news-items",
@@ -895,7 +918,7 @@
]
},
{
- "group": "Opiniones de analistas",
+ "group": "Información de analistas",
"pages": [
"es/ws-reference/data-websocket/get-analyst-insights-stream"
]
@@ -909,7 +932,7 @@
]
},
{
- "group": "Sentimiento del mercado",
+ "group": "Sentimiento de mercado",
"pages": [
"es/ws-reference/data-websocket/get-bulls-bears-say-stream"
]
@@ -929,7 +952,7 @@
]
},
{
- "tab": "Referencia de Webhooks",
+ "tab": "Referencia de Webhook",
"groups": [
{
"group": "Webhooks",
@@ -939,7 +962,7 @@
]
},
{
- "group": "API de webhooks",
+ "group": "API de Webhooks",
"pages": [
"es/api-reference/webhook_api/test-webhook-delivery"
]
@@ -950,7 +973,7 @@
"tab": "Referencia de TCP",
"groups": [
{
- "group": "Transmisión vía TCP",
+ "group": "Streaming por TCP",
"pages": [
"es/tcp-reference/introduction",
"es/tcp-reference/connection",
@@ -958,7 +981,7 @@
]
},
{
- "group": "Librerías de cliente",
+ "group": "Bibliotecas de cliente",
"pages": [
"es/tcp-reference/go-client",
"es/tcp-reference/python-client"
@@ -982,13 +1005,13 @@
"tab": "Kits de desarrollo de software (SDK)",
"groups": [
{
- "group": "SDKs",
+ "group": "Kits de desarrollo de software",
"pages": [
"es/sdks/overview"
]
},
{
- "group": "SDKs",
+ "group": "Kits de desarrollo de software",
"pages": [
"es/sdks/languages/java",
"es/sdks/languages/node",
@@ -1007,6 +1030,17 @@
]
}
]
+ },
+ {
+ "tab": "Hoja de ruta",
+ "groups": [
+ {
+ "group": "Hoja de ruta",
+ "pages": [
+ "es/changelog/roadmap"
+ ]
+ }
+ ]
}
],
"language": "es"
@@ -1034,7 +1068,7 @@
]
},
{
- "tab": "APIリファレンス",
+ "tab": "API リファレンス",
"groups": [
{
"group": "APIドキュメント",
@@ -1044,6 +1078,12 @@
"ja/api-reference/errors"
]
},
+ {
+ "group": "ガイド",
+ "pages": [
+ "ja/api-reference/guides/consensus-ratings-explained"
+ ]
+ },
{
"group": "アナリスト・インサイト",
"pages": [
@@ -1059,14 +1099,14 @@
]
},
{
- "group": "強気／弱気",
+ "group": "Bulls Say Bears Say",
"pages": [
"ja/api-reference/calendar_api/bulls-say-bears-say/overview",
"ja/api-reference/calendar_api/bulls-say-bears-say/latest-bull-and-bear-cases-for-a-given-ticker-symbol"
]
},
{
- "group": "カレンダー",
+ "group": "calendar",
"pages": [
"ja/api-reference/calendar_api/overview",
"ja/api-reference/calendar_api/block-trade/blocktrade-v1",
@@ -1123,7 +1163,7 @@
]
},
{
- "group": "カンファレンスコール・トランスクリプト",
+ "group": "カンファレンスコールの書き起こし",
"pages": [
"ja/api-reference/delivery_api/overview",
"ja/api-reference/delivery_api/calls/fetch-all-calls",
@@ -1133,14 +1173,14 @@
]
},
{
- "group": "遅延気配値",
+ "group": "遅延気配情報",
"pages": [
"ja/api-reference/data-api-proxy_api/quotedelayed/overview",
"ja/api-reference/data-api-proxy_api/quotedelayed/get-delayed-quotes-for-a-list-of-symbols"
]
},
{
- "group": "政府関係者による取引",
+ "group": "政府関係者の取引",
"pages": [
"ja/api-reference/calendar_api/government-trades/overview",
"ja/api-reference/calendar_api/government-trade-reports/government-trade-reports",
@@ -1156,7 +1196,7 @@
]
},
{
- "group": "市場データ",
+ "group": "マーケットデータ",
"pages": [
"ja/api-reference/data-api-proxy_api/market-data/overview",
"ja/api-reference/data-api-proxy_api/market-data/market-movers",
@@ -1187,14 +1227,14 @@
]
},
{
- "group": "遅延気配値",
+ "group": "遅延気配情報",
"pages": [
"ja/api-reference/data-api-proxy_api/quotedelayed/overview",
"ja/api-reference/data-api-proxy_api/quotedelayed/get-delayed-quotes-for-a-list-of-symbols"
]
},
{
- "group": "ティッカー・トレンド",
+ "group": "ticker トレンド",
"pages": [
"ja/api-reference/ticker-trends-api_api/ticker-trends/overview",
"ja/api-reference/ticker-trends-api_api/ticker-trends/get-ticker-trend-data",
@@ -1202,7 +1242,7 @@
]
},
{
- "group": "なぜ動いているのか（WIIMs）",
+ "group": "Why Is It Moving（WIIM）",
"pages": [
"ja/api-reference/news-api_api/wiims/overview",
"ja/api-reference/news-api_api/news/get-wiims"
@@ -1223,7 +1263,7 @@
]
},
{
- "group": "アナリストインサイト",
+ "group": "アナリスト・インサイト",
"pages": [
"ja/ws-reference/data-websocket/get-analyst-insights-stream"
]
@@ -1267,7 +1307,7 @@
]
},
{
- "group": "Webhook API",
+ "group": "ウェブフック API",
"pages": [
"ja/api-reference/webhook_api/test-webhook-delivery"
]
@@ -1275,10 +1315,10 @@
]
},
{
- "tab": "TCPリファレンス",
+ "tab": "TCP リファレンス",
"groups": [
{
- "group": "TCPストリーミング",
+ "group": "TCP ストリーミング",
"pages": [
"ja/tcp-reference/introduction",
"ja/tcp-reference/connection",
@@ -1335,6 +1375,17 @@
]
}
]
+ },
+ {
+ "tab": "未定義",
+ "groups": [
+ {
+ "group": "未定義",
+ "pages": [
+ "ja/changelog/roadmap"
+ ]
+ }
+ ]
}
],
"language": "ja"
@@ -1362,7 +1413,7 @@
]
},
{
- "tab": "API 참조",
+ "tab": "API 레퍼런스",
"groups": [
{
"group": "API 문서",
@@ -1372,6 +1423,12 @@
"ko/api-reference/errors"
]
},
+ {
+ "group": "가이드",
+ "pages": [
+ "ko/api-reference/guides/consensus-ratings-explained"
+ ]
+ },
{
"group": "애널리스트 인사이트",
"pages": [
@@ -1380,7 +1437,7 @@
]
},
{
- "group": "Bar 데이터",
+ "group": "가격 표시 바",
"pages": [
"ko/api-reference/data-api-proxy_api/bars/overview",
"ko/api-reference/data-api-proxy_api/bars/get-bars-v2"
@@ -1394,7 +1451,7 @@
]
},
{
- "group": "calendar",
+ "group": "캘린더",
"pages": [
"ko/api-reference/calendar_api/overview",
"ko/api-reference/calendar_api/block-trade/blocktrade-v1",
@@ -1420,7 +1477,7 @@
]
},
{
- "group": "기초 재무 지표",
+ "group": "기업 기초 재무 지표",
"pages": [
"ko/api-reference/data-api-proxy_api/fundamentals/overview",
"ko/api-reference/data-api-proxy_api/fundamentals/get-alpha-beta-v21",
@@ -1451,7 +1508,7 @@
]
},
{
- "group": "컨퍼런스 콜 녹취록",
+ "group": "컨퍼런스 콜 통화록",
"pages": [
"ko/api-reference/delivery_api/overview",
"ko/api-reference/delivery_api/calls/fetch-all-calls",
@@ -1468,7 +1525,7 @@
]
},
{
- "group": "정부 매매",
+ "group": "정부 거래",
"pages": [
"ko/api-reference/calendar_api/government-trades/overview",
"ko/api-reference/calendar_api/government-trade-reports/government-trade-reports",
@@ -1476,7 +1533,7 @@
]
},
{
- "group": "내부자 매매",
+ "group": "내부자 거래",
"pages": [
"ko/api-reference/calendar_api/insider-transaction/overview",
"ko/api-reference/calendar_api/insider-transaction/insider-transaction-filing",
@@ -1508,7 +1565,7 @@
]
},
{
- "group": "보도자료",
+ "group": "보도 자료",
"pages": [
"ko/api-reference/news-api_api/press-releases/overview",
"ko/api-reference/news-api_api/press-releases/get-press-releases"
@@ -1539,7 +1596,7 @@
]
},
{
- "tab": "웹소켓 참조",
+ "tab": "웹소켓 레퍼런스",
"groups": [
{
"group": "웹소켓",
@@ -1585,17 +1642,17 @@
]
},
{
- "tab": "웹훅 참조",
+ "tab": "웹훅 레퍼런스",
"groups": [
{
- "group": "웹훅",
+ "group": "웹후크",
"pages": [
"ko/webhook-reference/overview",
"ko/webhook-reference/webhook-engine"
]
},
{
- "group": "웹훅 API",
+ "group": "웹후크 API",
"pages": [
"ko/api-reference/webhook_api/test-webhook-delivery"
]
@@ -1603,7 +1660,7 @@
]
},
{
- "tab": "TCP 참조",
+ "tab": "TCP 레퍼런스",
"groups": [
{
"group": "TCP 스트리밍",
@@ -1654,15 +1711,26 @@
]
},
{
- "tab": "변경 내역",
+ "tab": "변경 로그",
"groups": [
{
- "group": "변경 내역",
+ "group": "변경 로그",
"pages": [
"ko/changelog/overview"
]
}
]
+ },
+ {
+ "tab": "로드맵",
+ "groups": [
+ {
+ "group": "로드맵",
+ "pages": [
+ "ko/changelog/roadmap"
+ ]
+ }
+ ]
}
],
"language": "ko"
diff --git a/es/api-reference/guides/consensus-ratings-explained.mdx b/es/api-reference/guides/consensus-ratings-explained.mdx
new file mode 100644
index 00000000..796d20a7
--- /dev/null
+++ b/es/api-reference/guides/consensus-ratings-explained.mdx
@@ -0,0 +1,320 @@
+---
+title: "Calificaciones de consenso explicadas"
+description: "Aprende cómo Benzinga calcula las calificaciones de consenso a partir de las recomendaciones de analistas individuales"
+---
+
+
+ Las calificaciones sin un precio objetivo válido se excluyen del análisis.
+
+
+
+
+ Si un analista de la misma firma actualiza su calificación varias veces, el conteo total incluye todas las ocasiones, pero solo la más reciente se utiliza en los cálculos (reflejado en el conteo único).
+
+
+
+ Las calificaciones de consenso se recalculan cada vez que se publican nuevas calificaciones de analistas o se actualizan las existentes.
+
+
+
+ Sin cobertura de analistas, no se puede calcular una calificación de consenso. La acción no mostrará datos de consenso.
+
+
+
+ No. El consenso solo cambia cuando los analistas emiten nuevas calificaciones o actualizan las existentes.
+
+
+
+***
+
+
+
+
+
+ Obtener datos de calificaciones de consenso para acciones
+
+
+
+ Obtener las calificaciones individuales de los analistas
+
+
\ No newline at end of file
diff --git a/es/changelog/roadmap.mdx b/es/changelog/roadmap.mdx
new file mode 100644
index 00000000..bc4fedc1
--- /dev/null
+++ b/es/changelog/roadmap.mdx
@@ -0,0 +1,120 @@
+---
+title: "Hoja de ruta"
+description: "Descubre en qué estamos trabajando a continuación."
+---
+
+
+¿Tienes alguna sugerencia de funcionalidad? [Crea un issue en GitHub](https://github.com/Benzinga/benzinga-docs/issues/new) o [contáctanos](mailto:licensing@benzinga.com).
+
\ No newline at end of file
diff --git a/es/introduction/architecture.mdx b/es/introduction/architecture.mdx
index 8fbdbfc7..e7c533fe 100644
--- a/es/introduction/architecture.mdx
+++ b/es/introduction/architecture.mdx
@@ -1,97 +1,518 @@
---
-title: Arquitectura
-description: Infraestructura escalable de datos financieros en tiempo real
-icon: database
+title: "Arquitectura de infraestructura"
+description: "Infraestructura de nivel empresarial que sustenta el 99,9% de disponibilidad de la API de Benzinga con supervisión y confiabilidad de clase mundial"
+icon: microchip
---
-Benzinga proporciona una infraestructura de API sólida y altamente escalable, diseñada para ofrecer datos financieros en tiempo real a aplicaciones y servicios en todo el mundo. Con un enfoque en la velocidad y la disponibilidad, la arquitectura de Benzinga aprovecha una variedad de tecnologías modernas, entre ellas **Go (Golang)**, **Kafka**, **WebSockets**, **Elasticsearch** y **microservicios**, para garantizar que los usuarios reciban datos confiables y de baja latencia siempre que los necesiten.
+
+ La infraestructura de Benzinga está diseñada para una **disponibilidad del 99,9%**, lo que garantiza que tus aplicaciones reciban datos financieros confiables y en tiempo real en todo momento. Nuestro entorno de producción está exhaustivamente probado, completamente monitorizada y respaldado por soporte de ingeniería de guardia 24/5.
+
-
+ ### التحجيم على مستوى العقدة (Karpenter)
-لتحسين الأداء بشكل أكبر، تستخدم Benzinga **التخزين المؤقت على الحافة (edge caching)** لضمان وصول البيانات، بما في ذلك التدفقات الآنية والمحتوى الثابت، إلى المستخدمين بأقل قدر ممكن من التأخير. ومن خلال توزيع نقاط تواجد (PoPs) بشكل استراتيجي حول العالم، تضمن Benzinga توافرًا عاليًا وزمن استجابة منخفضًا للعملاء عبر القارات.
+يتولى **Karpenter** إدارة سعة الـ cluster من خلال:
-يتيح هذا التصميم الموزع لـ Benzinga توفير بيانات آنية وموثوقة للعملاء بغض النظر عن موقعهم الجغرافي، بما يلبي احتياجات المستخدمين المحليين والعالميين على حد سواء.
+- تجهيز عقد بأحجام مثالية في أقل من 60 ثانية
+- دمج العقد قليلة الاستخدام لتقليل التكاليف
+- دعم مثيلات Spot للأحمال غير الحرجة
+- احترام قيود طوبولوجيا الـ pod ومناطق التوافر (availability zones)
---
-تجمع هذه البنية بين تقنيات حديثة قابلة للتوسع لتقديم بيانات ورؤى مالية سريعة وموثوقة، بما يدعم التزام Benzinga بالجودة والأداء. لمزيد من التفاصيل التقنية أو للبدء باستخدام واجهات برمجة التطبيقات API الخاصة بنا، يُرجى التواصل مع فريق دعم Benzinga أو زيارة مستنداتنا.
\ No newline at end of file
+
+ ## قابلية الرصد والمراقبة على مستوى بيئة الإنتاج
+
+
+تستخدم بنيتنا التحتية **مراقبة على مستوى المؤسسات** مع طبقات متعددة من قابلية الرصد، مما يضمن رؤية كاملة لصحة النظام وأدائه وموثوقيته. تتم مراقبة كل مكوّن بشكل مستمر مع تنبيهات مؤتمتة وبروتوكولات استجابة للحوادث.
+
+
+ ### حزمة مراقبة شاملة
+
+
+
+ ### Coralogix: التتبّع وتسجيل السجلات
+
+
+توفر Coralogix **قابلية ملاحظة كاملة** لطبقة التطبيق لدينا:
+
+
+ ### Datadog: التنبيه والاختبارات الاصطناعية
+
+
+يوفر Datadog **مراقبة استباقية** والتحقق المستمر:
+
+
+ ### تكامل Slack وإدارة الحوادث
+
+
+تتكامل جميع أنظمة المراقبة مع **قنوات Slack مخصّصة** لضمان الرصد الفوري والاستجابة السريعة:
+
+
+ ### التنبيهات والحوادث
+
+
+**عملية إسناد المطورين:**
+
+1. **تفعيل التنبيه** → إشعار Slack تلقائي يتضمّن السياق والقياسات
+2. **فرز من المهندس المناوب** → تقييم مستوى الخطورة وإنشاء قناة للحادث
+3. **تعيين المطور** → الإشارة إلى خبير المجال حسب الخدمة المتأثرة
+4. **التحقيق** → تحليل السبب الجذري باستخدام تتبعات Coralogix وقياسات Datadog
+5. **المعالجة** → نشر الإصلاح عبر خط أنابيب GitOps القياسي
+6. **مراجعة ما بعد الحادث (Post-Mortem)** → توثيق الحادث مع إجراءات وقائية
+
+
+ ## الأمان والامتثال
+
+
+
+ ### أمان الشبكة
+
+
+- **VPC Isolation** — عزل كامل للشبكة عن الإنترنت العامة
+- **Security Groups** — قواعد دخول/خروج صارمة، مع سياسة افتراضية قائمة على الرفض (deny-by-default)
+- **TLS Everywhere** — تشفير لجميع حركة المرور الداخلية والخارجية
+- **Secrets Management** — استخدام AWS Secrets Manager لبيانات الاعتماد الحساسة
+
+
+ ### التحكم في الوصول
+
+
+- **RBAC** — التحكم في الوصول المستند إلى الأدوار في Kubernetes لجميع العمليات
+- **SSO Integration** — تكامل تسجيل الدخول الأحادي مع موفّر الهوية المؤسسي
+- **Audit Logging** — الاحتفاظ بسجلات وصول كاملة لأغراض الامتثال
+
+---
+
+
+ ## التعافي من الكوارث
+
+
+
+ ### أهداف الاستعادة
+
+
+| المقياس | الهدف | الوضع الحالي |
+|--------|--------|---------|
+| **RTO** (هدف زمن الاستعادة) | < 15 دقيقة | ~5 دقائق |
+| **RPO** (هدف نقطة الاستعادة) | < 1 دقيقة | نسخ متماثل في الوقت الحقيقي |
+
+
+ ### ميزات المرونة
+
+
+- **النسخ المتماثل متعدد مناطق التوافر** — تُكرَّر البيانات عبر مناطق توافر متعددة
+- **التحويل التلقائي عند التعطّل** — فحوصات السلامة في Route 53 تُطلِق تحويل مسار DNS تلقائيًا
+- **عمليات نشر متدرجة** — عمليات نشر دون توقّف عن الخدمة مع تراجع تلقائي
+- **النسخ الاحتياطي والاستعادة** — نسخ احتياطية يومية تلقائية مع استعادة إلى نقطة زمنية محددة
+
+---
+
+
+ ## ضمانات موثوقية بمستوى الإنتاج
+
+
+
+ ### لماذا تُعدّ بنيتنا التحتية صلبة للغاية
+
+
+تُختبَر بنية Benzinga التحتية في بيئات الإنتاج **وعلى نطاق واسع**، حيث تتعامل مع ملايين الطلبات اليومية مع موثوقية مثبتة:
+
+
+ ### التميّز في المراقبة وقابلية الملاحظة
+
+
+يضمن **نظام المراقبة الشامل لدينا** اكتشاف المشكلات وحلّها قبل أن تؤثر في أعمالك:
+
+
+ ### ثقة العملاء: ماذا يعني هذا بالنسبة لك
+
+
+عند دمجك مع واجهات برمجة التطبيقات API الخاصة بـ Benzinga، فإنك تتصل ببنية تحتية **جاهزة للإنتاج** مدعومة بـ:
+
+| الميزة | فائدة العميل |
+|---------|----------------|
+| **تكرار على عدة مناطق توفّر (Multi-AZ)** | يبقى تطبيقك متصلًا عبر الإنترنت حتى أثناء انقطاعات مناطق التوفّر في AWS |
+| **التحجيم التلقائي** | تتم معالجة طلباتك بسلاسة أثناء ارتفاعات الزيارات بدون فرض قيود على المعدّل (Rate Limiting) |
+| **مراقبة على مدار الساعة (24/7)** | يتم اكتشاف المشكلات وحلها بواسطة المهندسين قبل أن تلاحظ أي تدهور |
+| **نشر بدون توقّف للخدمة (Zero-Downtime)** | تحديثاتنا لا تع interromp توفّر خدمتك أبدًا |
+| **سجل تدقيق كامل** | يتم تتبّع كل عملية نشر ومراجعتها، مع إمكانية التراجع الفوري عنها |
+| **تنبيهات استباقية** | يتم حل 95% من المشكلات المحتملة قبل تأثيرها على العملاء |
+
+
+ ## الملخص
+
+
+توفّر بنية Benzinga التحتية **موثوقية بمستوى المؤسسات** من خلال:
+
+
+ ## Descripción general
+
+
+Las calificaciones de consenso ofrecen una visión consolidada del sentimiento de los analistas sobre una acción, al combinar las calificaciones individuales de los analistas en una métrica única y fácil de entender. Esta guía explica cómo calculamos las calificaciones de consenso para ayudarle a tomar decisiones de inversión con fundamento.
+
+
+ ## Cómo se calculan las recomendaciones de consenso
+
+
+
+ ### Paso 1: Recopilación de calificaciones de analistas
+
+
+Recopilamos todas las calificaciones de analistas disponibles para una acción determinada. Cada calificación incluye:
+
+* **Nombre del analista** y **Nombre de la firma**
+* **Calificación** (p. ej., Strong Buy, Buy, Hold, Sell, Strong Sell)
+* **Precio objetivo** - El precio de la acción proyectado por el analista
+* **Fecha de actualización** - Cuándo se emitió la calificación
+
+
+ ### Paso 2: Filtrado de analistas únicos
+
+
+Para garantizar la precisión y evitar contar dos veces, solo incluimos la **calificación más reciente** de cada combinación única de analista y firma.
