distributed systems - Back Pressure Pattern

5. Back Pressure Pattern

Back Pressure is a design pattern used to handle situations where a system component is overloaded with too many requests or data. This pattern is particularly useful in event-driven architectures where a service, or a component, may receive events at a rate faster than it can process them.

The basic idea of the Back Pressure pattern is to provide a feedback mechanism that allows a service to signal upstream that it’s overwhelmed with the current load and cannot accept any more requests or data at the moment. This can be done in several ways, such as:

1. Buffering: The overwhelmed component can buffer incoming requests until it has the capacity to handle them. However, this is effective only up to a certain point. If the rate of incoming requests continuously exceeds the processing rate, the buffer will eventually fill up and can cause the system to crash.
2. Load Shedding: The component can start dropping incoming requests when it’s overwhelmed. While this approach may result in lost data or unserved requests, it can prevent system failure in high-load situations.
3. Throttling: The component can slow down the rate at which it accepts new requests. This can be done by delaying the acceptance of new requests or by accepting only a certain number of requests per unit of time.
4. Resizing: If the system is designed to be elastic, it can respond to high load by automatically adding more resources or instances of the overwhelmed component.

The benefits of the Back Pressure pattern include:

1. Resilience: By actively managing overload situations, the Back Pressure pattern can prevent system failure and improve overall resilience.
2. Flow Control: Back Pressure can help manage the flow of data or requests through the system, helping to ensure that all components operate within their capacity.

However, there are also some challenges and considerations:

1. Lost Data or Requests: Depending on how Back Pressure is implemented, it might result in lost data or unserved requests.
2. Complexity: Implementing Back Pressure can add complexity to the system. It requires careful design to ensure that signals are properly propagated and handled.
3. User Experience: Back Pressure can impact the user experience, as it can result in slower response times or dropped requests. It’s important to handle these situations in a way that minimizes the impact on users.

In summary, the Back Pressure pattern is an important strategy for managing overload situations in event-driven systems. While it can add complexity and potentially impact the user experience, it’s crucial for maintaining the resilience and stability of the system.