Microservices are small, independent, and loosely coupled software components that can be deployed and updated independently. They offer many benefits, such as scalability, resilience, and faster delivery. But how do you continuously deliver microservices without compromising quality, security, and performance? Here are some best practices to follow.
To support the entire lifecycle of your microservices, from development to deployment, you need a set of tools. These include a version control system such as Git to manage your code and configuration files, a build tool such as Maven or Gradle to compile, test, and package your microservices, a container platform such as Docker or Kubernetes to run your microservices in isolated and portable environments, a continuous integration (CI) tool such as Jenkins or Travis CI to automate the building, testing, and scanning of your microservices, and a continuous delivery (CD) tool such as Spinnaker or Argo CD for the automated deployment and rollback of your microservices across different environments.
I have recently worked on a different system architecture environments including: single monolith, distributed monolith, and true microservices. While there are benefits to building a distributed monolith there are significant costs also. The benefits are in granularity of the build and unit testing. The costs are in the extra coordination. The main CD problem with monolith and distributed monolith architectures is with integration testing. How to get enough confidence that a release is good enough? 1) put features behind feature flags (unit test both settings and combo settings), 2) test every release, 3) be prepared to recover the service, with small frequent releases that is easier even on a monolith.
The rise of DevOps culture combined with the advent of the tools to support it have truly unlocked the potential of the microservice architecture pattern. The choice of tooling is largely dependent on the situation, but the Continuous practice of Integration to address quality and security; Deployment to enable faster more sophisticated delivery strategies; and Monitoring to provide real time feedback; have provided faster feedback loops and empowered engineers to truly operate their code in a Production environment. All of these practices have been made easier and more attainable in recent years through the use of Docker and the Kubernetes orchestration framework, which have become the standard for microservice hosting.
To ensure that your microservices are testable, you should employ various strategies, such as mocking and stubbing to isolate them from external dependencies, contract testing to verify their API inputs and outputs, integration testing to check their communication with each other, performance testing to measure their throughput, latency, and resource consumption, and chaos testing to observe their resilience and recovery when failures or disruptions are injected.
Designing for testability is very important. One thing I want to add is the need to perform a load testing where applicable as this can help simulate how the service(s) will behave when it/they gain traction.
Let your tests drive your design. Using TDD will reveal problems in your design models. This is true for unit and integration tests. If you find it difficult to test a design there is probably a simpler solution.
Collecting and analyzing feedback from various sources, such as logs, metrics, traces, and user feedback, is essential for monitoring and improving your microservices. Logging frameworks like Logback or Log4j can capture and format events and errors. Metrics frameworks like Micrometer or Prometheus can measure key performance indicators like response time, error rate, and availability. Tracing frameworks like Zipkin or Jaeger can track and visualize the flow of requests across microservices. Observability platforms such as Grafana or New Relic can aggregate and visualize logs, metrics, and traces while providing alerts and dashboards. Finally, feedback loops like surveys or reviews should be used to gather user needs and preferences.
Microservice must be considered from a strategic support and delivery perspective. One of the most important aspects of delivering microservices at scale is ensuring strong processes are in place. Look at four key areas: lifecycle management, inventory management, secrets management, and least privilege. Lifecycle management involves deploying, monitoring, maintaining, and retiring microservices. Inventory management involves tracking the status of all microservices, including their status and sponsor. Secrets management involves managing database and system keys and passwords in a secure location. Least privilege, means systems have the minimum necessary access to systems and data necessary to do their intended task.
Amplifying feedback loops is perhaps the most important element of the DevOps ethos and continuous feedback is the primary goal. When this concept is applied to logging and telemetry, the potential to quickly and accurately assess system issues is greatly enhanced. This continuous monitoring feedback loop can be leveraged to create self-healing systems and greatly reduce the mean time to resolution. When extended to user analytics engineers are able to assess feature utilization in real time and make better more informed decisions about future enhancements.
To foster a culture of collaboration and ownership among your teams, responsible for designing, developing, testing, deploying, and operating their own microservices, use agile methodologies such as Scrum or Kanban. Cross-functional teams composed of developers, testers, operators, and product owners should be used to share the skills, knowledge, and responsibilities. Code reviews, pair programming, and code standards should be employed to ensure the quality and consistency of your code and configuration files. Feature flags, canary releases, and blue-green deployments should be used to enable gradual and safe rollouts of your microservices while minimizing the impact of errors and bugs. Finally, blameless postmortems, retrospectives, and learning sessions should be used to identify and address the root causes of failures and issues. By following these best practices you can continuously deliver microservices that meet the expectations and needs of your users and stakeholders while maintaining high standards of quality, security, and performance.
DevOps culture and its related practices are the engine that power Agile methodology. Many of the techniques and capabilities described here can be empowered by DevOps, but are present in Agile. What's unique about a DevOps culture is the shift left mentality and delivery of Operational capabilities to Development teams primarily through CICD pipelines that can be enhanced and refined to support the goals of Agle development teams.