+
+**Ejemplo:** Si el analista de Morgan Stanley John Doe ha calificado una acción varias veces, solo se incluye su calificación más reciente en el cálculo.
+
+
+ ### Paso 3: Clasificación de recomendaciones
+
+
+Las recomendaciones de los analistas se agrupan en cinco categorías estándar:
+
+| Categoría | Valor numérico |
+|----------|---------------|
+| **Venta fuerte** | 1 |
+| **Venta** | 2 |
+| **Mantener** | 3 |
+| **Compra** | 4 |
+| **Compra fuerte** | 5 |
+
+
+ ### Paso 4: Agrupar las calificaciones
+
+
+Contamos cuántos analistas entran en cada categoría.
+
+**Ejemplo de agregación:**
+
+* Compra fuerte: 8 analistas
+* Compra: 12 analistas
+* Mantener: 5 analistas
+* Venta: 2 analistas
+* Venta fuerte: 1 analista
+
+**Total:** 28 analistas únicos
+
+
+ ### Paso 5: Calcular el valor de la calificación de consenso
+
+
+El valor de la calificación de consenso se calcula como un promedio ponderado:
+
+```
+Consensus Value = (Strong Buy × 5 + Buy × 4 + Hold × 3 + Sell × 2 + Strong Sell × 1) / Total Analysts
+```
+
+**Con el ejemplo anterior:**
+
+```
+Consensus Value = (8×5 + 12×4 + 5×3 + 2×2 + 1×1) / 28
+Consensus Value = (40 + 48 + 15 + 4 + 1) / 28
+Consensus Value = 108 / 28
+Consensus Value = 3.86
+```
+
+
+ ### Paso 6: Determinar la calificación de consenso
+
+
+El valor de consenso se redondea al entero más cercano y se asigna una calificación:
+
+| Valor de consenso | Calificación estándar | Calificación simplificada |
+|----------------|-----------------|-------------------|
+| **1** | Venta fuerte | Venta |
+| **2** | Venta | Venta |
+| **3** | Mantener | Mantener |
+| **4** | Compra | Compra |
+| **5** | Compra fuerte | Compra |
+
+**En nuestro ejemplo:** 3.86 se redondea a **4**, lo que da como resultado una calificación de consenso de **«Compra»**.
+
+***
+
+
+ ## Opciones de visualización
+
+
+
+ ### Calificaciones estándar vs. simplificadas
+
+
+Ofrecemos dos formatos de presentación:
+
+**Estándar (5 categorías):**
+
+* Venta fuerte, Venta, Mantener, Compra, Compra fuerte
+
+**Simplificado (3 categorías):**
+
+* Venta (combina Venta fuerte + Venta)
+* Mantener
+* Compra (combina Compra + Compra fuerte)
+
+
+ ### Recuento frente a porcentaje
+
+
+**Recuento:**
+Muestra el número exacto de analistas en cada categoría.
+
+**Porcentaje:**
+Muestra la proporción de analistas en cada categoría, redondeada a porcentajes enteros que suman exactamente el 100 %.
+
+**Ejemplo:**
+
+* Compra: 71 % (20 analistas)
+* Mantener: 18 % (5 analistas)
+* Venta: 11 % (3 analistas)
+
+***
+
+
+ ## Cálculo del precio objetivo
+
+
+
+ ### Precio objetivo de consenso
+
+
+La media de todos los precios objetivo de los analistas:
+
+```
+PO Consenso = Suma de todos los Precios Objetivo / Número de Analistas
+```
+
+
+ ### Precios objetivo mínimo y máximo
+
+
+* **Precio objetivo mínimo:** El precio objetivo más bajo entre todos los analistas
+* **Precio objetivo máximo:** El precio objetivo más alto entre todos los analistas
+
+Estos valores definen un rango que refleja el espectro de expectativas de los analistas.
+
+***
+
+
+ ## Cómo interpretar las métricas
+
+
+
+ ### Recuento total de analistas vs. recuento único de analistas
+
+
+* **Recuento total de analistas:** Todas las calificaciones recopiladas (puede incluir múltiples calificaciones del mismo analista)
+* **Recuento único de analistas:** El número de combinaciones únicas analista–firma (empleado para los cálculos)
+
+El recuento único garantiza que la opinión de cada analista se cuente solo una vez, lo que proporciona un consenso más preciso.
+
+***
+
+
+ ## Consideraciones importantes
+
+
+
+ ### Actualización de las calificaciones
+
+
+Las calificaciones de consenso reflejan las opiniones más recientes de los analistas. La marca de tiempo **Updated At** indica cuándo se calculó por última vez el consenso.
+
+
+ ### Profundidad de cobertura
+
+
+Las calificaciones de consenso son más fiables cuando se basan en un mayor número de analistas distintos. Las acciones con cobertura limitada de analistas (por debajo de 3‑5 analistas) pueden tener calificaciones de consenso menos estables.
+
+
+ ### Distribución de recomendaciones
+
+
+Presta atención a la distribución de las recomendaciones, no solo al consenso. Una acción con 50% de recomendaciones de Compra y 50% de recomendaciones de Venta tendrá un consenso de "Mantener", pero esto oculta un desacuerdo significativo entre los analistas.
+
+***
+
+
+ ## Ejemplo de cálculo paso a paso
+
+
+Veamos un ejemplo completo con **XYZ Corporation**:
+
+
+ ### Datos en bruto (10 analistas)
+
+
+| Analista | Firma | Recomendación | Precio objetivo |
+|---------|------|--------|--------------|
+| Analista A | Goldman Sachs | Comprar | $150 |
+| Analista B | JP Morgan | Compra fuerte | $165 |
+| Analista C | Morgan Stanley | Comprar | $155 |
+| Analista D | Bank of America | Mantener | $140 |
+| Analista E | Citigroup | Compra fuerte | $170 |
+| Analista F | Wells Fargo | Comprar | $152 |
+| Analista G | Deutsche Bank | Mantener | $145 |
+| Analista H | Barclays | Vender | $130 |
+| Analista I | UBS | Comprar | $158 |
+| Analista J | Credit Suisse | Compra fuerte | $168 |
+
+
+ ### Cálculo paso a paso
+
+
+**1. Filtrar por analistas únicos:** Las 10 calificaciones son distintas (se usan 10 analistas)
+
+**2. Agregar recuentos:**
+
+* Strong Buy: 3
+* Buy: 4
+* Hold: 2
+* Sell: 1
+* Strong Sell: 0
+
+**3. Calcular el valor de consenso:**
+
+```
+(3×5 + 4×4 + 2×3 + 1×2 + 0×1) / 10 = (15 + 16 + 6 + 2 + 0) / 10 = 3.9
+```
+
+**4. Determinar el consenso:** 3.9 se redondea a **4 = "Compra"**
+
+**5. Precios objetivo (PO):**
+
+* PO de consenso: (150+165+155+140+170+152+145+130+158+168) / 10 = **$153.30**
+* PO mínima: **$130**
+* PO máxima: **$170**
+
+**6. Desglose porcentual:**
+
+* Compra: 70% (Compra fuerte 30% + Compra 40%)
+* Mantener: 20%
+* Vender: 10%
+
+
+ ### Salida de la calificación de consenso definitiva
+
+
+```json
+{
+ "consensusRating": "BUY",
+ "consensusRatingValue": 3.9,
+ "consensusPriceTarget": 153.30,
+ "priceTargetLow": 130,
+ "priceTargetHigh": 170,
+ "totalAnalysts": 10,
+ "uniqueAnalysts": 10,
+ "lastUpdated": "2026-01-16T10:30:00Z"
+}
+```
+
+***
+
+
+ ## Preguntas frecuentes
+
+
+
+ {/* En progreso */}
+
+
+
+---
+
+
+
+
+ {/* Planificado */}
+
+
+
+
+ En progreso
+
+
+
+
+
+
+
+ Transcripciones en formato PDF
+ Formato PDF descargable de transcripciones de llamadas de conferencia.
+
+
+ Cobertura histórica ampliada de transcripciones
+ Ampliación de la disponibilidad de datos históricos de transcripciones de llamadas de conferencia.
+
+
+
+ {/* Pendientes */}
+
+
+
+
+ Previsto
+
+
+
+
+
+
+
+ Panel de monitoreo mejorado
+ Panel orientado al cliente con monitoreo para todos los servicios.
+
+
+
+ Optimizaciones del motor de traducción
+ Mejoras de rendimiento y calidad en los servicios de traducción.
+
+
+ Integración de Security Master para noticias
+ Integración del Security Master interno para mejorar las capacidades de consulta.
+
+
+
+ {/* Completado */}
+
+
+
+
+ Backlog
+
+
+
+
+
+
+
+ Go SDK
+ Biblioteca cliente oficial de Go.
+
+
+ WebSocket para todos los calendars
+ Soporte de transmisión en tiempo real para todos los endpoints de calendar.
+
+
+
+
+
+ Completado
+
+
+
+
+
+
+
+ Security Master interno
+ Security master centralizado para mejorar la consistencia de los datos.
+
+
+
+ Streaming TCP
+ Conexiones TCP de baja latencia para datos en tiempo real.
+
+
+
+ Transcripciones de llamadas de conferencia
+ Transcripciones completas con identificación de oradores.
+
+
+
+ Motor de webhooks
+ Entrega de datos mediante push.
+
+
+ Kit de desarrollo de software (SDK) de Java
+ Biblioteca de cliente oficial de Java.
+
- ## Arquitectura de alto rendimiento con Go y Kafka
+
-
+
+
+ Confiabilidad probada en producción con redundancia multi-AZ
+
+
+ Observabilidad en tiempo real con Coralogix y Datadog
+
+
+ Despliegues sin tiempo de inactividad con escalado automático inteligente
+
+
-
+ ## Descripción general
-Basada en **Go (Golang)** por su capacidad de concurrencia y velocidad, la infraestructura de Benzinga gestiona de forma eficiente grandes volúmenes de tráfico de datos financieros. Las canalizaciones de datos y el streaming en tiempo real están impulsados por **Kafka**, lo que permite una ingesta, procesamiento y distribución de datos rápidos con una latencia mínima. Esta arquitectura garantiza escalabilidad y robustez en implementaciones globales, satisfaciendo las exigencias de la entrega de datos financieros en tiempo real.
+Nuestra plataforma está construida sobre una arquitectura moderna, nativa de la nube, que aprovecha servicios administrados de AWS, orquestación con Kubernetes y prácticas de despliegue GitOps. Esta **infraestructura de nivel de producción** procesa millones de solicitudes de API diariamente mientras mantiene tiempos de respuesta por debajo de 100 ms, con observabilidad completa y escalado automatizado.
-
-
-
+
- ## Acceso a datos en tiempo real mediante WebSockets y API REST
+
+
+---
+
+
+
+ Servicios implementados en varias Zonas de Disponibilidad para tolerancia a fallos
+
+
+ Una Virtual Private Cloud (VPC) aislada con políticas estrictas de grupos de seguridad
+
+
+ DNS global con comprobaciones de estado y enrutamiento de conmutación por error automático
+
+
+ Plano de control de Kubernetes administrado por AWS con un SLA del 99,95 %
+
+
+
+
+
+ Validación de claves de API y verificación de tokens JWT en el perímetro de la red
+
+
+ Limitación de solicitudes por cliente para garantizar una asignación equitativa de recursos
+
+
+ Distribución inteligente del tráfico entre pods de servicio en buen estado
+
+
+ Todo el tráfico se cifra con TLS 1.3; los certificados se renuevan automáticamente
+
+
+
+
+ ## Infraestructura principal
+
+
+
+ ### Base en la nube de AWS
+
+
+Nuestra infraestructura se ejecuta completamente en **Amazon Web Services (AWS)**, aprovechando:
+
+
+ ### Infraestructura de Kubernetes
+
+
+Operamos **dos clústeres de Kubernetes dedicados** para garantizar despliegues seguros y aislamiento de entornos:
+
+| Entorno | Propósito | Flujo de despliegue |
+|-------------|---------|-----------------|
+| **Clúster de Staging** | Pruebas de desarrollo, validación de QA, pruebas de integración | Los cambios de código se despliegan primero para su validación |
+| **Clúster de Producción** | Tráfico de clientes en producción con garantías de SLA | Solo se promueven versiones ya verificadas |
+
+
+ #### Componentes clave de Kubernetes
+
+
+- **Karpenter** — Autoescalador de nodos nativo de AWS que aprovisiona recursos de cómputo del tamaño adecuado en segundos, no minutos
+- **Horizontal Pod Autoscaler (HPA)** — Escalado automático de pods basado en CPU, memoria y métricas personalizadas
+- **Kong Gateway** — API gateway empresarial que gestiona tráfico de entrada/salida, limitación de solicitudes (rate limiting) y autenticación
+- **ArgoCD** — Controlador de despliegue basado en GitOps para lanzamientos declarativos y auditables
+
+---
+
+
+ ## API Gateway y gestión del tráfico
+
+
+
+ ### Kong Gateway
+
+
+Todo el tráfico de la API pasa a través de **Kong Gateway**, que proporciona:
+
+
+ ### Route 53 DNS
-Las API de Benzinga admiten tanto el protocolo **WebSocket** como **REST**, lo que permite a los clientes acceder a datos en tiempo real, así como realizar solicitudes bajo demanda. Las conexiones WebSocket son ideales para aplicaciones que requieren flujos continuos de datos, como cotizaciones de mercado en vivo y datos de negociación, mientras que las API REST cubren una amplia gama de solicitudes de datos históricos, fundamentos de empresas, noticias y análisis.
+AWS Route 53 proporciona:
+
+- **Enrutamiento global basado en latencia** — Los usuarios son dirigidos automáticamente al endpoint más rápido
+- **Comprobaciones de estado (health checks)** — Supervisión continua con conmutación por error automática en caso de fallo
+- **SLA de tiempo de actividad del 100%** — Garantía de disponibilidad respaldada por AWS para la resolución DNS
-
- ### Aspectos destacados de la API
+---
+
+
+ ## Pipeline de CI/CD
-- **Datos de mercado en tiempo real**: Transmita cotizaciones en vivo, operaciones y otros datos de mercado esenciales en tiempo real.
-- **Datos históricos**: Acceda a datos históricos, incluidos datos de barras, cotizaciones y desempeño del mercado a lo largo del tiempo.
-- **Noticias y análisis**: Manténgase al día con noticias en tiempo real y análisis que mueven el mercado.
-- **Fundamentos de la empresa**: Obtenga métricas financieras esenciales, como ingresos, beneficios y ratios clave.
+Nuestro pipeline de despliegue aplica estrictos controles de calidad antes de que cualquier código llegue a producción.
-
- ## Eficiencia en el Almacenamiento y la Búsqueda de Datos con Elasticsearch
+
-
-
-
+ ### Flujo de desarrollo
-Para un almacenamiento y una recuperación de datos eficientes, Benzinga utiliza **Elasticsearch** como componente central de su sistema de búsqueda e indexación. Elasticsearch permite un acceso rápido tanto a datos estructurados como no estructurados, lo que garantiza que los usuarios puedan consultar rápidamente grandes conjuntos de datos, como datos históricos y archivos de noticias, con tiempos de respuesta del orden de milisegundos. Esta arquitectura también admite capacidades de analítica, lo que permite a los clientes analizar y extraer información valiosa de los datos.
+```mermaid
+flowchart LR
+ A[Developer Commit] --> B[GitLab CI Pipeline]
+ B --> C{Linting & Tests}
+ C -->|Pass| D[Build Container Image]
+ C -->|Fail| E[Reject & Notify]
+ D --> F[Push to Registry]
+ F --> G[Peer Review Required]
+ G -->|2 Approvals| H[Update GitOps Repo]
+ H --> I[ArgoCD Sync]
+ I --> J[Deploy to Staging]
+ J -->|Validated| K[Promote to Production]
+```
-
-
-
-
-
- ## Infraestructura basada en microservicios para escalabilidad
+
+ ### Etapas del pipeline
-La arquitectura de Benzinga se fundamenta en un enfoque de **microservicios**, donde cada servicio gestiona una función específica —como ingesta de datos, procesamiento, almacenamiento o distribución—. Este enfoque modular mejora la escalabilidad, ya que permite escalar cada componente de forma independiente según la demanda. Además, los microservicios se comunican mediante protocolos ligeros, lo que garantiza baja latencia y resiliencia en todo el sistema.
+| Etapa | Descripción | Control de calidad |
+|-------|-------------|-------------------|
+| **Lint** | Verificaciones de estilo de código y análisis estático | Debe cumplir todas las reglas |
+| **Pruebas unitarias** | Ejecución de la suite de pruebas automatizadas | 100% de pruebas aprobadas |
+| **Escaneo de seguridad** | Análisis de vulnerabilidades del contenedor | Sin CVE de severidad crítica/alta |
+| **Build** | Creación de imagen de Docker etiquetada con el SHA del commit | Build satisfactorio |
+| **Revisión por pares** | Revisión de código manual por 2 desarrolladores | Se requieren dos aprobaciones |
+| **Actualización GitOps** | Etiqueta de imagen actualizada en el repositorio de ArgoCD | Promoción manual |
-
- ## Entrega con CDN para imágenes y contenido estático
+
+ ### GitOps con ArgoCD
-Para garantizar que las imágenes, logotipos y otros recursos estáticos se entreguen rápidamente, Benzinga utiliza una **CDN** (red de entrega de contenido). Esta arquitectura reduce los tiempos de carga y minimiza la latencia al almacenar en caché los recursos estáticos cerca de los usuarios, lo que asegura que las imágenes y los archivos se carguen casi al instante, independientemente de la ubicación geográfica.
+Todos los despliegues se gestionan mediante **ArgoCD**, siguiendo los principios de GitOps:
+
+- **Declarativo** — Estado deseado definido en Git, única fuente de verdad
+- **Sincronización automática** — ArgoCD detecta cambios y los aplica automáticamente
+- **Capacidad de reversión** — Reversión instantánea al deshacer commits de Git
+- **Registro de auditoría** — Historial completo de despliegues mediante el registro de commits de Git
-
- ## Beneficios clave de la arquitectura de Benzinga
+
+ Cada cambio en producción se puede rastrear hasta un commit específico de Git, con revisión por pares y aprobador, lo que garantiza una auditabilidad completa para los requisitos de cumplimiento.
+
+
+---
+
+
+ ## Arquitectura de escalado automático
-- **Escalabilidad**: Diseñada para escalar horizontalmente, con soporte para millones de solicitudes por minuto y grandes volúmenes de conexiones WebSocket concurrentes.
-- **Alta disponibilidad**: Sistemas redundantes y componentes distribuidos geográficamente garantizan el tiempo de actividad y la disponibilidad de los datos.
-- **Consistencia de datos**: Kafka y Elasticsearch en conjunto proporcionan un flujo y una recuperación de datos consistentes, con mecanismos de conmutación por error confiables.
-- **Baja latencia**: Optimizada para entregar datos con una latencia mínima, aprovechando el rendimiento de Go, el streaming de Kafka y las capacidades en tiempo real de WebSocket.
+Nuestra infraestructura se escala automáticamente en varios niveles para manejar picos de tráfico.
-
- ## Flexibilidad de despliegue e integración con la infraestructura
+
+ ### Autoescalado a nivel de pods (HPA)
-La arquitectura de Benzinga ofrece opciones de despliegue flexibles para satisfacer las diversas necesidades de sus clientes:
+Cada despliegue de servicio incluye la configuración de Horizontal Pod Autoscaler:
+
+```yaml
+# Ejemplo de configuración de HPA
+apiVersion: autoscaling/v2
+kind: HorizontalPodAutoscaler
+spec:
+ minReplicas: 3
+ maxReplicas: 50
+ metrics:
+ - type: Resource
+ resource:
+ name: cpu
+ target:
+ type: Utilization
+ averageUtilization: 70
+```
-- **Servicio en la nube gestionado**: Para los clientes que buscan una experiencia fluida, Benzinga ofrece un servicio en la nube totalmente gestionado, que incluye escalado automático y mantenimiento.
-- **Opción autoalojada**: Para quienes necesitan más control, la arquitectura de Benzinga puede adaptarse para despliegues en las instalaciones (on-premises) o en nubes privadas, garantizando plena propiedad de los datos y cumplimiento de las regulaciones locales.
+**Condiciones de escalado:**
-
- ### Alcance global con edge caching
+* Uso de CPU > 70%
+* Uso de memoria > 80%
+* Métricas personalizadas (profundidad de la cola de solicitudes, percentiles de latencia)
+
+
+
+
+ **Trazas distribuidas y registros (logging)**
+ - Agregación de registros en tiempo real de todos los servicios
+ - Trazas distribuidas a través de microservicios
+ - Monitoreo de rendimiento de aplicaciones (APM)
+ - Seguimiento de solicitudes de extremo a extremo con IDs de correlación
+ - Reconocimiento de patrones en los registros y detección de anomalías
+ - Paneles personalizados para métricas de negocio
+
+
+ **Alertas y monitoreo sintético**
+ - Pruebas continuas 24/7 de endpoints de API
+ - Monitoreo sintético multirregión
+ - Seguimiento de tiempo de respuesta y disponibilidad
+ - Alertas automatizadas con enrutamiento inteligente
+ - Seguimiento de indicadores de nivel de servicio (SLI)
+ - Detección de regresiones de rendimiento
+
+
+
+
+
+ Todos los registros de las aplicaciones de cada servicio, pod y contenedor se agregan en tiempo real, lo que proporciona acceso instantáneo a la información de depuración en toda la infraestructura.
