Observability for Microservice and Service Mesh Architectures
The Move to Microservices
A microservice architecture is a service-based approach that breaks down applications into multiple discrete processes or services. A microservice development architecture offers significant advantages, such as better fault isolation, the ability to mix and match multiple technology frameworks and libraries, and support for multiple parallel development teams. With a microservice architecture, DevOps teams can iterate more efficiently, respond more quickly to market changes and user needs, and innovate faster.
Microservices prioritize each individual service rather than many services simultaneously, enabling agility and supporting the continuous integration and continuous delivery (CI/CD) cycle. However, with these opportunities come challenges.
The full benefit of microservices can only be achieved when DevOps teams have access to the data they need to monitor activity, identify problems, and detect failures. The high number of moving pieces and additional services introduced by a microservice architecture add a great deal of complexity to both performance monitoring and troubleshooting.
Consider this scenario: 10 containers run one service. An application is comprised of five different services made up of different containers. Tracking them all can be mind-boggling, especially because these moving pieces literally move around.
Microservices and Observability
Unlike static, consistent VMs—which traditional monitoring tools support—microservices require tools providing a higher degree of observability. For example, a DevOps team can’t know how an app is performing without visibility into when internal events don’t occur as expected or when events occur when they shouldn’t. The application might be spun up and down in another location, and with conventional tooling, this might not be visible.
A microservice architecture along with continuous deployment creates a need for new team dynamics. With individual teams able to perform updates independently, inter-team communication and collaboration are critical to ensuring continuous delivery and agility.
Fewer than 10 microservices could likely be managed with existing tools and security, but once a team starts running more than 10, a service mesh architecture becomes necessary.
A service mesh is an additional platform layer on top of the infrastructure designed to enable secure communication between services. A service mesh manages all service-to-service communication within a microservice-based application. It provides policy-based networking for microservices, describing the desired behavior of the network in the face of constantly changing conditions and network topology.
Service Mesh and Observability
The additional layer of tooling offered by service meshes provides independent control over microservices and enhances security. It also provides detailed telemetry data for all service communication. This telemetry data provides observability into service behavior, which is essential for effective troubleshooting. Since this data is generated by the service mesh itself, there’s no additional development impact.
Ultimately, service meshes result in a developer-driven, services-first network—a network primarily focused on alleviating application developers from building network concerns into their applications’ code.
Service meshes create a network that empowers operators to define network behavior, node identity, and traffic flow through policy. They deliver visibility, resiliency, traffic, and control of distributed application services and offer immediate observability into the number of requests, distributed tracing, and latency based on response time.
What do you think? Have you had a chance to work with service meshes and did provide you with better observability or manageability? We love to hear your thoughts below.