Best Practices for Implementing Microservices Architecture in DevOps Environments
Tags: cloudnative, microservices, devops, vscode
Published: 2024-02-18 16:19:04



Introduction


Microservices architecture has become an increasingly popular approach for building complex applications in recent years. The microservices approach structures an application as a collection of loosely coupled services that communicate over well-defined APIs. This enables teams to develop, deploy, and scale different services independently, making it well-suited for continuous delivery and DevOps practices. 

However, implementing microservices successfully requires careful planning and following best practices around organization, automation, monitoring, and other areas. Failing to do so can lead to issues with complexity, reliability, aligning with business goals, and more. This article outlines key best practices technology leaders should consider when implementing microservices in DevOps environments.

Define Service Boundaries Around Business Capabilities

One of the most important early decisions is how to divide the overall application into individual microservices. Rather than focusing on technical layers or components, it works best to define service boundaries based on business capabilities. This enables each microservice to represent a specific business functionality that can evolve independently. For example, an e-commerce application might have separate microservices for the product catalog, shopping cart, order management, customer management, etc.

When aligned to business domains, microservice teams can more effectively focus their efforts on solving specific business problems and delivering user value. This domain-driven design approach also improves organizational alignment.

Automate Provisioning and Infrastructure Management 

Automating provisioning, configuration management, and infrastructure management is critical for achieving some of the main benefits of microservices. Relying on manual processes fails to deliver on the promise of increased developer productivity and velocity. It also risks reliability by making it easier for configuration drift and other issues to occur over time.

Utilize Infrastructure-as-Code solutions such as Terraform to fully script and automate the provisioning of resources like virtual machines, databases, storage, and networking. Manage configuration with tools like Ansible, Chef, or Puppet. Leverage container orchestrators like Kubernetes for deploying and managing containers. And build continuous delivery pipelines to promote services from dev to prod. Automating the infrastructure layer enables easier scaling, preventing configuration drift, and much faster recovery from failures.

Design Loosely Coupled Services

While microservices enable independent lifecycles per service, they still need to connect and communicate with each other somehow. Teams should follow best practices around loose coupling and developing well-defined service contracts early on.

Services should expose simple, minimal APIs that provide autonomous functionality without large payloads of data or chatty protocols with multiple back-and-forth requests. Prefer asynchronous and event-driven communication over synchronous request-reply. Leverage messages queues or event buses to prevent tight temporal couplings between services. These best practices help isolate and prevent changes from rippling across services.

Set up API Gateways and Reverse Proxies 

Even when loosely coupled, services still need to connect to call each other’s APIs. However, directly exposing all microservices risks overwhelming consumers with too many endpoints to manage. It also presents security and governance challenges around who can access what. 

API gateways provide a single entry point or routing layer to handle inbound requests and route them intelligently to the appropriate backend services. Gateways enable things like authentication, TLS termination, rate limiting, caching, and observability in a central spot. They simplify the overall architecture for consumers.

Similarly, internal reverse proxy services like Envoy Proxy help handle cross-cutting concerns like service discovery, retries, timeouts, rate limiting, routing rules between services, and breaking direct couplings. These proxies enable cleaner service implementations to focus on core business logic.

Embrace a Culture of Automation Testing

Given the number of independent services and deployment velocity goals with microservices, manual testing becomes impractical and bottlenecks releases. Organizations implementing microservices need to embrace comprehensive test automation across unit, integration, API, performance, security, and other types of testing. 

Make testing the shared responsibility of developers, QA, and DevOps. Provide test environments and self-service tooling to make it easy to build automation into pipelines. Leverage practices like shift-left testing, test-driven development (TDD), and test automation pyramid models. Getting testing automated and running frequently prevents drift, catches regressions faster, and provides safety nets for rapid iterations.

Monitor and Visualize Everything 

The distributed nature of microservices and their infrastructure means there are many moving parts to keep an eye on. Make sure to monitor metrics across services, containers, hosts, databases, queues, proxies, etc. Log everything and aggregate logs in a central location with correlation IDs for tracing a request end-to-end transaction through the system. 

Provide dashboards for application health, performance visbility, feature usage, service dependencies, logs, alerts, and more. This level of monitoring, logging, and visualization is necessary for the teams to effectively build, operate, debug, evolve and scale their services over time – especially when issues arise. No one wants to be flying blind.

Align Teams to Service Boundaries

To enable highly focused teams and increase velocity, development teams should align directly to the services they build and operate. Keep teams small with 2-pizza team sizes of 5-7 engineers covering a single service or small group of highly related services. This focuses their responsibilities and agility for inventing within those boundaries and domains. 

Provide teams autonomy over roadmaps, backlogs, architectures, languages, etc but also facilitate coordination across teams when broader changes cross boundaries via techniques like service contracts. Make product managers owners of particular microservices versus generalists across everything. Results should be faster iteration and innovation aligned to solving specific business problems.  

Standardize Common Patterns and Technologies

While microservices promise independence across team decisions, in practice some level of standards around common patterns, technologies, and platforms prevents wheel reinvention and wasted effort. For example, provide centralized platforms and tools for container deployment, logging, monitoring, CI/CD, testing, security, networking. Establish common patterns around APIs, messaging, data, security, and more. 
 
Documentation and shared learnings for approved patterns, problems solved, and lessons learned also help raise everyone’s game vs learning previous lessons repeatedly. However, be careful not to over standardize and leave room for innovation as well.

Security as Code and Everywhere 
 
 The increased attack surface of microservices and their APIs warrants security practices to be embedded everywhere including the culture. Make security scans, penetration testing, abuse case modeling, and enabling security headers, TLS, RBAC mandatory parts of pipelines and environments. Provide security guides, libraries, and policy-as-code templates for the teams leverage. Embed security experts within teams instead as separate last milegates to encourage shared ownership. Make security dashboards and monitoring part of standard observability practices. Promote chaos engineering techniques that purposefully inject failures regularly including security threats to ensure recovery procedures and safety nets work. Make security a key pillar of the approach versus an afterthought to avoid breaches.
  
Right Size Infrastructure and Leverage Auto-Scaling

A best practice with cloud infrastructure is rightsizing along the way rather than massively overprovisioning everything initially. Monitor usage across CPU, memory, IO for services and scale up or down accordingly based on load. Set auto-scaling policies based on metrics as well to automate adding or removing capacity to maintain performance targets automatically even when demand spikes. Plan capacity strategically around new feature launches or marketing campaigns versus static sizing. Optimizing infrastructure utilization this way controls costs while still providing necessary performance.

Plan for Refactoring and Rewriting Services 

The microservices approach enables starting off quickly by perhaps skipping certain foundational elements or taking shortcuts in early prototyping phases. However, as services age and reach scale thresholds the gaps begin to show in terms of technical debt, complexity debt, security issues, performance bottlenecks and more. Make sure teams understand services can form the legacy apps of tomorrow and will need rewrites, refactoring, and cleaning up down the road. Plan sprints and roadmap cycles explicitly targeting these rewriting initiatives over time versus only greenfield efforts. Also design new services learning from past services to prevent known issues from repeating downstream as well. 

Conclusion

Implementing microservices architecture brings immense strategic benefits but also numerous operational complexities if not done thoughtfully. Follow the key best practices around domain modeling, automation, testing, monitoring, organizational alignment, and more outlined in this article. Treat microservices adoption as an evolving journey versus a one time project. Continually optimize the approach over time as capabilities advance across development teams, platform tooling, and cloud infrastructure. The end goal is unlocking business velocity through streamlined software delivery aligned directly to innovation on critical user experiences.