+
+
+ Cada solicitud de API se rastrea de extremo a extremo a través de microservicios, balanceadores de carga, bases de datos y servicios externos. Esto permite un análisis rápido de la causa raíz de problemas de rendimiento o errores.
+
+
+ Detección automática de errores con trazas de pila, información contextual y número de usuarios afectados. Los errores se categorizan por gravedad e impacto.
+
+
+ Métricas en tiempo real sobre tiempos de respuesta de la API, rendimiento, tasas de error y utilización de recursos en todos los servicios.
+
+
+
+**Características clave de Coralogix en producción:**
+
+- **Política de retención**: 30 días de almacenamiento en caliente para acceso inmediato, 90 días de archivo para cumplimiento normativo
+- **Rendimiento de consultas**: Consultas en menos de un segundo sobre miles de millones de entradas de registro
+- **Integración de alertas**: Enrutamiento automatizado a canales de Slack e ingenieros de guardia
+- **Paneles personalizados**: Métricas específicas del negocio visibles para las partes interesadas en tiempo real
+
+
+
+ Las pruebas automatizadas se ejecutan cada 60 segundos desde múltiples regiones geográficas, validando la disponibilidad de la API, los tiempos de respuesta y la precisión de los datos antes de que los clientes se vean afectados.
+
+
+ La detección de anomalías basada en aprendizaje automático identifica patrones inusuales en las métricas, activando alertas antes de que los problemas afecten a los clientes.
+
+
+ Seguimiento en tiempo real de los objetivos de nivel de servicio (SLO) con generación de informes automatizados sobre objetivos de disponibilidad del 99,9 %.
+
+
+ Monitorización continua de los percentiles de latencia p50, p95 y p99 para garantizar un rendimiento constante.
+
+
+
+**Las pruebas sintéticas de Datadog incluyen:**
+
+| Tipo de prueba | Frecuencia | Regiones | Métricas supervisadas |
+|----------------|------------|----------|------------------------|
+| **Comprobaciones de estado de API** | Cada 60 s | 5 regiones globales | Disponibilidad, tiempo de respuesta, códigos de estado |
+| **Pruebas de precisión de datos** | Cada 5 min | 3 regiones | Frescura de los datos, validación de esquema, integridad |
+| **Pruebas de rendimiento** | Cada 60 s | 5 regiones | Latencia (p50/p95/p99), throughput, tasas de error |
+| **Pruebas de autenticación** | Cada 5 min | 2 regiones | Validación de clave de API, rate limiting, flujos OAuth |
+
+
+
+ **Alertas críticas**
+
+ * Incidentes P1/P2 que requieren acción inmediata
+ * Alertado automático del ingeniero de guardia
+ * Métricas en tiempo real y enlaces a runbooks
+ * Asignación de un responsable del incidente
+
+
+
+ **Información de rendimiento**
+
+ * Resúmenes diarios del estado
+ * Alertas de planificación de capacidad
+ * Notificaciones de tendencias de rendimiento
+ * Advertencias de detección de anomalías
+
+
+
+**Flujo de alertas de Slack:**
+
+```mermaid
+flowchart LR
+ A[Alerta Activada] --> B{Nivel de Severidad}
+ B -->|P1/P2| C[#alerts-production]
+ B -->|P3/P4| D[#monitoring-insights]
+ C --> E[Ingeniero de Guardia Notificado]
+ C --> F[Canal de Incidente Creado]
+ F --> G[Desarrollador Asignado]
+ G --> H[Investigación de Causa Raíz]
+ H --> I[Corrección Implementada]
+ I --> J[Informe Post-Mortem]
+```
+
+
+
+ Todos los incidentes P1/P2 activan un **paging automatizado inmediato** a los ingenieros de guardia con cobertura 24/5.
+
+
+
+ Nuestros sistemas de monitoreo han detectado y resuelto **el 95% de los problemas potenciales antes de que afecten a los clientes** mediante alertas proactivas y remediación automatizada.
+
+
+---
+
+
+
+ **Estadísticas de producción**
+ - Más de 10 millones de solicitudes de API procesadas diariamente
+ - Tiempo de respuesta medio inferior a 100 ms
+ - 99,9 % de disponibilidad histórica
+ - Sin pérdida de datos en más de 3 años
+
+
+ **Excelencia operativa**
+ - Cobertura de ingeniería on-call 24/5/365
+ - Conmutación por error automatizada y autorrecuperación
+ - Redundancia multirregión
+
+
+
+
+
+ Cada solicitud, entrada de log y métrica se sigue de extremo a extremo usando trazas distribuidas de Coralogix y registros centralizados
+
+
+ El monitoreo sintético de Datadog prueba las APIs cada 60 segundos desde múltiples regiones, y alerta sobre problemas antes de que afecten a los clientes
+
+
+ La integración automatizada con Slack enruta las alertas a canales dedicados con asignación inmediata de desarrolladores y seguimiento de la resolución
+
+
+ El análisis postmortem de todos los incidentes garantiza que los problemas no vuelvan a ocurrir, con medidas preventivas automatizadas
+
+
+
+
+ **Listo para producción**: Nuestra infraestructura ha procesado más de **mil millones de solicitudes de API** con un 99,9% de disponibilidad y mantiene una latencia inferior a 100 ms para la entrega de datos financieros en tiempo real.
+
+
+---
+
+
+
+ AWS EKS con implementación multi-AZ y plano de control gestionado que garantiza el máximo tiempo de actividad
+
+
+ Despliegues gestionados con ArgoCD, con registro de auditoría completo y capacidades de reversión inmediata
+
+
+ Karpenter + HPA para una gestión de capacidad transparente que maneja automáticamente los picos de tráfico
+
+
+ Trazado/registro con Coralogix + alertas/pruebas sintéticas con Datadog e integración con Slack para una respuesta rápida ante incidentes
+
+
+ Ingenieros dedicados de guardia
+
+
+ Defensa en profundidad con cifrado, RBAC y aislamiento de red para proteger sus datos
+
+
+
+
+ **Su éxito es nuestra prioridad**: Si tiene preguntas sobre nuestra infraestructura, las garantías de SLA o desea hablar de sus requisitos específicos de fiabilidad, póngase en contacto con su representante de cuenta o envíe un correo electrónico a [support@benzinga.com](mailto:support@benzinga.com).
+
\ No newline at end of file
diff --git a/es/openapi/calendar_api.spec.yml b/es/openapi/calendar_api.spec.yml
index 59775b44..ea62fd61 100644
--- a/es/openapi/calendar_api.spec.yml
+++ b/es/openapi/calendar_api.spec.yml
@@ -2974,14 +2974,19 @@ components:
calendarapi.AggregateRating:
properties:
buy:
+ example: 10
type: integer
hold:
+ example: 3
type: integer
sell:
+ example: 1
type: integer
strong_buy:
+ example: 5
type: integer
strong_sell:
+ example: 0
type: integer
type: object
calendarapi.AnalystInsightsJSON:
@@ -3021,22 +3026,31 @@ components:
aggregate_ratings:
$ref: "#/components/schemas/calendarapi.AggregateRating"
aggregate_type:
+ example: 90D
type: string
consensus_price_target:
+ example: 195.5
type: number
consensus_rating:
+ example: Buy
type: string
consensus_rating_val:
+ example: 4.2
type: number
high_price_target:
+ example: 225
type: number
low_price_target:
+ example: 150
type: number
total_analyst_count:
+ example: 19
type: integer
unique_analyst_count:
+ example: 15
type: integer
updated_at:
+ example: 2024-01-09T16:00:00Z
type: string
type: object
calendarapi.DividendJSON:
@@ -3122,40 +3136,53 @@ components:
calendarapi.InsiderTransaction:
properties:
accession_number:
+ example: 0001127602-24-000123
type: string
company_cik:
+ example: 320193
type: string
company_name:
+ example: Apple Inc.
type: string
company_symbol:
+ example: AAPL
type: string
filing_date:
+ example: 2024-01-09T00:00:00Z
type: string
footnotes:
items:
$ref: "#/components/schemas/calendarapi.SECFootnotes"
type: array
form_type:
+ example: "4"
type: string
html_url:
+ example: https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000320193
type: string
id:
+ example: 64a1b2c3d4e5f6789012345
type: string
is_10b5:
+ example: true
type: boolean
owner:
$ref: "#/components/schemas/calendarapi.Owner"
remaining_shares:
+ example: "125000"
type: string
remaining_underlying_shares:
+ example: "50000"
type: string
traded_percentage:
+ example: "15.5"
type: string
transactions:
items:
$ref: "#/components/schemas/calendarapi.Transaction"
type: array
updated:
+ example: 1704758400
type: integer
type: object
calendarapi.InsiderTransactionFilingDoc:
@@ -3192,18 +3219,25 @@ components:
calendarapi.Owner:
properties:
insider_cik:
+ example: "0001234567"
type: string
insider_name:
+ example: Tim Cook
type: string
insider_title:
+ example: Chief Executive Officer
type: string
is_director:
+ example: true
type: boolean
is_officer:
+ example: true
type: boolean
is_ten_percent_owner:
+ example: false
type: boolean
raw_signature:
+ example: /s/ Tim Cook
type: string
type: object
calendarapi.RatingJSON:
@@ -3249,8 +3283,10 @@ components:
calendarapi.SECFootnotes:
properties:
id:
+ example: F1
type: string
text:
+ example: Shares were sold pursuant to a Rule 10b5-1 trading plan
type: string
type: object
calendarapi.SplitJSON:
@@ -3264,40 +3300,58 @@ components:
calendarapi.Transaction:
properties:
acquired_or_disposed:
+ example: D
type: string
conversion_exercise_price_derivative:
+ example: "150.25"
type: string
date_deemed_execution:
+ example: 2024-01-09T00:00:00Z
type: string
date_exercisable:
+ example: 2024-01-09T00:00:00Z
type: string
date_expiration:
+ example: 2025-01-09T00:00:00Z
type: string
date_transaction:
+ example: 2024-01-09T00:00:00Z
type: string
is_derivative:
+ example: false
type: boolean
ownership:
+ example: Direct
type: string
post_transaction_quantity:
+ example: "250000"
type: string
price_per_share:
+ example: "150.25"
type: string
remaining_underlying_shares:
+ example: "50000"
type: string
security_title:
+ example: Common Stock
type: string
shares:
+ example: "10000"
type: string
transaction_code:
+ example: S
type: string
transaction_id:
+ example: TXN-20240109-001
type: string
underlying_security_title:
+ example: Common Stock
type: string
underlying_shares:
+ example: "10000"
type: string
voluntarily_reported:
+ example: false
type: boolean
type: object
servers:
diff --git a/es/openapi/data-api-proxy_api.spec.yml b/es/openapi/data-api-proxy_api.spec.yml
index dad0a26d..99899462 100644
--- a/es/openapi/data-api-proxy_api.spec.yml
+++ b/es/openapi/data-api-proxy_api.spec.yml
@@ -1480,6 +1480,8 @@ components:
type: object
bzhttp.ErrorCode:
enum:
+ - unsupported_message_type
+ - database_query_error
- json_unmarshaling_error
- no_data_found
- no_matching_endpoint
@@ -1491,10 +1493,10 @@ components:
- failed_dependency
- service_unavailable
- upstream_api_error
- - unsupported_message_type
- - database_query_error
type: string
x-enum-varnames:
+ - ErrorUnsupportedMessageType
+ - ErrorDBQueryError
- ErrorJSONUnmarshaling
- ErrorNoDataFound
- ErrorNoMatchingEndpoint
@@ -1506,8 +1508,6 @@ components:
- ErrorFailedDependency
- ErrorServiceUnavailable
- ErrorUpstreamAPIError
- - ErrorUnsupportedMessageType
- - ErrorDBQueryError
bzhttp.Resp:
properties:
data:
diff --git a/es/openapi/logo-api_api.spec.yml b/es/openapi/logo-api_api.spec.yml
index 54f8eb35..8c956185 100644
--- a/es/openapi/logo-api_api.spec.yml
+++ b/es/openapi/logo-api_api.spec.yml
@@ -157,6 +157,13 @@ paths:
name: max_width
schema:
type: string
+ - description: Si es true, agrega el parámetro de consulta flutter_compatible=true
+ a las URL SVG para garantizar la compatibilidad con la biblioteca
+ flutter_svg.
+ in: query
+ name: flutter_compatible
+ schema:
+ type: boolean
responses:
"200":
description: Respuesta exitosa con un array de objetos LogoClientResponse en el
diff --git a/es/openapi/newsquantified-api_api.spec.yml b/es/openapi/newsquantified-api_api.spec.yml
index 9c4285c7..c9c713b7 100644
--- a/es/openapi/newsquantified-api_api.spec.yml
+++ b/es/openapi/newsquantified-api_api.spec.yml
@@ -121,8 +121,6 @@ components:
type: object
bzhttp.ErrorCode:
enum:
- - unsupported_message_type
- - database_query_error
- json_unmarshaling_error
- no_data_found
- no_matching_endpoint
@@ -134,10 +132,10 @@ components:
- failed_dependency
- service_unavailable
- upstream_api_error
+ - unsupported_message_type
+ - database_query_error
type: string
x-enum-varnames:
- - ErrorUnsupportedMessageType
- - ErrorDBQueryError
- ErrorJSONUnmarshaling
- ErrorNoDataFound
- ErrorNoMatchingEndpoint
@@ -149,6 +147,8 @@ components:
- ErrorFailedDependency
- ErrorServiceUnavailable
- ErrorUpstreamAPIError
+ - ErrorUnsupportedMessageType
+ - ErrorDBQueryError
bzhttp.Resp:
properties:
data:
diff --git a/es/openapi/ticker-trends-api_api.spec.yml b/es/openapi/ticker-trends-api_api.spec.yml
index 95d6b551..7ed8077e 100644
--- a/es/openapi/ticker-trends-api_api.spec.yml
+++ b/es/openapi/ticker-trends-api_api.spec.yml
@@ -201,8 +201,6 @@ components:
type: object
bzhttp.ErrorCode:
enum:
- - unsupported_message_type
- - database_query_error
- json_unmarshaling_error
- no_data_found
- no_matching_endpoint
@@ -214,10 +212,10 @@ components:
- failed_dependency
- service_unavailable
- upstream_api_error
+ - unsupported_message_type
+ - database_query_error
type: string
x-enum-varnames:
- - ErrorUnsupportedMessageType
- - ErrorDBQueryError
- ErrorJSONUnmarshaling
- ErrorNoDataFound
- ErrorNoMatchingEndpoint
@@ -229,6 +227,8 @@ components:
- ErrorFailedDependency
- ErrorServiceUnavailable
- ErrorUpstreamAPIError
+ - ErrorUnsupportedMessageType
+ - ErrorDBQueryError
bzhttp.Resp:
properties:
data:
diff --git a/gt-lock.json b/gt-lock.json
index 81eb663a..2e11ab58 100644
--- a/gt-lock.json
+++ b/gt-lock.json
@@ -45,19 +45,19 @@
},
"ee9d261f48c27ab14e838f7f43c24b328cf08468f1e9be291fe2d51df7db3f56": {
"es": {
- "updatedAt": "2026-01-16T09:12:32.840Z",
+ "updatedAt": "2026-01-28T15:20:51.599Z",
"postProcessHash": "a54a24a91226e02411065b7800d4ab13029836319cad2456677076f88629aa99"
},
"ja": {
- "updatedAt": "2026-01-16T09:12:32.843Z",
+ "updatedAt": "2026-01-28T15:20:51.601Z",
"postProcessHash": "6fd5617957de38bf025330c33db225310431dc5792a4278cbe517f932da7ba52"
},
"ko": {
- "updatedAt": "2026-01-16T09:12:32.932Z",
+ "updatedAt": "2026-01-28T15:20:51.639Z",
"postProcessHash": "c6f2ec7a1b3c137cf21b59dcb8fe928238fc905a696bfa6c079129b86d9dc4ff"
},
"ar": {
- "updatedAt": "2026-01-16T09:12:32.954Z",
+ "updatedAt": "2026-01-28T15:20:51.647Z",
"postProcessHash": "0014a34b977bea17d8f1bc5fa363550f612384f9b076c95bab01b9d8c6e2ac82"
}
}
@@ -105,19 +105,19 @@
},
"4206787938097b3f7cf80ae91a7a2432655b9d24e8ff01a6691a3240b69dc573": {
"es": {
- "updatedAt": "2026-01-16T09:12:32.457Z",
+ "updatedAt": "2026-01-28T15:20:51.503Z",
"postProcessHash": "03ca70cf659879498aeae3eb522c6a1a283f5be9473e494ea4e84d9d747d4385"
},
"ja": {
- "updatedAt": "2026-01-16T09:12:32.458Z",
+ "updatedAt": "2026-01-28T15:20:51.503Z",
"postProcessHash": "0eb4679f1c31253d8c49c9e8e5f035b4942c17cd61d95ccbe6680f9ddfbf34af"
},
"ko": {
- "updatedAt": "2026-01-16T09:12:32.633Z",
+ "updatedAt": "2026-01-28T15:20:51.573Z",
"postProcessHash": "76c50a7b81e3fe72c1b6f4dd11b2db5fc585cc5abbb0acc3edb6ae3a8532eff8"
},
"ar": {
- "updatedAt": "2026-01-16T09:12:32.672Z",
+ "updatedAt": "2026-01-28T15:20:51.586Z",
"postProcessHash": "1a0fe0c73feeff622cd8329aa4e86f092ec06d954fb76d0fdeb70fba9e2415c2"
}
}
@@ -167,19 +167,19 @@
},
"969d424d653fae1ac27c787d554ba799b678a6763b43436657baa1e98165f479": {
"es": {
- "updatedAt": "2026-01-16T09:12:32.401Z",
