I start both product-service and rating-service. I have created a simple JMeter test script with 20 concurrent users which will be continuously accessing these endpoints for 30 seconds. We were able to successfully demonstrate the Bulkhead Pattern which is one of the resilient Microservice Design Patterns for Microservices Architecture.
The source code is available here. Very Useful content. Thanks for sharing this. I would like to know how you ran performance test to measure this. The performance test script is part of the project which you could see in the github. You need JMeter.
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As requests to the service continue, those resources may be exhausted. For example, the client's connection pool may be exhausted. At that point, requests by the consumer to other services are affected. Eventually the consumer can no longer send requests to other services, not just the original unresponsive service.
The same issue of resource exhaustion affects services with multiple consumers. A large number of requests originating from one client may exhaust available resources in the service.
Other consumers are no longer able to consume the service, causing a cascading failure effect. Partition service instances into different groups, based on consumer load and availability requirements. This design helps to isolate failures, and allows you to sustain service functionality for some consumers, even during a failure. A consumer can also partition resources, to ensure that resources used to call one service don't affect the resources used to call another service.
The remaining request handling threads could have continued serving other requests. The idea behind bulkheads is to set a limit on the number of concurrent calls we make to a remote service. We treat calls to different remote services as different, isolated pools and set a limit on how many calls can be made concurrently. The term bulkhead itself comes from its usage in ships where the bottom portion of the ship is divided into sections separated from each other.
If there is a breach, and water starts flowing in, only that section gets filled with water. This prevents the entire ship from sinking.
We provide it the code we want to execute as a functional construct - a lambda expression that makes a remote call or a Supplier of some value which is retrieved from a remote service, etc. The SemaphoreBulkhead internally uses java. Semaphore to control the number of concurrent calls and executes our code on the current thread. The ThreadPoolBulkhead uses a thread from a thread pool to execute our code. It internally uses a java. ArrayBlockingQueue and a java.
ThreadPoolExecutor to control the number of concurrent calls. We can think of this value as the number of permits that the semaphore is initialized with. Any thread which attempts to call the remote service over this limit can either get a BulkheadFullException immediately or wait for some time for a permit to be released by another thread. This is determined by the maxWaitDuration value.
When there are multiple threads waiting for permits, the fairCallHandlingEnabled configuration determines if the waiting threads acquire permits in a first-in, first-out order.
Finally, the writableStackTraceEnabled configuration lets us reduce the amount of information in the stack trace when a BulkheadFullException occurs. This can be useful because without it, our logs could get filled with a lot of similar information when the exception occurs multiple times. Usually when reading logs, just knowing that a BulkheadFullException has occurred is enough.
The internal ThreadPoolExecutor executes incoming tasks using one of the available, free threads. If no thread is free to execute an incoming task, the task is enqueued for executing later when a thread becomes available. If the queueCapacity has been reached, then the remote call is rejected with a BulkheadFullException. ThreadPoolBulkhead also has a writableStackTraceEnabled configuration to control the amount of information in the stack trace of a BulkheadFullException.
We will use the same example as the previous articles in this series.
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