The 5 stages of the microservice life cycle and the best tools to optimize them

Whether you’re transitioning from a monolithic to microservices architecture or building microservices from scratch, here are 13 tools to consider, for whichever stage of software development you’re at.

December 15, 2021

As microservice architectures grow in popularity, it’s crucial to understand how to undertake it in the right way to reap its benefits.

Just like the famous Software Development Life Cycle (SDLC), microservice development also has a life cycle process: first, design; second, build; next, deploy; then, maintain; and finally, manage. To set yourself up for success (and scalability) when building a  microservice architecture, you must approach each stage with care.

New tools and services can help DevOps engineers and teams with each stage of the microservice life cycle to achieve the highest real-time performance for your product, an optimized workflow for your company, and the best results for your customers.

Choosing the best tool at each step across this lifecycle — from designing to building to deploying to maintaining to managing — is key to developing the best overall microservice architecture. These decisions directly impact the quality, continuous delivery, maintainability, scalability, and future features of your microservices, as well as the productivity of your team that is working on it.

It might seem overwhelming to switch from a legacy monolithic application to a microservices architecture, or to build one wholly from the ground up. But these 13 tools to help you develop the most agile and responsive microservice architecture, from the experts at Cortex.

Stage 1: Design

How do you kick off building microservices? Like any new project, you’ll start by thinking through the larger distributed system. By “design,” we mean the pipeline to come up with plans or specifications to construct this system.

Consider: What do you want the individual service to do? What is the business case? Who is the user (alternatively, what are the different user personas)? How does the node fit within the broader ecosystem? What data do you have, and what do you need? These design choices will set up long-term success for the microservice.

You will want to come up with a list of capabilities that this system will have. Then you can break down these capabilities into the roles of the different modular services, as required by your system.

If you begin to build without the appropriate design, it becomes difficult and costly to go back and redefine service interactions and data structures.

When you’re writing out specs, as well, you ought to think about application programming interfaces (APIs). The microservice will be delivered through API calls, so your service and API must work well together.

Some potential microservice architecture design tools and services include:

This free diagram-making software can help you visualize your architecture, network diagram software, and create UML online. The useful program is easy to customize and easy to collaborate on. Plus, you can save the visualization right on GitHub or GitLab.

GraphQL is an open-source query language that’s particularly helpful for APIs. It is a strong-typed system that defines the capabilities of an API. The defined structure loads data from a server to a client — it's a way to get data into your application quickly, without over-fetching or under-fetching.

In application development, this structure allows frontend and backend teams to work asynchronously: Frontend teams can test their applications by mocking the required data structures, and once the server is set up, flip the switch to let the client apps load data from the actual API. There are a few GraphQL client libraries available for developer use.

The OpenAPI Specification, previously known as the Swagger Specification, is a format to describe, develop, test, and document REST-compliant APIs. (REST APIs are APIs that conform to the design principles of the REST, or representational state transfer architectural style. They’ve become a standard for designing web APIs in the past few years because they provide a set of rules that can deliver fully functioning web services.) It's operated by the OpenAPI Initiative (OAI), under the umbrella Linux Foundation.

OpenAPI documents are human-readable, which enables anyone working on the project to easily determine how each API works. They’re also machine-readable, and can be used by: 1) documentation generation tools to display the API; 2) code generation tools to generate servers and clients in various programming languages, and 3) testing tools, plus many other use cases.

gRPC is a universal open source high-performance Remote Procedure Call (RPC) framework that can run in any environment. This communication protocol is an alternative to REST APIs. It’s a lean platform using a lean transport system to deliver lean bits of code: in particular, the communication between microservices happen through stubs that gRPC handles.

gRPC can efficiently connect services in and across data centers with support for load balancing, tracing, health checking and authentication. It also has multilingual support (Java, Python, Go, C++, and more). Major companies such as Square, Lyft and Netflix have adopted gRPC for microservices communication.

Stage 2: Building

Once you have designed your microservice architecture, it’s time to build. Setting up microservice architecture is no easy task, but these tools help save time (and money). Different teams might choose to build each microservice differently, but the beauty of microservices is that they can be connected with the right components and APIs. Once you set up libraries and tools, as well, teams bootstrapping new projects will have more choices. Some options are below.

Cookiecutter is an open source library for building coding project templates, including for microservice projects. The tool is built with Python and utilizes Jinja to power its templating engine. Once Cookiecutter is installed and a template selected, developers can use their command-line interface (CLI) to start a new project. Cookiecutter can be used either with a Git repository, with a folder or even a Zip file.

Developers can also create their own project templates — a.k.a. scaffolding, bootstrap, boilerplate or skeleton — on the app. We use Cookiecutter at Cortex to build our software and maintain consistency and flexibility across teams.

For API management, you’ll need a flexible and collaborative API-building tool. Postman is a platform that allows developers to create, share, test, and document APIs. The streamlined platform has tools that enable steps of the API life cycle, from design to testing to documentation to mocking to sharing your APIs. Essentially, it will help validate APIs as you're building. It's available for many operating systems.