+ "updatedAt": "2026-01-28T15:20:51.481Z",
"postProcessHash": "ec16c69f7ae105e66df1eb05fa076080ece83e8f954d53d37107b3b9e816cc2a"
},
"ja": {
- "updatedAt": "2026-01-16T09:12:32.391Z",
+ "updatedAt": "2026-01-28T15:20:51.477Z",
"postProcessHash": "783f84eef09b206dc4329fd1a3d0f9d08f0a696fe4cc8242d06e340b421a2463"
},
"ko": {
- "updatedAt": "2026-01-16T09:12:32.416Z",
+ "updatedAt": "2026-01-28T15:20:51.487Z",
"postProcessHash": "30df6a6430e7595c1527ee3bf16aacfc1c4880771491ca36da2976f98ef837ff"
},
"ar": {
- "updatedAt": "2026-01-16T09:12:32.454Z",
+ "updatedAt": "2026-01-28T15:20:51.502Z",
"postProcessHash": "92e851031702666e62af55e311df42e11b3c92c7d59acfd23de91eb95ac6e65e"
}
}
@@ -187,19 +187,19 @@
"0c5d0348a995e91462a5556edf9087746d409bc748910a3dc1a67300fc9822cd": {
"9f72175980c3783a0d0d4aeeaceb0250498fab5555a978acaec08a9eda4df1e3": {
"es": {
- "updatedAt": "2026-01-16T09:12:33.015Z",
+ "updatedAt": "2026-01-28T15:20:51.671Z",
"postProcessHash": "f39eda11cae3a8fbb02de9c73001af2fff2c9a0e12749855b59084559cd02cb6"
},
"ja": {
- "updatedAt": "2026-01-16T09:12:33.063Z",
+ "updatedAt": "2026-01-28T15:20:51.685Z",
"postProcessHash": "350ebd31263afc4aaeadd09050acc32f776e9d45c3e2f1c45d84870294fd7142"
},
"ko": {
- "updatedAt": "2026-01-16T09:12:33.160Z",
+ "updatedAt": "2026-01-28T15:20:51.728Z",
"postProcessHash": "fb46320ad17c769d36959cb25a2e993b4d86f6b223ff1aed0b15093c6cb08f29"
},
"ar": {
- "updatedAt": "2026-01-16T09:12:33.208Z",
+ "updatedAt": "2026-01-28T15:20:51.747Z",
"postProcessHash": "8196cf7f77dd34bb5981705ce0dbcfba0d1f65a799395615be5c7a90852f03f5"
}
}
@@ -249,19 +249,19 @@
},
"6a643434e4902cc12d1066fea999afb1f9040051e9b61ccd633d281d2cf85db2": {
"es": {
- "updatedAt": "2026-01-16T09:12:32.475Z",
+ "updatedAt": "2026-01-28T15:20:51.511Z",
"postProcessHash": "da720e7a8ae0fdc6fb5a240b107851aa5858c95d4c4553ba308a3f508516c871"
},
"ja": {
- "updatedAt": "2026-01-16T09:12:32.474Z",
+ "updatedAt": "2026-01-28T15:20:51.511Z",
"postProcessHash": "d6f0c3e86e0dc2e693160e62cd8bcbbf7317be5dcca0dc3a83c1dee92281f400"
},
"ko": {
- "updatedAt": "2026-01-16T09:12:32.643Z",
+ "updatedAt": "2026-01-28T15:20:51.576Z",
"postProcessHash": "fd8a9571aca35a0de19311032fc882f161dafb25d1fc05333cf599b61820de85"
},
"ar": {
- "updatedAt": "2026-01-16T09:12:32.682Z",
+ "updatedAt": "2026-01-28T15:20:51.589Z",
"postProcessHash": "88c1e67342e55f5af7345d9745225c84f79252f846b956ca994c762f8d547e84"
}
}
@@ -269,19 +269,19 @@
"1906fcc291cbfc068e3653aede75cca600cc435cf70226610d6716f879d89f70": {
"1ae750c75fa54d6c94b01343fe80e6f36b7dcc10adaa37c0cfb81246bb61d771": {
"es": {
- "updatedAt": "2026-01-16T09:12:33.004Z",
+ "updatedAt": "2026-01-28T15:20:51.710Z",
"postProcessHash": "0e6232a16e58ebd0d7c8c40db7771dd2e99ec88a36e57991aafd0fd225d8a43a"
},
"ja": {
- "updatedAt": "2026-01-16T09:12:33.028Z",
+ "updatedAt": "2026-01-28T15:20:51.714Z",
"postProcessHash": "fd2877438338176e1f90a6bf42013b5a9bf69c613f1dcf7db624e94a2d329c35"
},
"ko": {
- "updatedAt": "2026-01-16T09:12:33.138Z",
+ "updatedAt": "2026-01-28T15:20:51.726Z",
"postProcessHash": "194006e7f2599dbdb1624bfe28a4fb5c4da6074f92d9fface5de3983ee8c95de"
},
"ar": {
- "updatedAt": "2026-01-16T09:12:33.199Z",
+ "updatedAt": "2026-01-28T15:20:51.743Z",
"postProcessHash": "2a05899e625f37c0e0c519d1e38e8aa7500e5521d875d78de098afb3468a5f40"
}
}
@@ -289,19 +289,19 @@
"1a92ad0a41ddb63b2a495d52de2167d0ce269d799dd07556a7c6405d7405a2da": {
"076188a78eed1dc7d8989258ecd50fc635e785b54530020439b24374c73b4b11": {
"es": {
- "updatedAt": "2026-01-16T09:12:33.018Z",
+ "updatedAt": "2026-01-28T15:20:51.672Z",
"postProcessHash": "230c3199608198a828486a2b8c21b20a1284f0188a770f855bc6c44ba2e25601"
},
"ja": {
- "updatedAt": "2026-01-16T09:12:33.040Z",
+ "updatedAt": "2026-01-28T15:20:51.677Z",
"postProcessHash": "15d33eafbfbafa5139408b7b7c0af5f2218acc4ca307770e61ce8da7bcf91536"
},
"ko": {
- "updatedAt": "2026-01-16T09:12:33.182Z",
+ "updatedAt": "2026-01-28T15:20:51.736Z",
"postProcessHash": "730f1cfb58fc5521a35ed97801d29ce4d41c90f32d62d410fe778920969b935c"
},
"ar": {
- "updatedAt": "2026-01-16T09:12:33.212Z",
+ "updatedAt": "2026-01-28T15:20:51.748Z",
"postProcessHash": "1d41eb9fd11954bd47e581e259af23b543dc382e947ec88369d06238e3f66dcc"
}
}
@@ -319,19 +319,19 @@
},
"647cb98741d21f70fd1999be3cbd5f336b78eabf946a59258a4c17b825239d77": {
"es": {
- "updatedAt": "2026-01-16T09:12:32.237Z",
+ "updatedAt": "2026-01-28T15:20:51.424Z",
"postProcessHash": "89d51d135b6a339590d85458995d22f9ead9dc8c52d48096a0dfefeb5bd4745f"
},
"ja": {
- "updatedAt": "2026-01-16T09:12:32.239Z",
+ "updatedAt": "2026-01-28T15:20:51.425Z",
"postProcessHash": "b7bc22941b250eae370c810d45c25cd267781f79cb8a4ca6e46dba156f43028e"
},
"ko": {
- "updatedAt": "2026-01-16T09:12:32.241Z",
+ "updatedAt": "2026-01-28T15:20:51.426Z",
"postProcessHash": "dee92b39d5762e4d241898bccb3c468fb9c36931bf7c18dcc42c18a35065d71c"
},
"ar": {
- "updatedAt": "2026-01-16T09:12:32.262Z",
+ "updatedAt": "2026-01-28T15:20:51.429Z",
"postProcessHash": "4773bcf4ee7939759396138f6c29e468d3600fbac4b12f5ad7c4bbd46460e5f9"
}
}
@@ -339,19 +339,19 @@
"22641fd1be113954bc6b0f6e75800d6775bf039a333de72f467471b580bef634": {
"d646cd268919ee5b8571dddc8ae5099aec797130972e867d6a9607678ddcb850": {
"es": {
- "updatedAt": "2026-01-16T09:12:33.024Z",
+ "updatedAt": "2026-01-28T15:20:51.713Z",
"postProcessHash": "b3c41d4a4debadbc6d3e0b1434f9a7c1bbc0a0a916a17f97bd052fa2fcc51a7f"
},
"ja": {
- "updatedAt": "2026-01-16T09:12:33.121Z",
+ "updatedAt": "2026-01-28T15:20:51.718Z",
"postProcessHash": "eef87a3a65b02d26c2a895dd2d3de9b709b9123b503b15cc651574019f18bc7e"
},
"ko": {
- "updatedAt": "2026-01-16T09:12:33.167Z",
+ "updatedAt": "2026-01-28T15:20:51.731Z",
"postProcessHash": "7d2dbdbe1e6f406950c6c6ca62459898d4e9856f26588e798a4dae5cdc0c2664"
},
"ar": {
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@@ -9190,22 +9241,62 @@
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"008a77e58dfed0f1ae340d5cab94b148520a287fcc66be555d128f200be64665": {
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+ "20b84bfe338ffdbd1b5edfc9eecabba6b10a0cf9181ba79d1ba3612bab07efbe": {
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diff --git a/ja/api-reference/guides/consensus-ratings-explained.mdx b/ja/api-reference/guides/consensus-ratings-explained.mdx
new file mode 100644
index 00000000..7cb7fc0f
--- /dev/null
+++ b/ja/api-reference/guides/consensus-ratings-explained.mdx
@@ -0,0 +1,320 @@
+---
+title: "コンセンサスレーティングの仕組み"
+description: "個々のアナリスト推奨から Benzinga がコンセンサスレーティングをどのように算出するかを解説します"
+---
+
+
+ 有効な目標株価が設定されていないレーティングは分析対象から除外されます。
+
+
+
+
+ 同じ証券会社のアナリストがレーティングを複数回更新した場合、合計数にはそのすべての更新が含まれますが、計算には最新のもののみが使用されます（ユニーク数に反映されます）。
+
+
+
+ コンセンサスレーティングは、新しいアナリストレーティングが公開されるか、既存のレーティングが更新されるたびに再計算されます。
+
+
+
+ アナリストによるカバレッジがない場合、コンセンサスレーティングは算出できません。その銘柄にはコンセンサスデータは表示されません。
+
+
+
+ いいえ。コンセンサスは、アナリストが新しいレーティングを出すか、既存のレーティングを更新したときにのみ変化します。
+
+
+
+***
+
+
+
+
+
+ 株式のコンセンサスレーティングデータを取得します
+
+
+
+ 個々のアナリストによるレーティングを取得します
+
+
\ No newline at end of file
diff --git a/ja/changelog/roadmap.mdx b/ja/changelog/roadmap.mdx
new file mode 100644
index 00000000..50192015
--- /dev/null
+++ b/ja/changelog/roadmap.mdx
@@ -0,0 +1,120 @@
+---
+title: "ロードマップ"
+description: "今後の開発予定をご確認ください。"
+---
+
+
+新機能のご要望はありませんか？[GitHub で issue を作成](https://github.com/Benzinga/benzinga-docs/issues/new)するか、[こちらからお問い合わせ](mailto:licensing@benzinga.com)ください。
+
\ No newline at end of file
diff --git a/ja/introduction/architecture.mdx b/ja/introduction/architecture.mdx
index dc7ca66d..6fe0cc60 100644
--- a/ja/introduction/architecture.mdx
+++ b/ja/introduction/architecture.mdx
@@ -1,97 +1,518 @@
---
-title: アーキテクチャ
-description: スケーラブルなリアルタイム金融データ基盤
-icon: database
+title: "インフラアーキテクチャ"
+description: "Benzinga の 99.9% API 可用性を支えるエンタープライズグレードのインフラと、世界水準の監視・信頼性"
+icon: microchip
---
-Benzinga は、世界中のアプリケーションやサービスにリアルタイムの金融データを配信するために設計された、堅牢で高いスケーラビリティを備えた API 基盤を提供しています。速度と可用性を重視した Benzinga のアーキテクチャは、ユーザーが必要なときに常に信頼性が高く低レイテンシなデータを受け取れるよう、**Go (Golang)**、**Kafka**、**ウェブソケット**、**Elasticsearch**、**マイクロサービス** などの最新技術を活用しています。
+
+ Benzinga のインフラは **99.9% の可用性** を実現するよう設計されており、アプリケーションが常時、信頼性の高いリアルタイム金融データを受信できるようになっています。本番環境は実運用で実証されており、全面的に監視され、平日24時間（24/5）のオンコールエンジニアリングサポートによって支えられています。
+
-
+ ### Escalado a nivel de nodo (Karpenter)
-Para mejorar aún más el rendimiento, Benzinga emplea **edge caching** para garantizar que los datos, incluidos los flujos en tiempo real y el contenido estático, lleguen a los usuarios con una latencia mínima. Al ubicar estratégicamente Puntos de Presencia (PoPs) en todo el mundo, Benzinga asegura una alta disponibilidad y baja latencia para clientes en todos los continentes.
+**Karpenter** gestiona la capacidad del clúster mediante:
-Esta arquitectura distribuida permite a Benzinga proporcionar datos confiables en tiempo real a los clientes, independientemente de su ubicación geográfica, satisfaciendo las necesidades de usuarios tanto locales como globales.
+- Aprovisiona nodos de tamaño óptimo en menos de 60 segundos
+- Consolida nodos infrautilizados para reducir costos
+- Admite instancias spot para cargas de trabajo no críticas
+- Respeta la topología de pods y las restricciones de zona de disponibilidad
---
-Esta arquitectura combina tecnologías modernas y escalables para ofrecer datos e insights financieros rápidos y confiables, respaldando el compromiso de Benzinga con la calidad y el rendimiento. Para obtener más detalles técnicos o para comenzar a usar nuestras API, comunícate con el equipo de soporte de Benzinga o visita nuestra documentación.
\ No newline at end of file
+
+ ## Observabilidad y monitorización a nivel de producción
+
+
+Nuestra infraestructura emplea **monitorización a nivel empresarial** con múltiples capas de observabilidad, lo que garantiza una visibilidad total del estado, el rendimiento y la fiabilidad del sistema. Cada componente se monitoriza de forma continua con alertas automatizadas y protocolos de respuesta a incidentes.
+
+
+ ### Stack de monitoreo integral
+
+
+
+ ### Coralogix: Trazas y registros
+
+
+Coralogix proporciona **observabilidad completa** en nuestra capa de aplicación:
+
+
+ ### Datadog: Alertas y pruebas sintéticas
+
+
+Datadog proporciona **monitorización proactiva** y validación continua:
+
+
+ ### Integración con Slack y gestión de incidentes
+
+
+Todos los sistemas de monitorización se integran con **canales dedicados de Slack** para visibilidad inmediata y respuesta rápida:
+
+
+ ### Alertas e incidentes
+
+
+**Proceso de asignación de desarrolladores:**
+
+1. **Alerta activada** → Notificación automática en Slack con contexto y métricas
+2. **Ingeniero de guardia realiza el triage** → Se evalúa la gravedad y se crea el canal de incidentes
+3. **Desarrollador asignado** → Se etiqueta a la persona experta en el tema según el servicio afectado
+4. **Investigación** → Análisis de causa raíz usando trazas de Coralogix y métricas de Datadog
+5. **Resolución** → Corrección desplegada mediante el pipeline estándar de GitOps
+6. **Análisis post mortem** → Incidente documentado con medidas preventivas
+
+
+ ## Seguridad y cumplimiento normativo
+
+
+
+ ### Seguridad de red
+
+
+- **Aislamiento de VPC** — Segmentación completa de la red respecto de la Internet pública
+- **Security Groups** — Reglas estrictas de entrada/salida, con denegación por defecto
+- **TLS en todas partes** — Todo el tráfico interno y externo cifrado
+- **Gestión de secretos** — AWS Secrets Manager para credenciales confidenciales
+
+
+ ### Control de acceso
+
+
+- **RBAC** — Control de acceso basado en roles (RBAC) de Kubernetes para todas las operaciones
+- **Integración SSO** — Integración con el proveedor de identidad empresarial (SSO)
+- **Registros de auditoría** — Registros de acceso completos conservados para fines de cumplimiento normativo
+
+---
+
+
+ ## Recuperación ante desastres
+
+
+
+ ### Objetivos de recuperación
+
+
+| Métrica | Objetivo | Actual |
+|--------|----------|--------|
+| **RTO** (Recovery Time Objective) | < 15 minutos | ~5 minutos |
+| **RPO** (Recovery Point Objective) | < 1 minuto | Replicación en tiempo real |
+
+
+ ### Características de resiliencia
+
+
+- **Replicación Multi-AZ** — Datos replicados entre zonas de disponibilidad
+- **Conmutación por error automatizada** — Las comprobaciones de estado de Route 53 activan la conmutación por error de DNS
+- **Despliegues progresivos** — Despliegues sin tiempo de inactividad con reversión automática
+- **Copia de seguridad y restauración** — Copias de seguridad diarias automatizadas con recuperación a un punto en el tiempo
+
+---
+
+
+ ## Garantías de confiabilidad a nivel de producción
+
+
+
+ ### Por qué nuestra infraestructura es a prueba de fallos
+
+
+La infraestructura de Benzinga está **probada en producción a gran escala**, gestionando millones de solicitudes diarias con fiabilidad demostrada:
+
+
+ ### Excelencia en monitoreo y observabilidad
+
+
+Nuestro **monitoreo integral** garantiza que los problemas se detecten y se resuelvan antes de que afecten su negocio:
+
+
+ ### Confianza de los clientes: qué significa esto para usted
+
+
+Cuando integra con las API de Benzinga, se conecta a una **infraestructura de nivel de producción** respaldada por:
+
+| Feature | Client Benefit |
+|---------|----------------|
+| **Multi-AZ Redundancy** | Su aplicación se mantiene en línea incluso durante caídas en zonas de disponibilidad de AWS |
+| **Automated Scaling** | Sus solicitudes se gestionan sin problemas durante picos de tráfico, sin aplicar limitación de tasa |
+| **24/7 Monitoring** | Los ingenieros detectan y resuelven los problemas antes de que usted note cualquier degradación |
+| **Zero-Downtime Deployments** | Nuestras actualizaciones nunca interrumpen la disponibilidad de su servicio |
+| **Complete Audit Trail** | Cada implementación se registra, se revisa y puede revertirse al instante |
+| **Proactive Alerting** | El 95% de los posibles problemas se resuelven antes de que afecten al cliente |
+
+
+ ## Resumen
+
+
+La infraestructura de Benzinga ofrece **fiabilidad a nivel empresarial** mediante:
+
+
+ ## 概要
+
+
+コンセンサスレーティングは、個々のアナリストのレーティングを集約し、特定銘柄に対するアナリストの見方を単一の分かりやすい指標として示すものです。本ガイドでは、コンセンサスレーティングをどのように算出しているかを説明し、適切な投資判断に役立てることを目的としています。
+
+
+ ## コンセンサス・レーティングの算出方法
+
+
+
+ ### ステップ 1: アナリスト・レーティングの収集
+
+
+特定の銘柄について、利用可能なすべてのアナリスト・レーティングを収集します。各レーティングには以下が含まれます：
+
+* **アナリスト名** と **所属機関名**
+* **レーティング**（例：Strong Buy、Buy、Hold、Sell、Strong Sell）
+* **目標株価** - アナリストが予測する株価
+* **更新日** - レーティングが発行された日
+
+
+ ### ステップ 2: 一意のアナリストごとのフィルタリング
+
+
+精度を確保し二重計上を防ぐため、各アナリストと証券会社の一意な組み合わせごとに、**最新のレーティングのみ**を集計対象とします。
+
+**例:** Morgan Stanley のアナリスト John Doe が同じ銘柄を複数回レーティングしている場合でも、計算に含まれるのは最新のレーティングのみです。
+
+
+ ### ステップ3: レーティングの分類
+
+
+アナリスト・レーティングは、次の5つの標準的なカテゴリに分類されます。
+
+| カテゴリ | 数値 |
+|----------|---------------|
+| **強い売り推奨** | 1 |
+| **売り** | 2 |
+| **ホールド** | 3 |
+| **買い** | 4 |
+| **強い買い推奨** | 5 |
+
+
+ ### ステップ 4: レーティングの集計
+
+
+各カテゴリーごとのアナリスト数を数えます。
+
+**集計例:**
+
+* Strong Buy: アナリスト 8人
+* Buy: アナリスト 12人
+* Hold: アナリスト 5人
