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Microservice (Observability (Application metrics (examples…

- - - - digram
      - examples
        
        AWS Elastic Load Balancer (ELB)
        
        Kubernetes
    - - Compared to client-side discovery, the client code is simpler since it does not have to deal with discovery. Instead, a client simply makes a request to the router
      - Some cloud environments provide this functionality, e.g. AWS Elastic Load Balancer
    - - Unless it’s part of the cloud environment, the router must is another system component that must be installed and configured. It will also need to be replicated for availability and capacity.
      - The router must support the necessary communication protocols (e.g HTTP, gRPC, Thrift, etc) unless it is TCP-based router
      - More network hops are required than when using Client Side Discovery
  - - - Netflix OSS
        
        Eureka
        
        Ribbon
    - - Fewer moving parts and network hops compared to Server-side Discovery
    - - This pattern couples the client to the Service Registry
      - Need to implement client-side service discovery logic for each programming language/framework used by your application, e.g Java/Scala
  - - - Netflix Eureka
    - - A service instance knows its own state so can implement a state model that’s more complex than UP/DOWN, e.g. STARTING, AVAILABLE, …
    - - Couples the service to the Service Registry
      - must implement service registration logic in each programming language/framework that you use to write your services, e.g. NodeJS
      - A service instance that is running yet unable to handle requests will often lack the self-awareness to unregister itself from the service registry
- - - - Netflix Hystrix
- - - - AWS Cloud Watch
    - - handling a large volume of logs requires substantial infrastructure
  - - - Spring Cloud Sleuth
      - Zipkin
      - Open Tracing
  - - - It is easier to view exceptions and track their resolution
    - - The exception tracking service is additional infrastructure
    - - sentry
  - - - Spring Boot Actuator
    - - The health check endpoint enables the health of a service instance to be periodically tested
    - - The health check might not sufficiently comprehensive or the service instance might fail between health checks and so requests might still be routed to a failed service instance
  - - - AWS CloudTrail
      - Graphite
    - - Tracking Every Release by Mike Brittain
    - - Enables deployments and changes to be easily correlated with issues leading to faster resolution.
  - - - Instrumentation libraries
        
        Java Metrics Library
        
        Prometheus client libraries
      - Metrics aggregation services
        
        Prometheus
        
        AWS Cloud Watch
    - - It provides deep insight into application behavior
    - - Metrics code is intertwined with business logic making it more complicated
    - - Aggregating metrics can require significant infrastructure
  - - - This pattern is widely used.
    - - Provides a record of user actions
    - - The auditing code is intertwined with the business logic, which makes the business logic more complicated
    - - Event Sourcing is a reliable way to implement auditing
- - - - keep each microservice's persistent data private to the service
        
        different ways
        
        Private-tables-per-service – each service owns a set of tables that must only be accessed by that service
        
        Schema-per-service – each service has a database schema that’s private to that service
    - - Helps ensure that the services are loosely coupled. Changes to one service’s database does not impact any other services.
      - Each service can use the type of database that is best suited to its needs.
        
        a service that does text searches could use ElasticSearch
        
        a service that manipulates a social graph could use Neo4j.
    - - Implementing business transactions that span multiple services is not straightforward
        
        solution
        
        Saga pattern
        
        https://microservices.io/patterns/data/saga.html
      - Implementing queries that join data that is now in multiple databases is challenging.
        
        solution
        
        API Composition
        
        Command Query Responsibility Segregation (CQRS)
      - Complexity of managing multiple SQL and NoSQL databases
- - - - JSON Web Token
    - - The identity of the requestor is securely passed around the system
      - Services can verify that the requestor is authorized to perform an operation
    - - The API Gateway uses this pattern.