How to design a microservices architecture with Docker containers

Application development trends guide industries (tech and non-tech alike) toward a more cloud-native and distributed model with digital-first strategies. Many organizations are adopting new technologies and distributed workflows to stay competitive. 

Software development pipelines enable teams to collaborate efficiently and maintain productivity. Notably, many organizations that were early adopters of containerization and multi-cloud environments are now leading in agility and scalability. Whether you’re developing a SaaS platform, modernizing legacy systems, or supporting continuous delivery, understanding how containers and orchestration tools fit into the bigger picture is essential.

What is Docker?

Docker is an open source container technology and a foundational platform for software containers. These containers encapsulate an application, along with its libraries, tools, and runtime, into a single, replicable package that can run consistently across multiple hosting environments like AWS, Microsoft Azure, and Google Cloud.

Docker containers helped revolutionize the software development world by enabling applications to perform the same way regardless of the underlying infrastructure. 

Today, developers use Docker to build modules called microservices, which decentralize packages and divide tasks into separate, stand-alone integrations that collaborate. For example, developers for a nationwide pizza chain can build a microservices application for taking an order, processing a payment, and creating a ‘make’ ticket for the cooks and a delivery ticket for the drivers. These microservices would then operate together to cook and deliver pizzas all over the country.

Key components of the Docker architecture

When people talk about Docker, they often mean Docker Engine, the runtime that allows you to build and run containers. But before you can run a Docker container, you need to create a Dockerfile.

• Dockerfile: Defines everything needed to run the container image, including the OS network specifications and file locations.  
• Docker Image: Once you have a Docker file, you can build a Docker Image, which is the portable, static component that runs on the Docker Engine. A Docker Image is a set of instructions (or a template) to build Docker containers.
• Docker Compose: Primarily used for defining and running multi-container Docker applications on a single host, ideal for development. For clustering across hosts, Kubernetes is now the standard. 
• Docker Swarm: Developers can use Docker Swarm to turn a pool of Docker hosts into a single, virtual Docker host. Swarm silently manages the scaling of your application to multiple hosts.
• Docker Hub: Docker Hub is a massive and growing ecosystem of containerized microservices. It hosts millions of container images, including official builds for popular services like NGINX, MySQL, and Redis, as well as thousands of community-maintained images. 

If you’re running on AWS, Amazon EC2 Container Service (ECS) is a container management service that supports Docker containers and allows you to run applications on a managed cluster of Amazon EC2 instances. ECS provides cluster management, including task management and scheduling, so you can scale your applications dynamically. Amazon ECS also eliminates the need to install and manage your own cluster manager. ECS allows you to launch and kill Docker-enabled applications, query the state of your cluster, and access other AWS services (e.g. CloudTrail, ELB, EBS volumes) and features like security groups via API calls.

Designing with microservices in Docker requires new thinking and approaches, but also creates unparalleled abilities for building stable, scalable integrations. 

What are microservices?

Microservices represent a shift away from traditional monolithic application development. Instead of building one large application, developers create specialized, cloud-hosted sub-applications, each with a specific business function. Microservices distribute application load balancing and can help ensure stability with replicable, scalable services interacting.

But what’s the right approach for breaking a monolithic integration apart? When deconstructing an application into modules, engineers tend to follow planned decomposition patterns, sorting the new software modules into logical working groups.

For example, a grocery chain’s shipping and tracking software that currently uses one application for fruit might decompose into modules that process bananas, oranges, etc. This may improve tracking aspects, but decomposing software along logical subdomains—fruit types in this instance—can have unforeseen consequences on business ability.

Microservice architecture takes a different approach to organizing modules. It decomposes applications around business capabilities, building cross-functional teams to develop, support, and continually deploy microservices. Fowler emphasizes the “products, not projects” approach to business-focused decomposition: delivering a package isn’t a one-time project with a team that breaks upon completion, but an ongoing, collaborative commitment to continually delivering excellent products.