+* Sell: アナリスト 2人
+* Strong Sell: アナリスト 1人
+
+**合計:** 重複を除くアナリスト 28人
+
+
+ ### ステップ5: コンセンサスレーティング値の計算
+
+
+コンセンサスレーティング値は、加重平均で計算されます。
+
+```
+Consensus Value = (Strong Buy × 5 + Buy × 4 + Hold × 3 + Sell × 2 + Strong Sell × 1) / Total Analysts
+```
+
+**先ほどの例を用いると：**
+
+```
+Consensus Value = (8×5 + 12×4 + 5×3 + 2×2 + 1×1) / 28
+Consensus Value = (40 + 48 + 15 + 4 + 1) / 28
+Consensus Value = 108 / 28
+Consensus Value = 3.86
+```
+
+
+ ### ステップ 6: コンセンサス評価の判定
+
+
+コンセンサス値は最も近い整数に四捨五入され、以下の評価にマッピングされます:
+
+| コンセンサス値 | 標準評価 | 簡易評価 |
+|----------------|----------|----------|
+| **1** | 強い売り | 売り |
+| **2** | 売り | 売り |
+| **3** | ホールド | ホールド |
+| **4** | 買い | 買い |
+| **5** | 強い買い | 買い |
+
+**この例では:** 3.86 は **4** に四捨五入され、コンセンサス評価は **「買い」** になります。
+
+***
+
+
+ ## 表示設定
+
+
+
+ ### 標準レーティングと簡略レーティング
+
+
+表示形式は次の 2 種類があります。
+
+**標準（5 区分）:**
+
+* Strong Sell、Sell、Hold、Buy、Strong Buy
+
+**簡略（3 区分）:**
+
+* Sell（Strong Sell と Sell をまとめたもの）
+* Hold
+* Buy（Buy と Strong Buy をまとめたもの）
+
+
+ ### 件数表示と割合表示
+
+
+**件数表示:**
+各カテゴリに属するアナリストの実人数を表示します。
+
+**割合表示:**
+各カテゴリに属するアナリストの比率を、合計が100%になるように整数（パーセント）に丸めて表示します。
+
+**例:**
+
+* Buy: 71%（アナリスト20人）
+* Hold: 18%（アナリスト5人）
+* Sell: 11%（アナリスト3人）
+
+***
+
+
+ ## 目標株価の計算
+
+
+
+ ### コンセンサス目標株価
+
+
+全アナリストの目標株価の平均値:
+
+```
+Consensus PT = Sum of all Price Targets / Number of Analysts
+```
+
+
+ ### 最低および最高目標株価
+
+
+* **最低目標株価:** すべてのアナリストの中で最も低い目標株価
+* **最高目標株価:** すべてのアナリストの中で最も高い目標株価
+
+これらにより、アナリスト予想のレンジ（幅）を把握できます。
+
+***
+
+
+ ## 指標の概要
+
+
+
+ ### アナリスト総数 vs. ユニークアナリスト数
+
+
+* **アナリスト総数:** 収集されたすべてのレーティング（同一アナリストからの複数レーティングを含む場合があります）
+* **ユニークアナリスト数:** アナリストとファームの一意な組み合わせ数（計算に使用）
+
+ユニーク数を用いることで、各アナリストの意見が一度だけカウントされ、より正確なコンセンサスが得られます。
+
+***
+
+
+ ## 重要な考慮事項
+
+
+
+ ### レーティングの最新性
+
+
+コンセンサス・レーティングは、最新のアナリストの見解を反映しています。**Updated At** タイムスタンプは、コンセンサスが最後に算出された時刻を示します。
+
+
+ ### カバレッジの深さ
+
+
+コンセンサスレーティングは、より多くの異なるアナリストによる評価に基づいているほど信頼性が高くなります。担当アナリストが 3～5 名に満たない銘柄は、コンセンサスレーティングが相対的に不安定になる可能性があります。
+
+
+ ### レーティング分布
+
+
+コンセンサスだけでなく、レーティングの分布にも目を向けてください。半数が Buy、半数が Sell の銘柄はコンセンサスとしては「Hold」になりますが、これはアナリスト間に大きな見解の相違があることを覆い隠してしまいます。
+
+***
+
+
+ ## 計算例のウォークスルー
+
+
+**XYZ Corporation** を題材に、計算の一連の手順を順を追って見ていきます。
+
+
+ ### 元データ（アナリスト10名）
+
+
+| アナリスト | 会社 | レーティング | 目標株価 |
+|---------|------|--------|--------------|
+| Analyst A | Goldman Sachs | 買い | $150 |
+| Analyst B | JP Morgan | 強い買い | $165 |
+| Analyst C | Morgan Stanley | 買い | $155 |
+| Analyst D | Bank of America | 中立 | $140 |
+| Analyst E | Citigroup | 強い買い | $170 |
+| Analyst F | Wells Fargo | 買い | $152 |
+| Analyst G | Deutsche Bank | 中立 | $145 |
+| Analyst H | Barclays | 売り | $130 |
+| Analyst I | UBS | 買い | $158 |
+| Analyst J | Credit Suisse | 強い買い | $168 |
+
+
+ ### ステップごとの計算
+
+
+**1. アナリストを一意なものに絞り込み:** 10件すべてのレーティングがユニーク（10人のアナリストがそれぞれ1件ずつ評価）
+
+**2. 件数を集計:**
+
+* Strong Buy: 3
+* Buy: 4
+* Hold: 2
+* Sell: 1
+* Strong Sell: 0
+
+**3. コンセンサス値を算出:**
+
+```
+(3×5 + 4×4 + 2×3 + 1×2 + 0×1) / 10 = (15 + 16 + 6 + 2 + 0) / 10 = 3.9
+```
+
+**4. コンセンサス評価を算出:** 3.9 を四捨五入すると **4 = 「Buy（買い）」**
+
+**5. 目標株価:**
+
+* コンセンサス目標株価: (150+165+155+140+170+152+145+130+158+168) / 10 = **$153.30**
+* 最低目標株価: **$130**
+* 最高目標株価: **$170**
+
+**6. 割合の内訳:**
+
+* Buy（買い）: 70%（Strong Buy（強い買い）30% + Buy（買い）40%）
+* Hold（中立）: 20%
+* Sell（売り）: 10%
+
+
+ ### 最終コンセンサスレーティングの出力
+
+
+```json
+{
+ "consensusRating": "BUY",
+ "consensusRatingValue": 3.9,
+ "consensusPriceTarget": 153.30,
+ "priceTargetLow": 130,
+ "priceTargetHigh": 170,
+ "totalAnalysts": 10,
+ "uniqueAnalysts": 10,
+ "lastUpdated": "2026-01-16T10:30:00Z"
+}
+```
+
+***
+
+
+ ## よくある質問
+
+
+
+ {/* 作業中 */}
+
+
+
+---
+
+
+
+
+ {/* 計画中 */}
+
+
+
+
+ 進行中
+
+
+
+
+
+
+
+ トランスクリプトの PDF 版
+ カンファレンスコールのトランスクリプトを、ダウンロード可能な PDF 形式で提供します。
+
+
+ トランスクリプトのヒストリカルデータ拡充
+ カンファレンスコールのトランスクリプトについて、ヒストリカルデータの提供範囲を拡大します。
+
+
+
+ {/* バックログ */}
+
+
+
+
+ 計画中
+
+
+
+
+
+
+
+ 監視ダッシュボードの拡張
+ すべてのサービス提供内容を監視するクライアント向けダッシュボードです。
+
+
+
+ 翻訳エンジンの最適化
+ 翻訳サービスのパフォーマンスおよび品質を向上させます。
+
+
+ ニュース向け Security Master 連携
+ 社内の Security Master を統合し、クエリ機能を強化します。
+
+
+
+ {/* 完了 */}
+
+
+
+
+ バックログ
+
+
+
+
+
+
+
+ Go SDK
+ 公式の Go クライアントライブラリです。
+
+
+ すべての calendar 用ウェブソケット
+ すべての calendar エンドポイント向けにリアルタイムストリーミングを提供します。
+
+
+
+
+
+ 完了
+
+
+
+
+
+
+
+ 自社セキュリティマスター
+ データ整合性を高めるための集中管理型セキュリティマスター。
+
+
+
+ TCP ストリーミング
+ リアルタイムデータ向けの低遅延 TCP 接続。
+
+
+
+ カンファレンスコールトランスクリプト
+ 話者情報付きの完全なトランスクリプト。
+
+
+
+ Webhook エンジン
+ プッシュ型のデータ配信。
+
+
+ Java SDK
+ 公式の Java クライアントライブラリ。
+
- ## Go と Kafka による高パフォーマンスなアーキテクチャ
+
-
+
+
+ マルチ AZ 冗長構成による本番環境で実証された高い信頼性
+
+
+ Coralogix および Datadog によるリアルタイムな可観測性
+
+
+ インテリジェントなオートスケーリングによるゼロダウンタイムのデプロイ
+
+
-
+ ## 概要
-高い並行性と高速性を持つ **Go (Golang)** を用いて構築された Benzinga のインフラストラクチャは、大量の金融データのトラフィックを効率的に処理します。データパイプラインとリアルタイムストリーミングは **Kafka** によって支えられており、最小限のレイテンシでの高速なデータ取り込み、処理、および配信を実現しています。このアーキテクチャにより、グローバルな展開においてもスケーラビリティと堅牢性が確保され、リアルタイム金融データ配信の要件を満たします。
+当社のプラットフォームは、AWS マネージドサービス、Kubernetes オーケストレーション、GitOps デプロイ手法を活用したモダンなクラウドネイティブ・アーキテクチャ上に構築されています。この**本番環境レベルのインフラストラクチャ**は、包括的な可観測性と自動スケーリングを備え、1 日あたり数百万件の API リクエストを処理しつつ、100ms 未満のレスポンス時間を維持します。
-
-
-
+
- ## ウェブソケットおよび REST API によるリアルタイムデータアクセス
+
+
+---
+
+
+
+ フォールトトレランスを確保するため、複数のアベイラビリティーゾーンに分散配置されたサービス
+
+
+ 厳格なセキュリティグループポリシーを適用した分離された Virtual Private Cloud (VPC)
+
+
+ ヘルスチェックと自動フェイルオーバー・ルーティング機能を備えたグローバル DNS
+
+
+ AWS 管理の Kubernetes コントロールプレーンによる 99.95% の SLA
+
+
+
+
+
+ エッジ側でのAPIキー検証およびJWTトークンの検証
+
+
+ 公平なリソース配分を保証するためのクライアントごとのリクエスト制限
+
+
+ 正常に稼働しているサービスポッド間でのインテリジェントなトラフィック分散
+
+
+ すべてのトラフィックをTLS 1.3で暗号化し、証明書を自動更新
+
+
+
+
+ ## コアインフラ
+
+
+
+ ### AWS クラウド基盤
+
+
+当社のインフラストラクチャはすべて **Amazon Web Services (AWS)** 上で稼働しており、次の機能を活用しています:
+
+
+ ### Kubernetes インフラストラクチャ
+
+
+安全なデプロイと環境の分離を確保するために、**2つの専用 Kubernetes クラスター** を運用しています。
+
+| Environment | Purpose | Deployment Flow |
+|-------------|---------|-----------------|
+| **Staging Cluster** | 開発者によるテスト、QA 検証、インテグレーションテスト | 検証のためにコード変更が最初にデプロイされる |
+| **Production Cluster** | SLA 保証付きの本番顧客トラフィック | 検証済みのリリースのみが本番に昇格される |
+
+
+ #### 主要な Kubernetes コンポーネント
+
+
+- **Karpenter** — 数分単位ではなく数秒で適切なサイズのコンピュートリソースをプロビジョニングする、AWS ネイティブなノード・オートスケーラー
+- **Horizontal Pod Autoscaler (HPA)** — CPU、メモリ、およびカスタムメトリクスに基づいて Pod を自動的にスケーリング
+- **Kong Gateway** — ingress/egress、レート制限、認証を処理するエンタープライズ向け API ゲートウェイ
+- **ArgoCD** — 宣言的で監査可能なリリースを実現する、GitOps ベースのデプロイメントコントローラー
+
+---
+
+
+ ## API ゲートウェイとトラフィック管理
+
+
+
+ ### Kong Gateway
+
+
+すべてのAPIトラフィックは **Kong Gateway** を通過し、次の機能を提供します:
+
+
+ ### Route 53 DNS
-Benzinga の API は **WebSocket** と **REST** の両プロトコルをサポートしており、クライアントはリアルタイムデータへのアクセスだけでなく、オンデマンドでのリクエスト送信も行えます。WebSocket 接続は、リアルタイムのマーケットクオートや取引データなど、継続的なデータフィードを必要とするアプリケーションに最適であり、一方 REST API は、過去データ、企業ファンダメンタルズ、ニュース、アナリティクスといった幅広いリクエストに対応します。
+AWS Route 53 は次の機能を提供します：
+
+- **グローバルなレイテンシベースのルーティング** — ユーザーを自動的に最速のエンドポイントにルーティング
+- **ヘルスチェック** — 障害発生時の自動フェイルオーバーを伴う継続的な監視
+- **100% 稼働 SLA** — DNS 解決に対する AWS による可用性保証
-
- ### API の特長
+---
+
+
+ ## CI/CD パイプライン
-- **リアルタイム市場データ**: リアルタイムの気配値（クォート）、約定、その他の主要な市場データをストリーミング配信できます。
-- **ヒストリカルデータ**: バーデータ、気配値、市場パフォーマンスなどを含む過去データ（ヒストリカルデータ）にアクセスできます。
-- **ニュースとインサイト**: リアルタイムのニュースや、市場を動かすインサイトを常に把握できます。
-- **企業ファンダメンタルズ**: 売上高、利益、主要な比率などの重要な財務指標を取得できます。
+デプロイパイプラインでは、本番環境にコードをリリースする前に厳格な品質ゲートを設けています。
-
- ## Elasticsearch を用いたデータ保存と検索効率
+
-
-
-
+ ### 開発ワークフロー
-効率的なデータ取得と保存のために、Benzinga は検索およびインデックス作成システムの中核コンポーネントとして **Elasticsearch** を使用しています。Elasticsearch により、構造化データと非構造化データの両方に高速アクセスでき、ユーザーはヒストリカルデータやニュースアーカイブといった大規模データセットをミリ秒レベルの応答時間でクエリできます。この構成は分析にも対応しており、クライアントはデータから有用なインサイトを抽出・分析できます。
+```mermaid
+flowchart LR
+ A[Developer Commit] --> B[GitLab CI Pipeline]
+ B --> C{Linting & Tests}
+ C -->|Pass| D[Build Container Image]
+ C -->|Fail| E[Reject & Notify]
+ D --> F[Push to Registry]
+ F --> G[Peer Review Required]
+ G -->|2 Approvals| H[Update GitOps Repo]
+ H --> I[ArgoCD Sync]
+ I --> J[Deploy to Staging]
+ J -->|Validated| K[Promote to Production]
+```
-
-
-
-
-
- ## スケーラビリティのためのマイクロサービスベースのインフラストラクチャ
+
+ ### パイプラインのステージ
-Benzinga のアーキテクチャは **マイクロサービスアーキテクチャ** に基づいており、各サービスがデータの取り込み、処理、保存、配信などの特定の機能を担当します。このモジュール式アプローチによりスケーラビリティが向上し、各コンポーネントは需要に応じて独立してスケールできます。さらに、マイクロサービス同士は軽量なプロトコルを介して通信するため、システム全体にわたって低遅延と高い耐障害性が確保されます。
+| ステージ | 説明 | 品質ゲート |
+|-------|-------------|--------------|
+| **Lint** | コードスタイルおよび静的解析チェック | すべてのルールに合格すること |
+| **Unit Tests** | テストスイートの自動実行 | テスト 100% 成功 |
+| **Security Scan** | コンテナ脆弱性スキャン | 重大/高リスクの CVE がないこと |
+| **Build** | コミット SHA でタグ付けした Docker イメージの作成 | ビルド成功 |
+| **Peer Review** | 2 名の開発者による手動でのコードレビュー | 2 名の承認が必要 |
+| **GitOps Update** | ArgoCD リポジトリ内のイメージタグ更新 | 手動プロモーション |
-
- ## 画像および静的コンテンツのCDN対応配信
+
+ ### ArgoCD を用いた GitOps
-画像、ロゴ、その他の静的アセットを高速に配信するため、Benzingaでは**CDN**（Content Delivery Network）を利用しています。この仕組みにより、静的リソースがユーザーの近くでキャッシュされ、読み込み時間が短縮されてレイテンシが最小化されるため、地理的な場所に関係なく画像やファイルをほぼ瞬時に読み込めます。
+すべてのデプロイは、GitOps の原則に従い **ArgoCD** によって管理されます:
+
+- **宣言的** — 望ましい状態を Git 上で定義し、単一の信頼できる情報源とする
+- **自動同期** — ArgoCD が変更を検知して自動的に適用する
+- **ロールバック機能** — Git コミットを戻すことで即時にロールバック可能
+- **監査証跡** — Git のコミットログによる完全なデプロイ履歴
-
- ## Benzinga のアーキテクチャの主な利点
+
+ 本番環境へのすべての変更は、特定の Git コミット、ピアレビュー、および承認者に紐づけて追跡できるため、コンプライアンス要件に対する完全な監査性を確保できます。
+
+
+---
+
+
+ ## オートスケーリングアーキテクチャ
-- **スケーラビリティ**: 水平スケーリングを前提に設計されており、1 分あたり数百万件のリクエストと、大量の同時ウェブソケット接続をサポートします。
-- **高可用性**: 冗長構成と地理的に分散したコンポーネントにより、稼働時間とデータ可用性を確保します。
-- **データ整合性**: Kafka と Elasticsearch の組み合わせにより、一貫したデータフローとデータ取得が可能で、信頼性の高いフェイルオーバー機構を備えています。
-- **低レイテンシ**: Go の性能、Kafka のストリーミング、ウェブソケットのリアルタイム機能を活用し、レイテンシを極力抑えてデータを配信するよう最適化されています。
+当社のインフラストラクチャは、トラフィックの急増に対応するため、複数のレベルで自動的にスケールします。
-
- ## デプロイの柔軟性とインフラ統合
+
+ ### Podレベルのスケーリング (HPA)
-Benzingaのアーキテクチャは、クライアントの多様なニーズに対応する柔軟なデプロイオプションをサポートしています。
+各サービスのデプロイには、Horizontal Pod Autoscaler (HPA) の設定が含まれています。
+
+```yaml
+# HPA設定の例
+apiVersion: autoscaling/v2
+kind: HorizontalPodAutoscaler
+spec:
+ minReplicas: 3
+ maxReplicas: 50
+ metrics:
+ - type: Resource
+ resource:
+ name: cpu
+ target:
+ type: Utilization
+ averageUtilization: 70
+```
-- **マネージドクラウドサービス**: シームレスな利用体験を求めるクライアント向けに、Benzingaは自動スケーリングやメンテナンスを含むフルマネージドのクラウドサービスを提供します。
-- **セルフホスト型オプション**: より細かな制御を必要とする場合、Benzingaのアーキテクチャはオンプレミスデプロイやプライベートクラウド環境に対応でき、データの完全な所有権と各地域の法規制への準拠を確保できます。
+**スケーリング条件:**
-
- ### エッジキャッシングによるグローバル展開
+* CPU 使用率 > 70%
+* メモリ使用率 > 80%
+* カスタムメトリクス（リクエストキュー長、レイテンシーのパーセンタイル値）
+
+
+
+
+ **分散トレーシングとログ監視**
+ - すべてのサービスからのリアルタイムなログ集約
+ - マイクロサービス間の分散トレーシング
+ - アプリケーション性能監視（APM）
+ - 相関IDを用いたエンドツーエンドのリクエスト追跡
+ - ログパターンの認識と異常検知
+ - ビジネスメトリクス向けのカスタムダッシュボード
+
+
+ **アラートとシンセティックモニタリング**
+ - 24時間365日の継続的なAPIエンドポイントテスト
+ - 複数リージョンでのシンセティックモニタリング
+ - レスポンスタイムと可用性の監視
+ - インテリジェントなルーティングによる自動アラート
+ - サービスレベル指標（SLI）の追跡
+ - パフォーマンス劣化の検知
+
+
+
+
+
+ すべてのサービス、Pod、およびコンテナからのアプリケーションログをリアルタイムに集約し、インフラ全体にわたるデバッグ情報へ即時にアクセス可能にします。
+
+
+ すべての API リクエストを、マイクロサービス、ロードバランサー、データベース、および外部サービスにまたがってエンドツーエンドでトレースします。これにより、パフォーマンス問題やエラーの根本原因を迅速に分析できます。
+
+
+ スタックトレース、コンテキスト情報、影響を受けたユーザー数を含む自動エラー検出を行います。エラーは重大度と影響度に基づいて分類されます。
+
+
+ すべてのサービスにわたる API レスポンスタイム、スループット、エラー率、およびリソース使用率に関するリアルタイムのメトリクスを提供します。
+
+
+
+**本番環境における Coralogix の主な機能:**
+
+- **保持ポリシー**: 即時アクセス用の 30 日間ホットストレージと、コンプライアンス対応のための 90 日間アーカイブ
+- **クエリパフォーマンス**: 数十億件のログエントリに対してサブ秒レイテンシでのクエリ
+- **アラート連携**: Slack チャンネルおよびオンコールエンジニアへの自動ルーティング
+- **カスタムダッシュボード**: ビジネス固有のメトリクスをステークホルダーがリアルタイムに閲覧可能
+
+
+
+ 自動テストが複数の地理的リージョンから 60 秒ごとに実行され、顧客に影響が出る前に API の可用性、レスポンスタイム、データの正確性を検証します。
+
+
+ 機械学習による異常検知がメトリクスにおける異常なパターンを特定し、問題が顧客に影響を与える前にアラートを発報します。
+
+
+ サービスレベル目標 (SLO) をリアルタイムで監視し、99.9% の可用性目標に対する自動レポートを生成します。
+
+
+ p50、p95、p99 レイテンシーのパーセンタイルを継続的に監視し、一貫したパフォーマンスを確保します。
+
+
+
+**Datadog のシンセティックテストには以下が含まれます:**
+
+| テスト種別 | 実行頻度 | リージョン | 監視メトリクス |
+|-----------|-----------|------------|-----------------|
+| **API ヘルスチェック** | 60 秒ごと | グローバル 5 リージョン | 可用性、レスポンスタイム、ステータスコード |
+| **データ精度テスト** | 5 分ごと | 3 リージョン | データ鮮度、スキーマバリデーション、整合性 |
+| **パフォーマンステスト** | 60 秒ごと | 5 リージョン | レイテンシー (p50/p95/p99)、スループット、エラー率 |
+| **認証テスト** | 5 分ごと | 2 リージョン | API キー検証、レート制限、OAuth フロー |
+
+
+
+ **クリティカルアラート**
+
+ * 即時対応が必要な P1/P2 インシデント
+ * オンコールエンジニアへの自動ページング
+ * リアルタイムメトリクスとランブックへのリンク
+ * インシデントコマンダーの割り当て
+
+
+
+ **パフォーマンスインサイト**
+
+ * 日次ヘルス状況サマリー
+ * キャパシティプランニング用アラート
+ * パフォーマンストレンド通知
+ * 異常検知の警告
+
+
+
+**Slack アラートワークフロー:**
+
+```mermaid
+flowchart LR
+ A[アラート発生] --> B{重大度レベル}
+ B -->|P1/P2| C[#alerts-production]
+ B -->|P3/P4| D[#monitoring-insights]
+ C --> E[オンコールエンジニアに通知]
+ C --> F[インシデントチャネル作成]
+ F --> G[開発者アサイン]
+ G --> H[根本原因調査]
+ H --> I[修正デプロイ]
+ I --> J[事後分析レポート]
+```
+
+
+
+ すべての P1/P2 インシデントは、平日 24 時間体制で待機しているオンコールエンジニアに対して、**即時の自動ページング**を行います。
+
+
+
+ 当社のモニタリングシステムは、プロアクティブなアラートと自動復旧により、**潜在的な問題の 95% を顧客影響前に検出・解決**しています。
+
+
+---
+
+
+
+ **本番環境での実績**
+ - 1,000 万件超の API リクエストを日次処理
+ - 平均レスポンスタイム 100ms 未満
+ - 稼働率 99.9% を達成
+ - 3 年超にわたりデータ損失ゼロ
+
+
+ **運用面での卓越性**
+ - 24/5/365 のオンコールエンジニア体制
+ - 自動フェイルオーバーとセルフヒーリング
+ - 複数リージョンによる冗長構成
+
+
+
+
+
+ すべてのリクエスト、ログエントリ、メトリクスを、Coralogix の分散トレーシングと集中ログ管理を用いてエンドツーエンドで追跡します
+
+
+ Datadog のシンセティックモニタリングにより、複数リージョンから 60 秒ごとに API をテストし、お客様への影響が出る前に問題をアラートします
+
+
+ 自動化された Slack 連携により、アラートを専用チャンネルへルーティングし、開発者の即時アサインと解決状況のトラッキングを行います
+
+
+ すべてのインシデントに対してポストモーテム分析を行い、自動化された予防措置によって問題が再発しないようにします
+
+
+
+
+ **本番運用対応**: 当社のインフラストラクチャは、可用性 99.9% を維持しつつ、リアルタイム金融データ配信で 100ms 未満のレイテンシを保ちながら、これまでに **数十億件の API リクエスト** を処理してきました。
+
+
+---
+
+
+
+ AWS EKS を用いたマルチ AZ デプロイとマネージドコントロールプレーンにより、最大限の稼働時間を確保します
+
+
+ ArgoCD によるリリース管理で、完全な監査証跡と即時ロールバック機能を提供します
+
+
+ Karpenter と HPA によるシームレスなキャパシティ管理で、トラフィックのスパイクを自動的に処理します
+
+
+ Coralogix によるトレース/ログと Datadog によるアラート/シンセティクス、さらに Slack 連携により、迅速なインシデント対応を実現します
+
+
+ 専任のオンコールエンジニアが対応にあたります
+
+
+ 暗号化、RBAC、ネットワーク分離による多層防御で、お客様のデータを保護します
+
+
+
+
+ **お客様の成功が最優先です**: インフラストラクチャ、SLA 保証、またはお客様固有の信頼性要件についてご質問やご相談がある場合は、アカウント担当者までお問い合わせいただくか、[support@benzinga.com](mailto:support@benzinga.com) までメールでご連絡ください。
+
\ No newline at end of file
diff --git a/ja/openapi/calendar_api.spec.yml b/ja/openapi/calendar_api.spec.yml
index 9d2b2c04..1ccdf68f 100644
--- a/ja/openapi/calendar_api.spec.yml
+++ b/ja/openapi/calendar_api.spec.yml
@@ -2749,14 +2749,19 @@ components:
calendarapi.AggregateRating:
properties:
buy:
+ example: 10
type: integer
hold:
+ example: 3
type: integer
sell:
+ example: 1
type: integer
strong_buy:
+ example: 5
type: integer
strong_sell:
+ example: 0
type: integer
type: object
calendarapi.AnalystInsightsJSON:
@@ -2796,22 +2801,31 @@ components:
aggregate_ratings:
$ref: "#/components/schemas/calendarapi.AggregateRating"
aggregate_type:
+ example: 90D
type: string
consensus_price_target:
+ example: 195.5
type: number
consensus_rating:
+ example: Buy
type: string
consensus_rating_val:
+ example: 4.2
type: number
high_price_target:
+ example: 225
type: number
low_price_target:
+ example: 150
type: number
total_analyst_count:
+ example: 19
type: integer
unique_analyst_count:
+ example: 15
type: integer
updated_at:
+ example: 2024-01-09T16:00:00Z
type: string
type: object
calendarapi.DividendJSON:
@@ -2897,40 +2911,53 @@ components:
calendarapi.InsiderTransaction:
properties:
accession_number:
+ example: 0001127602-24-000123
type: string
company_cik:
+ example: 320193
type: string
company_name:
+ example: Apple Inc.
