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47 changes: 47 additions & 0 deletions hash-based-routing.html.md.erb
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---
title: Hash-Based Routing
owner: CF for VMs Networking
---

## <a id="purpose"></a> Purpose

Hash-Based Routing is a load-balancing algorithm that distributes incoming requests to application instances based on a hash of a specific HTTP header value. This ensures consistent routing behavior where requests containing the same header value are always directed to the same instance.

## <a id="key-features"></a> Key Features

- **Configurable via Per-Route Options**: Easily set up Hash-Based Routing using application route options
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Maybe add a link to per-route-options documentation?

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@hoffmaen hoffmaen Nov 6, 2025

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Suggested change
- **Configurable via Per-Route Options**: Easily set up Hash-Based Routing using application route options
- **Configurable via Per-Route Options**: Easily configurable via per-route options

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It is the same words twice.
WDYT about
Configurable via Per-Route Options: Hash-Based load-balancing setup through application route options

- **Consistent Hashing**: Implements the Maglev consistent hashing algorithm as outlined in the paper "Maglev: A Fast and Reliable Software Network Load Balancer" (https://storage.googleapis.com/gweb-research2023-media/pubtools/2904.pdf)
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Suggested change
- **Consistent Hashing**: Implements the Maglev consistent hashing algorithm as outlined in the paper "Maglev: A Fast and Reliable Software Network Load Balancer" (https://storage.googleapis.com/gweb-research2023-media/pubtools/2904.pdf)
- **Consistent Hashing**: Consistent hashing via the Maglev Algorithm (see [Maglev: A Fast and Reliable Software Network Load Balancer](https://storage.googleapis.com/gweb-research2023-media/pubtools/2904.pdf) for details)

- **Minimal Rehashing**: Uses the Maglev lookup table to map application instances by hash, minimizing the need to recalculate the entire table when instances are added or removed
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the recalculation is not the expensive part. The really expensive part is the resulting shift of specific hashes to other instances. This rehashing minimization makes sure that happens as little as possible and keeps the "allocation" of hash values to their instances as stable as possible.

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Yes, you are right. I did not like the word recalculation either, I wanted to say the same what you mentioned.
Maybe:

**Minimal Rehashing**: Uses the Maglev lookup table to map application instances by hash, ensuring that hash positions are shifted to other instances as little as possible when application instances are added or removed."

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sounds great!

- **Configurable Hash Header**: Allows specifying which HTTP header to use for hashing via the `hash_header` property (e.g., `X-Resource-ID`)
- **Sticky Session Precedence**: Prioritizes sticky sessions over hash-based routing when available
- **Handling imbalanced loads**: Implements balance factor-based overload detection and mitigation
- **No availability zones preference**: The global properties `locallyOptimistic` and `localAvailabilityZone` will be ignored when using Hash-Based Routing

Hash-Based Routing implements a clear precedence hierarchy:

1. **Sticky Sessions**: First checks if a sticky session is used and the sticky session endpoint is available
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is the sticky session counted towards the balance / in-flight requests or not?

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@b1tamara b1tamara Nov 4, 2025

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All in-flight requests will be counted (incl. sticky session requests). It happens via {RoundRobin Iterater | HashBased Iterator | LeastConnection Iterator}.PreRequest logic

2. **Hash-Based Routing**: Calculates the hash of the specified HTTP header value and routes the requests to a pre-determined application instance
3. **Default Load Balancing**: Falls back to default load balancing (round-robin) if the header configured in the application route for hash-based routing is absent in the request


## <a id="hash-based-vs-session-affinity"></a> Hash-Based Routing vs. Session Affinity

Using Session Affinity, requests from a particular client are always routed to the same app instance. This allows apps to store session data specific to a user session (see more details in the [Session Affinity](https://docs.cloudfoundry.org/concepts/http-routing.html#-session-affinity) documentation).

While Session Affinity offers a solution for maintaining session consistency, it poses scalability challenges, as Session Affinity is confined to a single instance. It increases the risk that large customers could be routed to the same instance by chance. On the other hand, enabling Session Affinity requires additional implementation effort on the application side to return a sticky session cookie in responses.

In contrast, Hash-Based Routing provides a more scalable and balanced approach by consistently distributing requests based on a hash of a specific HTTP header value (e.g., `X-Resource-ID` or `Tenant-ID`). This hash value determines the appropriate application instance for each request, ensuring that requests with the same hash are consistently routed to the same instance, but might be routed to another predetermined instance when the current one is saturated (find more about Handling imbalanced loads below).

This makes it especially suitable for applications requiring high scalability and performance, such as microservices architectures or multi-tenant applications, when dealing with limited or memory-intensive resources in backend services.
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These paragraphs are very wordy and a bit meandering. LLM?

Either way, the main point is:
Session affinity works on session level. Heavy users may end up on the same instance and through session affinity pin to it, thus overloading it. Identifying sessions for web applications is usually done via session cookie and does not pose too much implementation burden. CF only supports a single cookie name however, defaulting to JSESSIONID.

With hash based routing, identifiers other than the session ID can be used, and spill-over to other instances is possible with the balance factor (see next section).



## <a id="handling-imbalance-loads"></a> Handling imbalanced loads

The implementation of the hash-based routing includes mechanisms to detect imbalanced loads across application instances. This is achieved through a balance factor that defines the acceptable threshold for load imbalance, which is configurable via the `hash_balance_factor` property.

When an application instance is being considered for selection, it will be checked whether it is handling more traffic than its fair share compared to the average load across all application instances. This load is measured by the number of in-flight requests. For example, with a balance factor of 1.25, no application instance should exceed 125% of the average number of in-flight requests across all application instances initiated by the current router. Consequently, requests must be distributed to different pre-determined application instance that is not overloaded.


## <a id="retries-in-hash-based"></a> Retries in Hash-Based Routing

For the idempotent requests, the retry mechanism is supported in Hash-Based Routing. When a request fails due to a network error or a 5xx response from the application instance, the router retries the request with a different predetermined application instance. The next entry in the predefined Maglev lookup table determines this instance. This is the same approach used in handling imbalanced loads. This ensures that the retry mechanism adheres to the principles of Hash-Based Routing while providing resilience against transient failures.