Microservices also decentralize traditional storage models found in monolithic application development. Microservices work best with native management of their own data stores, either repeated instances of the same database technology or a blend of separate database types as most appropriate for the service. The advantages of the microservice approach are still being explored. So, as with all systems, be aware of potential pitfalls and limitations of the practice.

Challenges of building a microservice architecture

The benefits of microservices come with several challenges: 

1. Service tracking: Services distributed across multiple containers and hosts can be hard to track. Rather than a single stop to tweak monolithic integrations, collaborating microservices scattered throughout your environment need to be inventoried and quickly accessible.
2. Rapid resource scaling: Each microservice consumes far fewer resources than monolithic applications, but remember that the number of microservices in production will grow rapidly as your architecture scales. Without proper management, many little hosts can consume as much compute power and storage as a monolithic application.
3. Inefficient minimal resourcing: If you’re using the AWS environment, there’s a bottom limit to the resources you can assign to any task. Microservices may be so small that they require only a portion of a minimal Amazon EC2 instance, resulting in wasted resources and costs that exceed the actual resource demand of the microservice.
4. Increased deployment complexity: Microservices stand alone and can be developed in many programming languages. But every language depends on its own libraries and frameworks, so these multiple programming languages will require a completely different set of libraries and frameworks. This increases resource overhead (and costs) and makes deployment a complex consideration.

But these obstacles aren’t insurmountable. This is where container technology like Docker can step in and fill existing gaps.

Docker to the rescue for microservices

Docker technology addresses these microservices challenges through the following: 

• Task isolation: Create a Docker container for each individual microservice. This solves the problem of resource bloat from over-provisioned instances idling under the almost non-existent strain of a lone service, and multiple containers can be run per instance.
• Coding language support: Divvy all the services required to run a language, including libraries and framework information, into linked containers to simplify and manage multiple platforms.
• Database separation: Use Docker volumes or dedicated data containers for storage separation.
• Automate monitoring: Tools like Sumo Logic integrate with Docker to monitor running containers, logs, and performance metrics for continuous delivery pipelines.

Five principles to enable your architecture

1. Cultivate a solid foundation. Everything starts with people, so make sure yours are ready to live and breathe in a microservices environment.
2. API-first design. Each microservice should have a clearly defined API contract — often REST or gRPC — which serves as its communication interface. Design your services API-first to support loose coupling and discoverability
3. Ensure separation of concerns. Each microservice must have a single, defined purpose. If it starts feeling like they should add a responsibility, add a new microservice (and a new API) instead.
4. Production approval through testing. Write comprehensive testing parameters for each microservice, then combine them into a full testing suite for use in your continuous delivery pipeline.
5. Automate deployment. Automate code analysis, container security scans, pass/fail testing, and every other possible process in your microservice environment. Leverage container orchestration tools and continuous deployment pipelines to manage microservices at scale.

How do Docker and Kubernetes relate?

Kubernetes and Docker are often mentioned together, but they serve distinct roles in the container ecosystem. Docker provides the container runtime and includes tools such as the Docker CLI, Docker Daemon, Docker Desktop, Docker Compose, and Docker Hub. It also offers a native clustering tool for orchestrating and scheduling containers across machine clusters. 

In contrast, Kubernetes is a container orchestration platform designed to automate the deployment, scaling, and management of containerized applications across clusters. It’s meant to coordinate clusters of nodes at scale in production efficiently. It works around the concept of pods, which are scheduling units (and can contain one or more containers) in the Kubernetes ecosystem, and are distributed among nodes to provide high availability.

One can easily run a Docker build on a Kubernetes cluster, but Kubernetes itself is not a complete solution and is meant to include custom plugins.

Although Kubernetes and Docker are fundamentally different technologies, they work well together and facilitate the management and deployment of containers in a distributed architecture. 

Make the move to microservices

The shift to microservices, powered by Docker containers and orchestrated through Kubernetes clusters, allows organizations like yours to build more scalable, resilient, and agile applications. By adopting a containerization strategy combined with DevOps automation, you can modernize your application development and deployment processes.

To learn more about managing containers, check out how Sumo Logic’s Docker App can help you monitor and optimize your Docker containers and Kubernetes environment for better performance and visibility.