type: string
company_symbol:
+ example: AAPL
type: string
filing_date:
+ example: 2024-01-09T00:00:00Z
type: string
footnotes:
items:
$ref: "#/components/schemas/calendarapi.SECFootnotes"
type: array
form_type:
+ example: "4"
type: string
html_url:
+ example: https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000320193
type: string
id:
+ example: 64a1b2c3d4e5f6789012345
type: string
is_10b5:
+ example: true
type: boolean
owner:
$ref: "#/components/schemas/calendarapi.Owner"
remaining_shares:
+ example: "125000"
type: string
remaining_underlying_shares:
+ example: "50000"
type: string
traded_percentage:
+ example: "15.5"
type: string
transactions:
items:
$ref: "#/components/schemas/calendarapi.Transaction"
type: array
updated:
+ example: 1704758400
type: integer
type: object
calendarapi.InsiderTransactionFilingDoc:
@@ -2967,18 +2994,25 @@ components:
calendarapi.Owner:
properties:
insider_cik:
+ example: "0001234567"
type: string
insider_name:
+ example: Tim Cook
type: string
insider_title:
+ example: Chief Executive Officer
type: string
is_director:
+ example: true
type: boolean
is_officer:
+ example: true
type: boolean
is_ten_percent_owner:
+ example: false
type: boolean
raw_signature:
+ example: /s/ Tim Cook
type: string
type: object
calendarapi.RatingJSON:
@@ -3024,8 +3058,10 @@ components:
calendarapi.SECFootnotes:
properties:
id:
+ example: F1
type: string
text:
+ example: Shares were sold pursuant to a Rule 10b5-1 trading plan
type: string
type: object
calendarapi.SplitJSON:
@@ -3039,40 +3075,58 @@ components:
calendarapi.Transaction:
properties:
acquired_or_disposed:
+ example: D
type: string
conversion_exercise_price_derivative:
+ example: "150.25"
type: string
date_deemed_execution:
+ example: 2024-01-09T00:00:00Z
type: string
date_exercisable:
+ example: 2024-01-09T00:00:00Z
type: string
date_expiration:
+ example: 2025-01-09T00:00:00Z
type: string
date_transaction:
+ example: 2024-01-09T00:00:00Z
type: string
is_derivative:
+ example: false
type: boolean
ownership:
+ example: Direct
type: string
post_transaction_quantity:
+ example: "250000"
type: string
price_per_share:
+ example: "150.25"
type: string
remaining_underlying_shares:
+ example: "50000"
type: string
security_title:
+ example: Common Stock
type: string
shares:
+ example: "10000"
type: string
transaction_code:
+ example: S
type: string
transaction_id:
+ example: TXN-20240109-001
type: string
underlying_security_title:
+ example: Common Stock
type: string
underlying_shares:
+ example: "10000"
type: string
voluntarily_reported:
+ example: false
type: boolean
type: object
servers:
diff --git a/ja/openapi/data-api-proxy_api.spec.yml b/ja/openapi/data-api-proxy_api.spec.yml
index 7b1f534a..2de21958 100644
--- a/ja/openapi/data-api-proxy_api.spec.yml
+++ b/ja/openapi/data-api-proxy_api.spec.yml
@@ -1321,6 +1321,8 @@ components:
type: object
bzhttp.ErrorCode:
enum:
+ - unsupported_message_type
+ - database_query_error
- json_unmarshaling_error
- no_data_found
- no_matching_endpoint
@@ -1332,10 +1334,10 @@ components:
- failed_dependency
- service_unavailable
- upstream_api_error
- - unsupported_message_type
- - database_query_error
type: string
x-enum-varnames:
+ - ErrorUnsupportedMessageType
+ - ErrorDBQueryError
- ErrorJSONUnmarshaling
- ErrorNoDataFound
- ErrorNoMatchingEndpoint
@@ -1347,8 +1349,6 @@ components:
- ErrorFailedDependency
- ErrorServiceUnavailable
- ErrorUpstreamAPIError
- - ErrorUnsupportedMessageType
- - ErrorDBQueryError
bzhttp.Resp:
properties:
data:
diff --git a/ja/openapi/logo-api_api.spec.yml b/ja/openapi/logo-api_api.spec.yml
index ad3d41c9..c23a586c 100644
--- a/ja/openapi/logo-api_api.spec.yml
+++ b/ja/openapi/logo-api_api.spec.yml
@@ -141,6 +141,12 @@ paths:
name: max_width
schema:
type: string
+ - description: true の場合、flutter_svg ライブラリとの互換性を保つために、SVG の URL にクエリパラメータ
+ flutter_compatible=true を追加します。
+ in: query
+ name: flutter_compatible
+ schema:
+ type: boolean
responses:
"200":
description: data フィールドに LogoClientResponse オブジェクトの配列を含む成功したレスポンス
diff --git a/ja/openapi/newsquantified-api_api.spec.yml b/ja/openapi/newsquantified-api_api.spec.yml
index 64778b73..a2cb84d3 100644
--- a/ja/openapi/newsquantified-api_api.spec.yml
+++ b/ja/openapi/newsquantified-api_api.spec.yml
@@ -106,8 +106,6 @@ components:
type: object
bzhttp.ErrorCode:
enum:
- - unsupported_message_type
- - database_query_error
- json_unmarshaling_error
- no_data_found
- no_matching_endpoint
@@ -119,10 +117,10 @@ components:
- failed_dependency
- service_unavailable
- upstream_api_error
+ - unsupported_message_type
+ - database_query_error
type: string
x-enum-varnames:
- - ErrorUnsupportedMessageType
- - ErrorDBQueryError
- ErrorJSONUnmarshaling
- ErrorNoDataFound
- ErrorNoMatchingEndpoint
@@ -134,6 +132,8 @@ components:
- ErrorFailedDependency
- ErrorServiceUnavailable
- ErrorUpstreamAPIError
+ - ErrorUnsupportedMessageType
+ - ErrorDBQueryError
bzhttp.Resp:
properties:
data:
diff --git a/ja/openapi/ticker-trends-api_api.spec.yml b/ja/openapi/ticker-trends-api_api.spec.yml
index c19dc6fb..d9bb360e 100644
--- a/ja/openapi/ticker-trends-api_api.spec.yml
+++ b/ja/openapi/ticker-trends-api_api.spec.yml
@@ -172,8 +172,6 @@ components:
type: object
bzhttp.ErrorCode:
enum:
- - unsupported_message_type
- - database_query_error
- json_unmarshaling_error
- no_data_found
- no_matching_endpoint
@@ -185,10 +183,10 @@ components:
- failed_dependency
- service_unavailable
- upstream_api_error
+ - unsupported_message_type
+ - database_query_error
type: string
x-enum-varnames:
- - ErrorUnsupportedMessageType
- - ErrorDBQueryError
- ErrorJSONUnmarshaling
- ErrorNoDataFound
- ErrorNoMatchingEndpoint
@@ -200,6 +198,8 @@ components:
- ErrorFailedDependency
- ErrorServiceUnavailable
- ErrorUpstreamAPIError
+ - ErrorUnsupportedMessageType
+ - ErrorDBQueryError
bzhttp.Resp:
properties:
data:
diff --git a/ko/api-reference/guides/consensus-ratings-explained.mdx b/ko/api-reference/guides/consensus-ratings-explained.mdx
new file mode 100644
index 00000000..7957b2c6
--- /dev/null
+++ b/ko/api-reference/guides/consensus-ratings-explained.mdx
@@ -0,0 +1,320 @@
+---
+title: "컨센서스 등급 설명"
+description: "Benzinga가 개별 애널리스트의 추천을 기반으로 컨센서스 등급을 어떻게 계산하는지 알아봅니다"
+---
+
+
+ 유효한 목표가가 없는 등급은 분석에서 제외됩니다.
+
+
+
+
+ 동일한 기관에 속한 애널리스트가 투자의견을 여러 번 변경한 경우, 총 애널리스트 수에는 모든 변경 건이 포함되지만, 계산에는 가장 최근 투자의견만 사용됩니다(이는 고유 애널리스트 수에 반영됩니다).
+
+
+
+ 컨센서스 투자의견은 새로운 애널리스트 투자의견이 게시되거나 기존 투자의견이 업데이트될 때마다 다시 계산됩니다.
+
+
+
+ 애널리스트 커버리지가 없으면 컨센서스 투자의견을 계산할 수 없습니다. 해당 종목에는 컨센서스 데이터가 표시되지 않습니다.
+
+
+
+ 아닙니다. 컨센서스는 애널리스트가 새 투자의견을 발행하거나 기존 투자의견을 업데이트할 때에만 변경됩니다.
+
+
+
+***
+
+
+
+
+
+ 주식의 컨센서스 등급 데이터를 조회합니다
+
+
+
+ 개별 애널리스트 등급을 조회합니다
+
+
\ No newline at end of file
diff --git a/ko/changelog/roadmap.mdx b/ko/changelog/roadmap.mdx
new file mode 100644
index 00000000..870ece8a
--- /dev/null
+++ b/ko/changelog/roadmap.mdx
@@ -0,0 +1,120 @@
+---
+title: "로드맵"
+description: "우리가 앞으로 무엇을 개발할지 확인하세요."
+---
+
+
+새로운 기능을 요청하고 싶으신가요? [GitHub에서 이슈를 열어 주세요](https://github.com/Benzinga/benzinga-docs/issues/new) 또는 [문의하기](mailto:licensing@benzinga.com)로 연락해 주세요.
+
\ No newline at end of file
diff --git a/ko/introduction/architecture.mdx b/ko/introduction/architecture.mdx
index 61cc800c..9eee2a23 100644
--- a/ko/introduction/architecture.mdx
+++ b/ko/introduction/architecture.mdx
@@ -1,97 +1,518 @@
---
-title: 아키텍처
-description: 확장 가능한 실시간 금융 데이터 인프라
-icon: database
+title: "인프라 아키텍처"
+description: "Benzinga의 99.9% API 가용성을 뒷받침하는 엔터프라이즈급 인프라, 세계적 수준의 모니터링 및 안정성"
+icon: microchip
---
-Benzinga는 전 세계의 애플리케이션과 서비스에 실시간 금융 데이터를 제공하도록 설계된 견고하고 고도로 확장 가능한 API 인프라를 제공합니다. 속도와 가용성에 중점을 두고, Benzinga의 아키텍처는 사용자가 필요할 때마다 신뢰할 수 있는 저지연 데이터를 받을 수 있도록 **Go (Golang)**, **Kafka**, **웹소켓**, **Elasticsearch**, **마이크로서비스** 등 다양한 최신 기술을 활용합니다.
+
+ Benzinga의 인프라는 **99.9% 가용성**을 보장하도록 설계되어, 애플리케이션이 24시간 실시간 금융 데이터를 안정적으로 수신할 수 있도록 합니다. 프로덕션 환경은 실전에서 검증되었으며, 완전한 모니터링과 주 5일 24시간 온콜 엔지니어링 지원으로 뒷받침됩니다.
+
-
+ ### ノードレベルのスケーリング（Karpenter）
-パフォーマンスをさらに向上させるため、Benzinga はリアルタイムストリームや静的コンテンツを含むデータがユーザーに最小限の遅延で届くよう、**エッジキャッシング**を採用しています。世界各地に Point of Presence (PoP) を戦略的に配置することで、世界中のクライアントに対して高可用性と低レイテンシを実現しています。
+**Karpenter** はクラスターのキャパシティを次のように管理します：
-この分散アーキテクチャにより、Benzinga はクライアントの地理的な所在地に関係なく信頼性の高いリアルタイムデータを提供し、ローカルおよびグローバルなユーザー双方のニーズに対応します。
+- 60秒以内に最適なサイズのノードをプロビジョニングする
+- 活用率の低いノードを集約してコストを削減する
+- 重要度の低いワークロード向けにスポットインスタンスをサポートする
+- Pod のトポロジーおよびアベイラビリティゾーンの制約を考慮する
---
-このアーキテクチャは、最新かつスケーラブルな技術を組み合わせることで、高速で信頼性の高い金融データとインサイトを提供し、品質とパフォーマンスへの Benzinga のコミットメントを支えています。より技術的な詳細や API の利用を開始する方法については、Benzinga のサポートチームまでお問い合わせいただくか、ドキュメントをご覧ください。
\ No newline at end of file
+
+ ## 本番環境レベルのオブザーバビリティとモニタリング
+
+
+当社のインフラストラクチャは、多層的なオブザーバビリティを備えた**エンタープライズグレードのモニタリング**を採用しており、システムの健全性、パフォーマンス、信頼性を完全に可視化できるようにしています。すべてのコンポーネントは、自動アラートとインシデント対応プロセスにより継続的に監視されています。
+
+
+ ### 包括的な監視スタック
+
+
+
+ ### Coralogix: トレーシングとログ取得
+
+
+Coralogix はアプリケーション層に対する**完全なオブザーバビリティ**を提供します。
+
+
+ ### Datadog: アラートとシンセティック監視
+
+
+Datadog は**プロアクティブな監視**と継続的な検証を提供します。
+
+
+ ### Slack 連携とインシデント管理
+
+
+すべての監視システムは、即時の可視性と迅速な対応のために、**専用の Slack チャンネル** と連携しています:
+
+
+ ### アラートとインシデント
+
+
+**開発者アサインのプロセス:**
+
+1. **アラート検知** → コンテキストとメトリクス付きの自動 Slack 通知
+2. **オンコールエンジニアによるトリアージ** → 重大度を評価し、インシデント用チャンネルを作成
+3. **開発者アサイン** → 影響を受けたサービスに基づき、担当の専門エンジニアをタグ付け
+4. **調査** → Coralogix のトレースと Datadog のメトリクスを用いた根本原因分析
+5. **解決** → 標準的な GitOps パイプラインを通じて修正をデプロイ
+6. **ポストモーテム** → インシデントを文書化し、再発防止策を定義
+
+
+ ## セキュリティとコンプライアンス
+
+
+
+ ### ネットワークセキュリティ
+
+
+- **VPC 分離** — パブリックインターネットからの完全なネットワーク分離
+- **セキュリティグループ** — 厳格なインバウンド／アウトバウンドルール、デフォルト拒否ポリシー
+- **TLS の徹底適用** — すべての内部・外部トラフィックを暗号化
+- **シークレット管理** — 機密性の高い認証情報を AWS Secrets Manager で管理
+
+
+ ### アクセス制御
+
+
+- **RBAC** — すべての操作に対する Kubernetes ロールベースのアクセス制御
+- **SSO 統合** — エンタープライズ向け ID プロバイダーとの統合
+- **監査ログ** — コンプライアンス対応のために保持される完全なアクセスログ
+
+---
+
+
+ ## 災害復旧
+
+
+
+ ### 復旧目標
+
+
+| 指標 | 目標 | 現状 |
+|--------|--------|---------|
+| **RTO** (Recovery Time Objective) | 15分未満 | 約5分 |
+| **RPO** (Recovery Point Objective) | 1分未満 | リアルタイムでのレプリケーション |
+
+
+ ### レジリエンス機能
+
+
+- **マルチ AZ レプリケーション** — 可用性ゾーン間でのデータ複製
+- **自動フェイルオーバー** — Route 53 のヘルスチェックによって DNS フェイルオーバーを実行
+- **ローリングデプロイ** — ゼロダウンタイムでのデプロイと自動ロールバック
+- **バックアップとリストア** — ポイントインタイムリカバリ対応の自動日次バックアップ
+
+---
+
+
+ ## 本番環境対応の信頼性保証
+
+
+
+ ### なぜ当社のインフラは堅牢なのか
+
+
+Benzinga のインフラは、**大規模な本番環境で検証済み**であり、実運用で日次数百万件のリクエストを高い信頼性で処理しています。
+
+
+ ### モニタリングとオブザーバビリティの徹底
+
+
+当社の**包括的なモニタリング**により、問題はお客様のビジネスへ影響が及ぶ前に検知・解決されます。
+
+
+ ### クライアントからの信頼: それがお客様にもたらすもの
+
+
+Benzinga の API と連携することで、次のような仕組みによって支えられた **本番環境対応のインフラストラクチャ** に接続できます。
+
+| 機能 | クライアント側のメリット |
+|---------|----------------|
+| **マルチAZ冗長構成** | AWS アベイラビリティーゾーン障害時でも、アプリケーションはオンラインを維持します |
+| **自動スケーリング** | トラフィック急増時でも、レート制限にかかることなくシームレスにリクエストを処理します |
+| **24/7 監視** | お客様が性能低下に気付く前に、エンジニアが問題を検知して解決します |
+| **ゼロダウンタイムデプロイ** | アップデートによってサービスの可用性が中断されることはありません |
+| **完全な監査証跡** | すべてのデプロイを追跡・レビューし、即時にロールバック可能です |
+| **プロアクティブなアラート** | 潜在的な問題の 95% を、顧客への影響前に解決します |
+
+
+ ## 概要
+
+
+Benzinga のインフラストラクチャは、次の要素により **エンタープライズグレードの信頼性** を提供します。
+
+
+ ## 개요
+
+
+컨센서스 평점은 개별 애널리스트 의견을 하나의 이해하기 쉬운 지표로 집계해, 특정 종목에 대한 애널리스트 심리를 통합적으로 보여 줍니다. 이 가이드는 정보에 기반한 투자 의사결정을 내릴 수 있도록, 컨센서스 평점이 어떻게 산출되는지 설명합니다.
+
+
+ ## 컨센서스 등급이 계산되는 방식
+
+
+
+ ### 1단계: 애널리스트 의견 수집
+
+
+특정 종목에 대해 이용 가능한 모든 애널리스트 투자의견을 수집합니다. 각 의견에는 다음 정보가 포함됩니다:
+
+* **애널리스트 이름** 및 **소속 기관명**
+* **투자의견 등급** (예: Strong Buy, Buy, Hold, Sell, Strong Sell)
+* **목표가** - 애널리스트가 제시한 목표 주가
+* **업데이트 날짜** - 해당 의견이 발표된 날짜
+
+
+ ### 단계 2: 고유 애널리스트 필터링
+
+
+정확성을 높이고 이중 집계를 방지하기 위해 각 고유 애널리스트-기관 조합에 대해 **가장 최근 등급**만 포함합니다.
+
+**예시:** 예를 들어, Morgan Stanley 소속 애널리스트 John Doe가 한 종목에 여러 번 등급을 부여한 경우, 계산에는 가장 최근 등급만 포함됩니다.
+
+
+ ### 3단계: 등급 분류
+
+
+애널리스트 투자의견은 다섯 가지 표준 범주로 분류됩니다:
+
+| 범주 | 수치 값 |
+|----------|---------------|
+| **강력 매도** | 1 |
+| **매도** | 2 |
+| **보유** | 3 |
+| **매수** | 4 |
+| **강력 매수** | 5 |
+
+
+ ### 단계 4: 투자의견 집계
+
+
+각 카테고리에 속한 애널리스트 수를 집계합니다.
+
+**집계 예시:**
+
+* 강력 매수: 8명의 애널리스트
+* 매수: 12명의 애널리스트
+* 보유: 5명의 애널리스트
+* 매도: 2명의 애널리스트
+* 강력 매도: 1명의 애널리스트
+
+**총계:** 중복 없는 애널리스트 28명
+
+
+ ### 5단계: 컨센서스 등급 값 계산
+
+
+컨센서스 등급 값은 가중평균으로 계산합니다.
+
+```
+Consensus Value = (Strong Buy × 5 + Buy × 4 + Hold × 3 + Sell × 2 + Strong Sell × 1) / Total Analysts
+```
+
+**위의 예시를 기준으로 하면:**
+
+```
+Consensus Value = (8×5 + 12×4 + 5×3 + 2×2 + 1×1) / 28
+Consensus Value = (40 + 48 + 15 + 4 + 1) / 28
+Consensus Value = 108 / 28
+Consensus Value = 3.86
+```
+
+
+ ### 6단계: 컨센서스 등급 결정
+
+
+컨센서스 값은 가장 가까운 정수로 반올림한 후, 다음 등급에 매핑됩니다:
+
+| 컨센서스 값 | 표준 등급 | 단순화 등급 |
+|----------------|-----------------|-------------------|
+| **1** | 강력 매도 | 매도 |
+| **2** | 매도 | 매도 |
+| **3** | 보유 | 보유 |
+| **4** | 매수 | 매수 |
+| **5** | 강력 매수 | 매수 |
+
+**이 예시에서:** 3.86은 **4**로 반올림되며, 이는 **"매수"** 컨센서스 등급에 해당합니다.
