--- layout: pattern title: Retry folder: retry permalink: /patterns/retry/ categories: Other tags: - Java - Difficulty-Expert - Performance --- ## Retry / resiliency Enables an application to handle transient failures from external resources. ## Intent Transparently retry certain operations that involve communication with external resources, particularly over the network, isolating calling code from the retry implementation details. ![alt text](./etc/retry.png "Retry") ## Explanation The `Retry` pattern consists retrying operations on remote resources over the network a set number of times. It closely depends on both business and technical requirements: how much time will the business allow the end user to wait while the operation finishes? What are the performance characteristics of the remote resource during peak loads as well as our application as more threads are waiting for the remote resource's availability? Among the errors returned by the remote service, which can be safely ignored in order to retry? Is the operation [idempotent](https://en.wikipedia.org/wiki/Idempotence)? Another concern is the impact on the calling code by implementing the retry mechanism. The retry mechanics should ideally be completely transparent to the calling code (service interface remains unaltered). There are two general approaches to this problem: from an enterprise architecture standpoint (**strategic**), and a shared library standpoint (**tactical**). *(As an aside, one interesting property is that, since implementations tend to be configurable at runtime, daily monitoring and operation of this capability is shifted over to operations support instead of the developers themselves.)* From a strategic point of view, this would be solved by having requests be redirected to a separate intermediary system, traditionally an [ESB](https://en.wikipedia.org/wiki/Enterprise_service_bus), but more recently a [Service Mesh](https://medium.com/microservices-in-practice/service-mesh-for-microservices-2953109a3c9a). From a tactical point of view, this would be solved by reusing shared libraries like [Hystrix](https://github.com/Netflix/Hystrix)[1]. This is the type of solution showcased in the simple example that accompanies this *README*. In our hypothetical application, we have a generic interface for all operations on remote interfaces: ```java public interface BusinessOperation { T perform() throws BusinessException; } ``` And we have an implementation of this interface that finds our customers by looking up a database: ```java public final class FindCustomer implements BusinessOperation { @Override public String perform() throws BusinessException { ... } } ``` Our `FindCustomer` implementation can be configured to throw `BusinessException`s before returning the customer's ID, thereby simulating a 'flaky' service that intermittently fails. Some exceptions, like the `CustomerNotFoundException`, are deemed to be recoverable after some hypothetical analysis because the root cause of the error stems from "some database locking issue". However, the `DatabaseNotAvailableException` is considered to be a definite showstopper - the application should not attempt to recover from this error. We can model a 'recoverable' scenario by instantiating `FindCustomer` like this: ```java final BusinessOperation op = new FindCustomer( "12345", new CustomerNotFoundException("not found"), new CustomerNotFoundException("still not found"), new CustomerNotFoundException("don't give up yet!") ); ``` In this configuration, `FindCustomer` will throw `CustomerNotFoundException` three times, after which it will consistently return the customer's ID (`12345`). In our hypothetical scenario, our analysts indicate that this operation typically fails 2-4 times for a given input during peak hours, and that each worker thread in the database subsystem typically needs 50ms to "recover from an error". Applying these policies would yield something like this: ```java final BusinessOperation op = new Retry<>( new FindCustomer( "1235", new CustomerNotFoundException("not found"), new CustomerNotFoundException("still not found"), new CustomerNotFoundException("don't give up yet!") ), 5, 100, e -> CustomerNotFoundException.class.isAssignableFrom(e.getClass()) ); ``` Executing `op` *once* would automatically trigger at most 5 retry attempts, with a 100 millisecond delay between attempts, ignoring any `CustomerNotFoundException` thrown while trying. In this particular scenario, due to the configuration for `FindCustomer`, there will be 1 initial attempt and 3 additional retries before finally returning the desired result `12345`. If our `FindCustomer` operation were instead to throw a fatal `DatabaseNotFoundException`, which we were instructed not to ignore, but more importantly we did *not* instruct our `Retry` to ignore, then the operation would have failed immediately upon receiving the error, not matter how many attempts were left.

[1] Please note that *Hystrix* is a complete implementation of the *Circuit Breaker* pattern, of which the *Retry* pattern can be considered a subset of. ## Applicability Whenever an application needs to communicate with an external resource, particularly in a cloud environment, and if the business requirements allow it. ## Presentations You can view Microsoft's article [here](https://docs.microsoft.com/en-us/azure/architecture/patterns/retry). ## Consequences **Pros:** * Resiliency * Provides hard data on external failures **Cons:** * Complexity * Operations maintenance ## Related Patterns * [Circuit Breaker](https://martinfowler.com/bliki/CircuitBreaker.html)