This AWS service, Amazon API Gateway, helps development teams to create, publish, and secure REST, HTTP, and WebSocket APIs at varying scales. API developers can create APIs that access AWS or other web services, as well as data stored in the AWS Cloud.

Stage 3: Deploying

The third microservice life cycle stage is deployment, or production. Here’s where it gets tricky. You’ll want to think strategically about your moves at this stage. Compared to the process of deploying monolithic architecture — running multiple, identical copies of a single, usually large application — it’s far more complex.

A microservices application can consist of tens or even hundreds of services, written in a variety of languages and frameworks. Each one is a mini‑application with specific deployment, resource, scaling, and monitoring requirements. Service boundaries abound. Plus, often, separate teams have worked on different microservices, possibly in different programming languages.

Microservices can be deployed in several ways: they can be part of a serverless architecture, hosted in containers, developed using PaaS, or, theoretically, used to build a locally hosted application. Most often, though, they're cloud native, and ether in a serverless architecture (application designs that incorporate third-party “Backend as a Service” (BaaS) services) or and used with container orchestration (with many nodes, containers also offer platform-independence and interoperability, and can be created with Docker).

Still, once the infrastructure is set up, such independent releases offer the promise of shorter release cycles and increased deployment cadence because of the ability for developer teams to use continuous delivery pipelines for code changes and bug fixes. This saves time down the line while coordinating with multiple teams during regular maintenance or upgrade efforts.

Luckily, adaptable tools like the ones below can help developers to optimize their workflows and automate many of the tedious steps.

Also known as K8s, Kubernetes is open-source software designed specifically to automate the deployment, scaling, and management of containerized applications with multiple hosts. (Google originally designed the Kubernetes project, but the Cloud Native Computing Foundation now maintains it.)

The Kubernetes software groups the different containers that make up an application into logical units while load-balancing across them. It allows for cluster management, scheduling, service discovery, monitoring, secrets management, and more.

Nomad supports similar core use cases as Kubernetes for application deployment and management. Nomad is a simple and flexible scheduler and workload orchestrator that deploys and manages containers and non-containerized applications at scale. It focuses on cluster management and scheduling, but comes with tools such as Consul for service discovery/service mesh and Vault for secret management.

Nomad supports virtualized, containerized and standalone applications, including Docker, Java, IIS on Windows, Qemu, etc. It can be deployed in local dev, production, on-prem, and in the cloud in a consistent manner.

Stage 4: Maintaining

So, your microservices are deployed — now,  you have to maintain them. Monitoring and testing are an important part of maintenance for any project, and microservices are no different. With so many moving parts, building the right maintenance workflow is key. Otherwise, you risk blindspots when you experience a performance issue.

it can be difficult to visualize all of your microservices and understand their dependencies, leaving you with potential blind spots when you experience a performance issue. These tools below help to identify issues, specifically in microservices, and alert teams to fix them.

Datadog offers a suite of monitoring tools for servers, databases, tools, and services, through a SaaS-based data analytics platform. Datadog allows users to visualize all of the microservices at once and understand their complex interactions and dependencies, so you can quickly locate issues and troubleshoot. With a service map, developers can prioritize maintenance and optimization of important services. They can also identify potential choke points, like shared databases, across service boundaries.

PagerDuty is a popular on-call management tool for system administrators and support teams. It collects alerts from your monitoring tools, gives you an overall view of all of your monitoring alarms, and alerts an on-duty engineer if there's a problem.

Prometheus is a well-known open-source monitoring system with an active community and broad range of features. Its features such as multi-dimensional data collection and flexible querying are good for microservice maintenance. It can help developers keep track of system metrics — including memory usage and CPU consumption — over a given time period and can be used to determine the health of a software system.

Stage 5: Managing

You’re not done after you’ve set up your microservice architecture. After designing, building, deploying, and monitoring, questions still remain when incidents occur: how did this happen? Is it an issue for one service, or for many? Who is in charge of fixing this? What is the fix, and how quickly can someone apply it? You’ll want to catalog the answers to these issues for future reference.

Unfortunately, most microservice teams are behind the times here, and rely on outdated spreadsheets for cataloging issues, tracking fixes, and identifying their owners.

There’s a lack of tools for teams to enforce high-level policies and best practices and conduct proper management on their microservices.

  • That’s where Cortex comes in.  

Cortex provides a suite of tools that makes it easy to see your services and owners in one place, and we foster accountability and show you how to improve using a gamified scorecard.

Cortex’s microservices catalog helps teams record all the microservices currently running, and provides you with information on what each microservice is, how each operates, and who owns each one.

The key components of our tools are especially valuable to teams across the organization throughout the life cycle. These tools feature: 1) a production readiness review (PRR), or predefined checklist to make sure that the software is ready to deploy; 2) visibility into ownership; 3) easy integration within one tool; and 4) it automates updates.

There’s likely to still be a learning curve in your organization, and you’ll need to implement smart best practices to ensure efficient operations over time.  You need to constantly invest — and reinvest — in how you’re operating your microservices. A strong, flexible plan and the right tools for ongoing management will enable long-term success.

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