+
+***
+
+
+ ## 표시 옵션
+
+
+
+ ### 표준형 vs. 단순형 Ratings
+
+
+다음 두 가지 표시 형식을 제공합니다.
+
+**표준형 (5개 범주):**
+
+* Strong Sell, Sell, Hold, Buy, Strong Buy
+
+**단순형 (3개 범주):**
+
+* Sell (Strong Sell + Sell 통합)
+* Hold
+* Buy (Buy + Strong Buy 통합)
+
+
+ ### 개수 vs. 백분율 표시
+
+
+**개수 표시:**
+각 범주에 속한 애널리스트 수를 그대로 표시합니다.
+
+**백분율 표시:**
+각 범주에 속한 애널리스트 비율을 표시하며, 합계가 정확히 100%가 되도록 반올림된 정수 백분율로 제공합니다.
+
+**예시:**
+
+* 매수: 71% (애널리스트 20명)
+* 보유: 18% (애널리스트 5명)
+* 매도: 11% (애널리스트 3명)
+
+***
+
+
+ ## 목표 주가 산출
+
+
+
+ ### 컨센서스 목표가
+
+
+모든 애널리스트가 제시한 목표가의 평균:
+
+```
+Consensus PT = Sum of all Price Targets / Number of Analysts
+```
+
+
+ ### 최저 및 최고 목표 주가
+
+
+* **최저 목표 주가:** 모든 애널리스트가 제시한 목표 주가 중 가장 낮은 값
+* **최고 목표 주가:** 모든 애널리스트가 제시한 목표 주가 중 가장 높은 값
+
+이는 애널리스트들이 예상하는 가격의 범위를 나타냅니다.
+
+***
+
+
+ ## 지표 이해
+
+
+
+ ### 전체 애널리스트 수 vs. 고유 애널리스트 수
+
+
+* **전체 애널리스트 수:** 수집된 모든 투자의견/평가 수(동일 애널리스트의 여러 평가 포함 가능)
+* **고유 애널리스트 수:** 서로 다른 애널리스트-펌 조합의 개수(계산에 사용)
+
+고유 수치는 각 애널리스트의 의견이 한 번만 반영되도록 하여, 더 정확한 컨센서스를 산출하는 데 도움이 됩니다.
+
+***
+
+
+ ## 중요 사항
+
+
+
+ ### 투자의견 최신성
+
+
+컨센서스 투자의견은 가장 최근 애널리스트 의견을 반영합니다. **Updated At** 타임스탬프는 컨센서스가 마지막으로 계산된 시점을 나타냅니다.
+
+
+ ### 커버리지 깊이
+
+
+컨센서스 레이팅은 서로 다른 애널리스트 수가 많을수록 신뢰성이 높습니다. 애널리스트 커버리지가 제한적인 종목(커버하는 애널리스트가 3–5명 미만인 경우)은 컨센서스 레이팅이 상대적으로 덜 안정적일 수 있습니다.
+
+
+ ### 투자 의견 분포
+
+
+컨센서스만 보지 말고, 투자 의견이 어떻게 분포되어 있는지도 함께 살펴봐야 합니다. 매수 의견이 50%, 매도 의견이 50%인 종목은 컨센서스가 "보유"로 표시되지만, 이는 애널리스트들 사이의 상당한 의견 차이를 가려버릴 수 있습니다.
+
+***
+
+
+ ## 예시 계산 과정 살펴보기
+
+
+**XYZ Corporation**에 대한 예시를 단계별로 살펴보겠습니다:
+
+
+ ### 원시 데이터 (애널리스트 10명)
+
+
+| 애널리스트 | 회사 | 투자의견 | 목표가 |
+|---------|------|--------|--------------|
+| 애널리스트 A | Goldman Sachs | 매수 | $150 |
+| 애널리스트 B | JP Morgan | 강력 매수 | $165 |
+| 애널리스트 C | Morgan Stanley | 매수 | $155 |
+| 애널리스트 D | Bank of America | 보유 | $140 |
+| 애널리스트 E | Citigroup | 강력 매수 | $170 |
+| 애널리스트 F | Wells Fargo | 매수 | $152 |
+| 애널리스트 G | Deutsche Bank | 보유 | $145 |
+| 애널리스트 H | Barclays | 매도 | $130 |
+| 애널리스트 I | UBS | 매수 | $158 |
+| 애널리스트 J | Credit Suisse | 강력 매수 | $168 |
+
+
+ ### 단계별 계산
+
+
+**1. 고유 애널리스트 필터링:** 10개 평점이 모두 서로 다른 애널리스트로부터 나온 것이므로, 고유 애널리스트 수는 10명입니다(애널리스트 10명 사용).
+
+**2. 개수 집계:**
+
+* Strong Buy: 3
+* Buy: 4
+* Hold: 2
+* Sell: 1
+* Strong Sell: 0
+
+**3. 컨센서스 값 계산:**
+
+```
+(3×5 + 4×4 + 2×3 + 1×2 + 0×1) / 10 = (15 + 16 + 6 + 2 + 0) / 10 = 3.9
+```
+
+**4. 컨센서스 결정:** 3.9를 반올림하면 **4 = "Buy"**
+
+**5. 목표가:**
+
+* 컨센서스 목표가: (150+165+155+140+170+152+145+130+158+168) / 10 = **$153.30**
+* 최저 목표가: **$130**
+* 최고 목표가: **$170**
+
+**6. 비율 분포:**
+
+* Buy: 70% (Strong Buy 30% + Buy 40%)
+* Hold: 20%
+* Sell: 10%
+
+
+ ### 최종 컨센서스 등급 결과
+
+
+```json
+{
+ "consensusRating": "BUY",
+ "consensusRatingValue": 3.9,
+ "consensusPriceTarget": 153.30,
+ "priceTargetLow": 130,
+ "priceTargetHigh": 170,
+ "totalAnalysts": 10,
+ "uniqueAnalysts": 10,
+ "lastUpdated": "2026-01-16T10:30:00Z"
+}
+```
+
+***
+
+
+ ## 자주 묻는 질문
+
+
+
+ {/* 진행 중 */}
+
+
+
+---
+
+
+
+
+ {/* 예정 */}
+
+
+
+
+ 진행 중
+
+
+
+
+
+
+
+ 실적발표 콜 전문 PDF 버전
+ 실적발표 콜 전문을 PDF 형식으로 다운로드할 수 있도록 제공합니다.
+
+
+ 실적발표 콜 전문 과거 데이터 범위 확장
+ 실적발표 콜 전문에 대해 제공되는 과거 데이터 범위를 확장합니다.
+
+
+
+ {/* 백로그 */}
+
+
+
+
+ 예정
+
+
+
+
+
+
+
+ 모니터링 대시보드 고도화
+ 모든 서비스 상품에 대한 모니터링을 제공하는 고객용 대시보드.
+
+
+
+ 번역 엔진 최적화
+ 번역 서비스의 성능 및 품질 개선.
+
+
+ 뉴스용 Security Master 연동
+ 사내 Security Master를 연동해 조회 기능을 강화.
+
+
+
+ {/* 완료됨 */}
+
+
+
+
+ 백로그
+
+
+
+
+
+
+
+ Go SDK
+ 공식 Go 클라이언트 라이브러리.
+
+
+ 모든 calendar용 웹소켓
+ 모든 calendar 엔드포인트에 대한 실시간 스트리밍 지원.
+
+
+
+
+
+ 완료
+
+
+
+
+
+
+
+ 사내 Security Master
+ 데이터 일관성을 높이기 위한 중앙집중식 Security Master.
+
+
+
+ TCP 스트리밍
+ 실시간 데이터를 위한 저지연 TCP 연결.
+
+
+
+ 컨퍼런스 콜 회의록
+ 발언자 식별이 포함된 전체 회의록.
+
+
+
+ Webhook 엔진
+ 푸시 기반 데이터 전송.
+
+
+ Java SDK
+ 공식 Java 클라이언트 라이브러리.
+
- ## Go와 Kafka를 활용한 고성능 아키텍처
+
-
+
+
+ 다중 AZ 이중화를 통한 검증된 프로덕션 안정성
+
+
+ Coralogix 및 Datadog 기반 실시간 가시성
+
+
+ 지능형 오토스케일링을 통한 무중단 배포
+
+
-
+ ## 개요
-Benzinga의 인프라는 뛰어난 동시성과 속도를 제공하는 **Go (Golang)**으로 구축되어 대규모 금융 데이터 트래픽을 효율적으로 처리합니다. 데이터 파이프라인과 실시간 스트리밍은 **Kafka**를 기반으로 하며, 이를 통해 지연을 최소화하면서 빠른 데이터 수집, 처리, 배포가 가능합니다. 이 아키텍처는 글로벌 배포 환경 전반에서 확장성과 안정성을 보장해 실시간 금융 데이터 제공에 대한 요구를 충족합니다.
+당사의 플랫폼은 AWS 관리형 서비스, Kubernetes 오케스트레이션, GitOps 배포 방식을 활용하는 현대적인 클라우드 네이티브 아키텍처 위에 구축되어 있습니다. 이 **프로덕션급 인프라**는 포괄적인 가시성과 자동 확장 기능을 통해 매일 수백만 건의 API 요청을 처리하면서도 100ms 미만의 응답 시간을 유지합니다.
-
-
-
+
- ## 웹소켓 및 REST API를 통한 실시간 데이터 액세스
+
+
+---
+
+
+
+ 장애 허용성을 위해 여러 가용 영역(Availability Zone)에 서비스를 배포합니다
+
+
+ 엄격한 보안 그룹 정책이 적용된 격리된 Virtual Private Cloud
+
+
+ 상태 점검(Health Check)과 자동 장애 조치 라우팅을 지원하는 글로벌 DNS
+
+
+ AWS에서 관리되는 Kubernetes 제어 플레인으로 99.95% SLA 제공
+
+
+
+
+
+ 엣지에서 API 키 검증 및 JWT 토큰 검증 수행
+
+
+ 공정한 리소스 할당을 보장하기 위한 클라이언트별 요청 속도 제한
+
+
+ 정상 서비스 파드 간 지능형 트래픽 분산
+
+
+ 모든 트래픽을 TLS 1.3으로 암호화하고 인증서를 자동 갱신
+
+
+
+
+ ## 핵심 인프라
+
+
+
+ ### AWS 클라우드 기반
+
+
+당사 인프라는 전적으로 **Amazon Web Services (AWS)** 에서 운영되며, 다음과 같은 이점을 활용합니다:
+
+
+ ### Kubernetes 인프라
+
+
+우리는 안전한 배포와 환경 격리를 보장하기 위해 **두 개의 전용 Kubernetes 클러스터**를 운영합니다:
+
+| 환경 | 목적 | 배포 흐름 |
+|-------------|---------|-----------------|
+| **Staging 클러스터** | 개발자 테스트, QA 검증, 통합 테스트 | 코드 변경 사항을 먼저 배포해 검증 |
+| **Production 클러스터** | SLA가 보장되는 실시간 고객 트래픽 처리 | 검증된 릴리스만 승격 |
+
+
+ #### 주요 Kubernetes 컴포넌트
+
+
+- **Karpenter** — 분 단위가 아닌 수 초 만에 적정 규모의 컴퓨팅 리소스를 프로비저닝하는 AWS 네이티브 노드 오토스케일러
+- **Horizontal Pod Autoscaler (HPA)** — CPU, 메모리 및 사용자 정의 메트릭 기반의 자동 Pod 스케일링
+- **Kong Gateway** — 인그레스/이그레스, 요청 속도 제한(rate limiting), 인증을 처리하는 엔터프라이즈급 API 게이트웨이
+- **ArgoCD** — 선언적이고 감사 추적이 가능한 릴리스를 위한 GitOps 기반 배포 컨트롤러
+
+---
+
+
+ ## API 게이트웨이 및 트래픽 관리
+
+
+
+ ### Kong Gateway
+
+
+모든 API 트래픽은 **Kong Gateway**를 통해 흐르며 다음 기능을 제공합니다:
+
+
+ ### Route 53 DNS
-Benzinga의 API는 **웹소켓**과 **REST** 프로토콜을 모두 지원하므로, 클라이언트는 실시간 데이터에 접근하고 필요 시 온디맨드 요청을 보낼 수 있습니다. 웹소켓 연결은 실시간 시세 및 거래 데이터와 같은 지속적인 데이터 피드가 필요한 애플리케이션에 적합하며, REST API는 과거 데이터, 기업 기초 재무 지표, 뉴스, 분석 데이터에 대한 다양한 요청을 처리합니다.
+AWS Route 53는 다음 기능을 제공합니다:
+
+- **글로벌 지연 시간 기반 라우팅** — 사용자가 자동으로 가장 빠른 엔드포인트로 라우팅됨
+- **헬스 체크** — 장애 발생 시 자동 장애 조치를 포함한 지속적인 모니터링
+- **100% 가동 시간 SLA** — DNS 해석에 대해 AWS가 보증하는 가용성
-
- ### API 주요 기능
+---
+
+
+ ## CI/CD 파이프라인
-- **실시간 시세 데이터**: 실시간 시세, 체결, 기타 핵심 시장 데이터를 스트리밍합니다.
-- **과거 데이터**: 바(bar) 데이터, 시세, 기간별 시장 성과를 포함한 과거 데이터를 조회합니다.
-- **뉴스 및 인사이트**: 실시간 뉴스와 시장에 영향을 주는 인사이트를 지속적으로 확인합니다.
-- **회사 기초 재무 지표**: 매출, 이익, 주요 비율과 같은 핵심 재무 지표를 조회합니다.
+배포 파이프라인은 코드가 프로덕션 환경에 반영되기 전에 엄격한 품질 게이트를 강제합니다.
-
- ## Elasticsearch를 통한 데이터 저장 및 검색 효율화
+
-
-
-
+ ### 개발 워크플로
-효율적인 데이터 검색 및 저장을 위해 Benzinga는 검색 및 인덱싱 시스템의 핵심 구성 요소로 **Elasticsearch**를 사용합니다. Elasticsearch는 정형·비정형 데이터를 모두 빠르게 액세스할 수 있게 해 주며, 사용자가 과거 데이터와 뉴스 아카이브 등 대규모 데이터셋을 밀리초 단위 응답 속도로 빠르게 조회할 수 있도록 합니다. 이 아키텍처는 분석 작업도 지원하여, 클라이언트가 데이터를 분석하고 그로부터 가치 있는 인사이트를 도출할 수 있게 합니다.
+```mermaid
+flowchart LR
+ A[Developer Commit] --> B[GitLab CI Pipeline]
+ B --> C{Linting & Tests}
+ C -->|Pass| D[Build Container Image]
+ C -->|Fail| E[Reject & Notify]
+ D --> F[Push to Registry]
+ F --> G[Peer Review Required]
+ G -->|2 Approvals| H[Update GitOps Repo]
+ H --> I[ArgoCD Sync]
+ I --> J[Deploy to Staging]
+ J -->|Validated| K[Promote to Production]
+```
-
-
-
-
-
- ## 확장성을 위한 마이크로서비스 기반 인프라
+
+ ### 파이프라인 단계
-Benzinga의 아키텍처는 **마이크로서비스** 방식에 기반하며, 각 서비스는 데이터 수집, 처리, 저장 또는 전달과 같은 특정 기능을 담당합니다. 이러한 모듈식 접근 방식은 확장성을 높여 각 구성 요소가 수요에 따라 독립적으로 확장될 수 있도록 합니다. 또한 마이크로서비스는 경량 프로토콜을 통해 통신하여 전체 시스템 전반에 걸쳐 낮은 지연 시간과 높은 탄력성을 제공합니다.
+| 단계 | 설명 | 품질 게이트 |
+|-------|-------------|--------------|
+| **Lint** | 코드 스타일 및 정적 분석 검사 | 모든 규칙 통과 필수 |
+| **Unit Tests** | 자동화된 테스트 스위트 실행 | 100% 테스트 통과 |
+| **Security Scan** | 컨테이너 취약점 스캔 | 치명적/높은 심각도의 CVE 없음 |
+| **Build** | 커밋 SHA로 태그된 Docker 이미지 생성 | 빌드 성공 |
+| **Peer Review** | 2명의 개발자가 수행하는 수동 코드 리뷰 | 두 명의 승인 필요 |
+| **GitOps Update** | ArgoCD 리포지토리에서 이미지 태그 업데이트 | 수동 승급 |
-
- ## 이미지 및 정적 콘텐츠를 위한 CDN 기반 제공
+
+ ### ArgoCD를 사용한 GitOps
-이미지, 로고 및 기타 정적 자산을 빠르게 제공하기 위해 Benzinga는 **CDN**(Content Delivery Network)을 사용합니다. 이 아키텍처는 정적 리소스를 사용자와 가까운 위치에 캐시하여 로드 시간을 줄이고 지연을 최소화하며, 사용자의 지리적 위치와 관계없이 이미지와 파일이 거의 즉시 로드되도록 합니다.
+모든 배포는 GitOps 원칙을 따르며 **ArgoCD**를 통해 관리됩니다:
+
+- **선언적(Declarative)** — 원하는 상태를 Git에 정의하고 이를 단일 신뢰 소스로 사용
+- **자동 동기화(Automated sync)** — ArgoCD가 변경 사항을 감지하고 자동으로 적용
+- **롤백 기능(Rollback capability)** — Git 커밋을 되돌려 즉시 롤백 가능
+- **감사 추적(Audit trail)** — Git 커밋 로그를 통해 전체 배포 이력 확인 가능
-
- ## Benzinga 아키텍처의 주요 이점
+
+ 모든 프로덕션 변경 사항은 특정 Git 커밋, 동료 검토, 승인자까지 추적 가능하므로, 컴플라이언스 요구사항을 충족하는 완전한 감사 가능성을 보장합니다.
+
+
+---
+
+
+ ## 자동 확장 아키텍처
-- **확장성**: 수평 확장이 가능하도록 설계되어, 분당 수백만 건의 요청과 대규모 동시 웹소켓 연결을 지원합니다.
-- **고가용성**: 이중화된 시스템과 지리적으로 분산된 구성요소를 통해 업타임과 데이터 가용성을 보장합니다.
-- **데이터 일관성**: Kafka와 Elasticsearch를 함께 사용해 일관된 데이터 흐름과 조회를 제공하며, 신뢰할 수 있는 페일오버 메커니즘을 갖추고 있습니다.
-- **저지연**: Go의 성능, Kafka의 스트리밍, 웹소켓의 실시간 기능을 활용해 지연 시간을 최소화하도록 최적화되어 있습니다.
+당사 인프라는 트래픽 급증을 처리하기 위해 여러 수준에서 자동으로 확장됩니다.
-
- ## 배포 유연성과 인프라 통합
+
+ ### Pod 수준 스케일링 (HPA)
-Benzinga의 아키텍처는 다양한 고객 요구를 충족할 수 있도록 유연한 배포 옵션을 지원합니다:
+각 서비스 배포에는 Horizontal Pod Autoscaler 구성이 포함됩니다:
+
+```yaml
+# HPA 구성 예제
+apiVersion: autoscaling/v2
+kind: HorizontalPodAutoscaler
+spec:
+ minReplicas: 3
+ maxReplicas: 50
+ metrics:
+ - type: Resource
+ resource:
+ name: cpu
+ target:
+ type: Utilization
+ averageUtilization: 70
+```
-- **관리형 클라우드 서비스**: 원활한 사용 경험을 원하는 고객을 위해 Benzinga는 자동 확장과 유지 관리를 포함한 완전 관리형 클라우드 서비스를 제공합니다.
-- **자체 호스팅 옵션**: 더 많은 제어 권한이 필요한 경우 Benzinga의 아키텍처를 온프레미스 배포나 프라이빗 클라우드 환경에 맞게 구성할 수 있어, 데이터 소유권을 완전히 유지하면서 지역 규제를 준수할 수 있습니다.
+**스케일링 트리거:**
-
- ### 에지 캐싱을 통한 글로벌 서비스
+* CPU 사용률 > 70%
+* 메모리 사용률 > 80%
+* 사용자 정의 지표(요청 큐 깊이, 지연 시간 백분위수)
+
+
+
+
+ **분산 트레이싱 및 로깅**
+ - 모든 서비스의 실시간 로그 수집
+ - 마이크로서비스 전반에 대한 분산 트레이싱
+ - 애플리케이션 성능 모니터링(APM)
+ - Correlation ID를 통한 엔드 투 엔드 요청 추적
+ - 로그 패턴 인식 및 이상 감지
+ - 비즈니스 지표용 사용자 정의 대시보드
+
+
+ **알림 및 합성 모니터링**
+ - 24/7 지속적인 API 엔드포인트 테스트
+ - 다중 리전 합성 모니터링
+ - 응답 시간 및 가용성 추적
+ - 지능형 라우팅을 통한 자동 알림
+ - 서비스 수준 지표(SLI) 추적
+ - 성능 회귀(regression) 감지
+
+
+
+
+
+ 모든 서비스, 파드, 컨테이너에서 발생하는 애플리케이션 로그를 실시간으로 수집하여, 전체 인프라 전반에 대한 디버깅 정보를 즉시 확인할 수 있습니다.
+
+
+ 모든 API 요청을 마이크로서비스, 로드 밸런서, 데이터베이스, 외부 서비스 전 구간에 걸쳐 엔드투엔드로 추적합니다. 이를 통해 성능 문제나 오류의 근본 원인을 신속하게 분석할 수 있습니다.
+
+
+ 스택 트레이스, 컨텍스트 정보, 영향받은 사용자 수를 포함한 자동 오류 감지를 제공합니다. 오류는 심각도와 영향 범위에 따라 분류됩니다.
