The user makes a single call to the aggregator service, and the aggregator then calls each relevant microservice.
Real world example
Our web marketplace needs information about products and their current inventory. It makes a call to an aggregator service which in turn calls the product information microservice and product inventory microservice returning the combined information.
Provide a helper service instance on a client and offload common functionality away from a shared resource.
Real world example
A remote service has many clients accessing a function it provides. The service is a legacy application and is impossible to update. Large numbers of requests from users are causing connectivity issues. New rules for request frequency should be implemented along with latency checks and client-side logging.
Aggregate calls to microservices in a single location, the API Gateway. The user makes a single call to the API Gateway, and the API Gateway then calls each relevant microservice.
With the Microservices pattern, a client may need data from multiple different microservices. If the client called each microservice directly, that could contribute to longer load times, since the client would have to make a network request for each microservice called. Moreover, having the client call each microservice directly ties the client to that microservice - if the internal implementations of the microservices change (for example, if two microservices are combined sometime in the future) or if the location (host and port) of a microservice changes, then every client that makes use of those microservices must be updated.
The caching pattern avoids expensive re-acquisition of resources by not releasing them immediately after use. The resources retain their identity, are kept in some fast-access storage, and are re-used to avoid having to acquire them again.
Real world example
Handle costly remote service calls in such a way that the failure of a single service/component cannot bring the whole application down, and we can reconnect to the service as soon as possible.
Real world example
Imagine a web application that has both local files/images and remote services that are used for fetching data. These remote services may be either healthy and responsive at times, or may become slow and unresponsive at some point of time due to variety of reasons. So if one of the remote services is slow or not responding successfully, our application will try to fetch response from the remote service using multiple threads/processes, soon all of them will hang (also called thread starvation) causing our entire web application to crash. We should be able to detect this situation and show the user an appropriate message so that he/she can explore other parts of the app unaffected by the remote service failure. Meanwhile, the other services that are working normally, should keep functioning unaffected by this failure.
Used to handle all problems that can be encountered when doing distributed transactions.
This pattern can be used when we need to make commits into 2 (or more) databases to complete transaction, which cannot be done atomically and can thereby create problems.
CQRS Command Query Responsibility Segregation - Separate the query side from the command side.
Use the CQRS pattern when
Instead of storing just the current state of the data in a domain, use an append-only store to record the full series of actions taken on that data. The store acts as the system of record and can be used to materialize the domain objects. This can simplify tasks in complex domains, by avoiding the need to synchronize the data model and the business domain, while improving performance, scalability, and responsiveness. It can also provide consistency for transactional data, and maintain full audit trails and history that can enable compensating actions.
Leader Election pattern is commonly used in cloud system design. It can help to ensure that task instances select the leader instance correctly and do not conflict with each other, cause contention for shared resources, or inadvertently interfere with the work that other task instances are performing.
Poison Pill is known predefined data item that allows to provide graceful shutdown for separate distributed consumption process.
Real world example
Let's think about a message queue with one producer and one consumer. The producer keeps pushing new messages in the queue and the consumer keeps reading them. Finally when it's time to gracefully shut down the producer sends the poison pill message.