+
+
+ 모든 서비스에 대한 API 응답 시간, 처리량, 오류율, 리소스 사용량의 실시간 메트릭을 제공합니다.
+
+
+
+**프로덕션 환경에서의 주요 Coralogix 기능:**
+
+- **보관 정책(Retention Policy)**: 즉시 조회를 위한 30일 핫 스토리지, 규제 준수를 위한 90일 아카이브
+- **쿼리 성능**: 수십억 건의 로그 항목에 대해 1초 미만 응답의 쿼리 처리
+- **알림 연동**: Slack 채널 및 온콜 담당 엔지니어에게 자동 라우팅
+- **커스텀 대시보드**: 비즈니스별 메트릭을 이해관계자가 실시간으로 확인 가능
+
+
+
+ 자동화된 테스트가 여러 지리적 리전에서 60초마다 실행되어, 고객에게 문제가 발생하기 전에 API 가용성, 응답 시간, 데이터 정확성을 검증합니다.
+
+
+ 머신러닝 기반 이상 징후 탐지가 메트릭에서 비정상 패턴을 식별하여, 문제가 고객에게 영향을 미치기 전에 알림을 트리거합니다.
+
+
+ 서비스 수준 목표(SLO)를 실시간으로 추적하고, 99.9% 가용성 목표에 대한 보고를 자동화합니다.
+
+
+ p50, p95, p99 지연 시간 퍼센타일을 지속적으로 모니터링하여 일관된 성능을 보장합니다.
+
+
+
+**Datadog Synthetic 테스트에는 다음이 포함됩니다:**
+
+| 테스트 유형 | 빈도 | 리전 | 모니터링 메트릭 |
+|-----------|-----------|---------|-----------------|
+| **API 상태 점검(Health Check)** | 60초마다 | 전 세계 5개 리전 | 가용성, 응답 시간, 상태 코드 |
+| **데이터 정확성 테스트** | 5분마다 | 3개 리전 | 데이터 최신성, 스키마 검증, 무결성 |
+| **성능 테스트** | 60초마다 | 5개 리전 | 지연 시간(p50/p95/p99), 처리량, 오류율 |
+| **인증 테스트** | 5분마다 | 2개 리전 | API 키 검증, 요청 제한(rate limiting), OAuth 플로우 |
+
+
+
+ **중요 알림**
+
+ * 즉각적인 조치가 필요한 P1/P2 등급 인시던트
+ * 온콜 엔지니어 자동 호출
+ * 실시간 메트릭 및 런북 링크
+ * 인시던트 커맨더 배정
+
+
+
+ **성능 인사이트**
+
+ * 일일 상태 요약
+ * 용량 계획 관련 알림
+ * 성능 추세 알림
+ * 이상 탐지 경고
+
+
+
+**Slack 알림 워크플로우:**
+
+```mermaid
+flowchart LR
+ A[Alert Triggered] --> B{Severity Level}
+ B -->|P1/P2| C[#alerts-production]
+ B -->|P3/P4| D[#monitoring-insights]
+ C --> E[On-Call Engineer Paged]
+ C --> F[Incident Channel Created]
+ F --> G[Developer Assigned]
+ G --> H[Root Cause Investigation]
+ H --> I[Fix Deployed]
+ I --> J[Post-Mortem Report]
+```
+
+
+
+ 모든 P1/P2 인시던트에 대해 24/5 커버리지를 가진 온콜 엔지니어에게 **즉각적인 자동 페이징(paging)**이 전송됩니다.
+
+
+
+ 사전 알림과 자동 복구를 통해, 모니터링 시스템이 **고객에게 영향이 가기 전 잠재적 이슈의 95%를 탐지하고 해결**했습니다.
+
+
+---
+
+
+
+ **프로덕션 통계**
+ - 하루 1,000만 건 이상의 API 요청 처리
+ - 평균 응답 시간 100ms 미만
+ - 99.9%의 누적 가용성 달성
+ - 3년 이상 데이터 손실 0건
+
+
+ **운영 우수성**
+ - 연중 평일 24시간 온콜 엔지니어 지원
+ - 자동 페일오버 및 자가 복구
+ - 멀티 리전 이중화 구성
+
+
+
+
+
+ 모든 요청, 로그, 메트릭을 Coralogix 분산 트레이싱과 중앙 집중식 로깅으로 엔드투엔드(end-to-end) 추적합니다
+
+
+ Datadog 합성 모니터링(synthetic monitoring)이 여러 리전에서 60초마다 API를 테스트하여, 고객에게 영향이 가기 전에 문제를 사전 경고합니다
+
+
+ 자동화된 Slack 연동을 통해 경보를 전용 채널로 전달하고, 개발자를 즉시 할당하여 해결 진행 상황을 추적합니다
+
+
+ 모든 인시던트에 대해 사후 분석(post-mortem)을 수행하고 자동화된 예방 조치를 적용하여, 동일한 문제가 재발하지 않도록 합니다
+
+
+
+
+ **프로덕션 준비 완료**: 당사의 인프라는 **수십억 건의 API 요청**을 처리하면서 99.9% 가용성을 유지해 왔으며, 실시간 금융 데이터 전송 시 100ms 미만의 지연 시간을 유지합니다.
+
+
+---
+
+
+
+ 최대 가용성을 보장하는 멀티 AZ 배포 및 관리형 컨트롤 플레인을 갖춘 AWS EKS
+
+
+ 전체 감사 이력과 즉시 롤백 기능을 제공하는 ArgoCD 기반 릴리스
+
+
+ 트래픽 급증을 자동으로 처리할 수 있도록 원활한 용량 관리를 제공하는 Karpenter + HPA
+
+
+ Coralogix 트레이싱/로깅 + Datadog 알림/합성(Synthetics) 모니터링과 Slack 연동을 통한 신속한 장애 대응
+
+
+ 전담 온콜(on-call) 엔지니어
+
+
+ 암호화, RBAC, 네트워크 격리를 통한 다계층 방어로 데이터를 보호
+
+
+
+
+ **고객 성공이 최우선입니다**: 인프라, SLA 보장 사항 또는 귀사의 구체적인 신뢰성 요구 사항 논의와 관련된 문의는 담당 어카운트 매니저에게 연락하시거나 [support@benzinga.com](mailto:support@benzinga.com)으로 이메일을 보내주시기 바랍니다.
+
\ No newline at end of file
diff --git a/ko/openapi/calendar_api.spec.yml b/ko/openapi/calendar_api.spec.yml
index a11ece30..7dc356f2 100644
--- a/ko/openapi/calendar_api.spec.yml
+++ b/ko/openapi/calendar_api.spec.yml
@@ -2757,14 +2757,19 @@ components:
calendarapi.AggregateRating:
properties:
buy:
+ example: 10
type: integer
hold:
+ example: 3
type: integer
sell:
+ example: 1
type: integer
strong_buy:
+ example: 5
type: integer
strong_sell:
+ example: 0
type: integer
type: object
calendarapi.AnalystInsightsJSON:
@@ -2804,22 +2809,31 @@ components:
aggregate_ratings:
$ref: "#/components/schemas/calendarapi.AggregateRating"
aggregate_type:
+ example: 90D
type: string
consensus_price_target:
+ example: 195.5
type: number
consensus_rating:
+ example: Buy
type: string
consensus_rating_val:
+ example: 4.2
type: number
high_price_target:
+ example: 225
type: number
low_price_target:
+ example: 150
type: number
total_analyst_count:
+ example: 19
type: integer
unique_analyst_count:
+ example: 15
type: integer
updated_at:
+ example: 2024-01-09T16:00:00Z
type: string
type: object
calendarapi.DividendJSON:
@@ -2905,40 +2919,53 @@ components:
calendarapi.InsiderTransaction:
properties:
accession_number:
+ example: 0001127602-24-000123
type: string
company_cik:
+ example: 320193
type: string
company_name:
+ example: Apple Inc.
type: string
company_symbol:
+ example: AAPL
type: string
filing_date:
+ example: 2024-01-09T00:00:00Z
type: string
footnotes:
items:
$ref: "#/components/schemas/calendarapi.SECFootnotes"
type: array
form_type:
+ example: "4"
type: string
html_url:
+ example: https://www.sec.gov/cgi-bin/browse-edgar?action=getcompany&CIK=0000320193
type: string
id:
+ example: 64a1b2c3d4e5f6789012345
type: string
is_10b5:
+ example: true
type: boolean
owner:
$ref: "#/components/schemas/calendarapi.Owner"
remaining_shares:
+ example: "125000"
type: string
remaining_underlying_shares:
+ example: "50000"
type: string
traded_percentage:
+ example: "15.5"
type: string
transactions:
items:
$ref: "#/components/schemas/calendarapi.Transaction"
type: array
updated:
+ example: 1704758400
type: integer
type: object
calendarapi.InsiderTransactionFilingDoc:
@@ -2975,18 +3002,25 @@ components:
calendarapi.Owner:
properties:
insider_cik:
+ example: "0001234567"
type: string
insider_name:
+ example: Tim Cook
type: string
insider_title:
+ example: Chief Executive Officer
type: string
is_director:
+ example: true
type: boolean
is_officer:
+ example: true
type: boolean
is_ten_percent_owner:
+ example: false
type: boolean
raw_signature:
+ example: /s/ Tim Cook
type: string
type: object
calendarapi.RatingJSON:
@@ -3032,8 +3066,10 @@ components:
calendarapi.SECFootnotes:
properties:
id:
+ example: F1
type: string
text:
+ example: Shares were sold pursuant to a Rule 10b5-1 trading plan
type: string
type: object
calendarapi.SplitJSON:
@@ -3047,40 +3083,58 @@ components:
calendarapi.Transaction:
properties:
acquired_or_disposed:
+ example: D
type: string
conversion_exercise_price_derivative:
+ example: "150.25"
type: string
date_deemed_execution:
+ example: 2024-01-09T00:00:00Z
type: string
date_exercisable:
+ example: 2024-01-09T00:00:00Z
type: string
date_expiration:
+ example: 2025-01-09T00:00:00Z
type: string
date_transaction:
+ example: 2024-01-09T00:00:00Z
type: string
is_derivative:
+ example: false
type: boolean
ownership:
+ example: Direct
type: string
post_transaction_quantity:
+ example: "250000"
type: string
price_per_share:
+ example: "150.25"
type: string
remaining_underlying_shares:
+ example: "50000"
type: string
security_title:
+ example: Common Stock
type: string
shares:
+ example: "10000"
type: string
transaction_code:
+ example: S
type: string
transaction_id:
+ example: TXN-20240109-001
type: string
underlying_security_title:
+ example: Common Stock
type: string
underlying_shares:
+ example: "10000"
type: string
voluntarily_reported:
+ example: false
type: boolean
type: object
servers:
diff --git a/ko/openapi/data-api-proxy_api.spec.yml b/ko/openapi/data-api-proxy_api.spec.yml
index 7bd9bf7d..f0435094 100644
--- a/ko/openapi/data-api-proxy_api.spec.yml
+++ b/ko/openapi/data-api-proxy_api.spec.yml
@@ -1339,6 +1339,8 @@ components:
type: object
bzhttp.ErrorCode:
enum:
+ - unsupported_message_type
+ - database_query_error
- json_unmarshaling_error
- no_data_found
- no_matching_endpoint
@@ -1350,10 +1352,10 @@ components:
- failed_dependency
- service_unavailable
- upstream_api_error
- - unsupported_message_type
- - database_query_error
type: string
x-enum-varnames:
+ - ErrorUnsupportedMessageType
+ - ErrorDBQueryError
- ErrorJSONUnmarshaling
- ErrorNoDataFound
- ErrorNoMatchingEndpoint
@@ -1365,8 +1367,6 @@ components:
- ErrorFailedDependency
- ErrorServiceUnavailable
- ErrorUpstreamAPIError
- - ErrorUnsupportedMessageType
- - ErrorDBQueryError
bzhttp.Resp:
properties:
data:
diff --git a/ko/openapi/logo-api_api.spec.yml b/ko/openapi/logo-api_api.spec.yml
index 1f271735..217cb660 100644
--- a/ko/openapi/logo-api_api.spec.yml
+++ b/ko/openapi/logo-api_api.spec.yml
@@ -144,6 +144,12 @@ paths:
name: max_width
schema:
type: string
+ - description: true인 경우 flutter_svg 라이브러리와의 호환성을 위해 SVG URL에
+ flutter_compatible=true 쿼리 매개변수를 추가합니다.
+ in: query
+ name: flutter_compatible
+ schema:
+ type: boolean
responses:
"200":
description: data 필드에 LogoClientResponse 객체 배열을 포함하는 성공 응답
diff --git a/ko/openapi/newsquantified-api_api.spec.yml b/ko/openapi/newsquantified-api_api.spec.yml
index e85a6c6d..04e44ca4 100644
--- a/ko/openapi/newsquantified-api_api.spec.yml
+++ b/ko/openapi/newsquantified-api_api.spec.yml
@@ -108,8 +108,6 @@ components:
type: object
bzhttp.ErrorCode:
enum:
- - unsupported_message_type
- - database_query_error
- json_unmarshaling_error
- no_data_found
- no_matching_endpoint
@@ -121,10 +119,10 @@ components:
- failed_dependency
- service_unavailable
- upstream_api_error
+ - unsupported_message_type
+ - database_query_error
type: string
x-enum-varnames:
- - ErrorUnsupportedMessageType
- - ErrorDBQueryError
- ErrorJSONUnmarshaling
- ErrorNoDataFound
- ErrorNoMatchingEndpoint
@@ -136,6 +134,8 @@ components:
- ErrorFailedDependency
- ErrorServiceUnavailable
- ErrorUpstreamAPIError
+ - ErrorUnsupportedMessageType
+ - ErrorDBQueryError
bzhttp.Resp:
properties:
data:
diff --git a/ko/openapi/ticker-trends-api_api.spec.yml b/ko/openapi/ticker-trends-api_api.spec.yml
index 5f923aea..a3d728df 100644
--- a/ko/openapi/ticker-trends-api_api.spec.yml
+++ b/ko/openapi/ticker-trends-api_api.spec.yml
@@ -177,8 +177,6 @@ components:
type: object
bzhttp.ErrorCode:
enum:
- - unsupported_message_type
- - database_query_error
- json_unmarshaling_error
- no_data_found
- no_matching_endpoint
@@ -190,10 +188,10 @@ components:
- failed_dependency
- service_unavailable
- upstream_api_error
+ - unsupported_message_type
+ - database_query_error
type: string
x-enum-varnames:
- - ErrorUnsupportedMessageType
- - ErrorDBQueryError
- ErrorJSONUnmarshaling
- ErrorNoDataFound
- ErrorNoMatchingEndpoint
@@ -205,6 +203,8 @@ components:
- ErrorFailedDependency
- ErrorServiceUnavailable
- ErrorUpstreamAPIError
+ - ErrorUnsupportedMessageType
+ - ErrorDBQueryError
bzhttp.Resp:
properties:
data:
+ ### 노드 수준 스케일링 (Karpenter)
-성능을 더욱 향상하기 위해 Benzinga는 **에지 캐싱(Edge Caching)** 을 활용하여 실시간 스트림과 정적 콘텐츠를 포함한 데이터가 최소한의 지연으로 사용자에게 도달하도록 합니다. 전 세계에 전략적으로 Points of Presence(PoP)를 배치함으로써 Benzinga는 전 대륙의 클라이언트에게 높은 가용성과 낮은 지연 시간을 제공합니다.
+**Karpenter**는 클러스터 용량을 다음과 같이 관리합니다.
-이 분산 아키텍처를 통해 Benzinga는 지리적 위치와 관계없이 클라이언트에게 신뢰할 수 있는 실시간 데이터를 제공하여 로컬 및 글로벌 사용자의 요구를 모두 충족합니다.
+- 60초 이내에 최적 크기의 노드를 프로비저닝합니다
+- 비용 절감을 위해 저활용 노드를 통합합니다
+- 비핵심 워크로드에 대해 스팟 인스턴스를 지원합니다
+- 파드 토폴로지 및 가용 영역 제약 조건을 준수합니다
---
-이 아키텍처는 현대적이고 확장 가능한 기술을 결합하여 빠르고 안정적인 금융 데이터와 인사이트를 제공하며, 품질과 성능에 대한 Benzinga의 약속을 뒷받침합니다. 더 자세한 기술 정보가 필요하거나 API 사용을 시작하려면 Benzinga 지원 팀에 문의하시거나 문서를 참조하십시오.
\ No newline at end of file
+
+ ## 프로덕션 수준의 오브저버빌리티 및 모니터링
+
+
+우리 인프라는 여러 계층의 오브저버빌리티를 갖춘 **엔터프라이즈급 모니터링**을 적용해 시스템 상태, 성능, 신뢰성에 대한 완전한 가시성을 보장합니다. 모든 컴포넌트는 자동 경보 및 인시던트 대응 프로토콜과 함께 상시 모니터링됩니다.
+
+
+ ### 포괄적인 모니터링 스택
+
+
+
+ ### Coralogix: 트레이싱 및 로깅
+
+
+Coralogix는 애플리케이션 계층에 대한 **완전한 가시성(Observability)** 을 제공합니다:
+
+
+ ### Datadog: 알림 및 Synthetics
+
+
+Datadog은 **사전 예방적 모니터링**과 지속적인 검증 기능을 제공합니다:
+
+
+ ### Slack 연동 & 인시던트 관리
+
+
+모든 모니터링 시스템은 **전용 Slack 채널**과 연동되어 즉각적인 가시성과 빠른 대응을 제공합니다:
+
+
+ ### 알림 및 인시던트
+
+
+**개발자 배정 프로세스:**
+
+1. **알림 발생** → 컨텍스트와 메트릭이 포함된 자동 Slack 알림 전송
+2. **온콜 엔지니어 트리아지** → 심각도 평가 및 인시던트 채널 생성
+3. **개발자 배정** → 영향받은 서비스 기준으로 담당 전문가 태깅
+4. **조사** → Coralogix 트레이스와 Datadog 메트릭을 활용한 근본 원인 분석
+5. **해결** → 표준 GitOps 파이프라인을 통한 수정 사항 배포
+6. **사후 분석(Post-Mortem)** → 예방 조치를 포함한 인시던트 문서화
+
+
+ ## 보안 및 컴플라이언스
+
+
+
+ ### 네트워크 보안
+
+
+- **VPC 격리** — 퍼블릭 인터넷으로부터 완전한 네트워크 분리
+- **보안 그룹(Security Groups)** — 엄격한 인바운드/아웃바운드 규칙, 기본 거부(deny-by-default) 정책
+- **전 구간 TLS(TLS Everywhere)** — 모든 내부 및 외부 트래픽을 암호화
+- **시크릿 관리(Secrets Management)** — 민감한 자격 증명을 AWS Secrets Manager로 관리
+
+
+ ### 액세스 제어
+
+
+- **RBAC** — 모든 작업에 대한 Kubernetes 역할 기반 액세스 제어
+- **SSO 통합** — 엔터프라이즈 ID 공급자(Identity Provider) 연동
+- **감사 로깅** — 규정 준수를 위해 보존되는 전체 액세스 로그
+
+---
+
+
+ ## 재해 복구
+
+
+
+ ### 복구 목표
+
+
+| 지표 | 목표 | 현재 |
+|--------|--------|---------|
+| **RTO** (Recovery Time Objective) | < 15분 | 약 5분 |
+| **RPO** (Recovery Point Objective) | < 1분 | 실시간 복제 |
+
+
+ ### 탄력성 기능
+
+
+- **다중 AZ 복제** — 가용 영역 간 데이터 복제
+- **자동 장애 조치** — Route 53 상태 검사로 DNS 장애 조치 수행
+- **롤링 배포** — 자동 롤백을 지원하는 무중단 배포
+- **백업 및 복구** — 지정 시점 복구(Point-in-Time Recovery)가 가능한 일일 자동 백업
+
+---
+
+
+ ## 프로덕션 환경급 신뢰성 보장
+
+
+
+ ### 우리의 인프라가 견고한 이유
+
+
+Benzinga의 인프라는 **대규모 프로덕션 환경에서 검증**되었으며, 입증된 안정성으로 하루 수백만 건의 요청을 처리합니다:
+
+
+ ### 모니터링 및 옵저버빌리티
+
+
+당사의 **종합적인 모니터링**은 문제가 귀사의 비즈니스에 영향을 미치기 전에 탐지되고 해결되도록 합니다:
+
+
+ ### 고객 신뢰: 이것이 여러분에게 의미하는 바
+
+
+Benzinga의 API를 통합하면, 다음과 같은 요소로 뒷받침되는 **프로덕션급 인프라**에 연결하게 됩니다:
+
+| Feature | Client Benefit |
+|---------|----------------|
+| **Multi-AZ Redundancy** | AWS 가용 영역(Availability Zone) 장애가 발생해도 애플리케이션이 온라인 상태를 유지합니다 |
+| **Automated Scaling** | 트래픽 급증 시에도 요청 제한 없이 요청이 원활하게 처리됩니다 |
+| **24/7 Monitoring** | 성능 저하를 인지하기 전에 엔지니어가 문제를 감지하고 해결합니다 |
+| **Zero-Downtime Deployments** | 업데이트로 인해 서비스 가용성이 중단되지 않습니다 |
+| **Complete Audit Trail** | 모든 배포가 추적·검토되며, 즉시 롤백이 가능합니다 |
+| **Proactive Alerting** | 고객에게 영향이 가기 전에 잠재적인 문제의 95%가 해결됩니다 |
+
+
+ ## 요약
+
+
+Benzinga의 인프라는 다음과 같은 요소를 통해 **엔터프라이즈급 신뢰성**을 제공합니다:
+
+