As applications become more complex, developers have moved from a monolithic architecture to microservices to more easily scale individual services and meet user expectations.
Because of their scalability, microservices have become popular for developing modern web, mobile, and cloud-based applications. In fact, major companies like Netflix, Uber, and Amazon have moved away from a monolithic architecture in favor of microservices, which speaks to the reliability of a microservices architecture.
Read on to learn more about why you should use microservices, how to build and scale microservices, the benefits of scaling, potential issues you may face, and the tools available to help.
What are Microservices?
Microservices are a software development architecture that organizes an application as a collection of loosely coupled services. Each service is self-contained and performs a specific task. Microservices communicate with each other through APIs.
For example, the user authentication microservice can provide an API that allows the product catalog microservice to verify the identity of a user before returning product information.
Microservices offer many benefits over traditional monolithic applications, including:
- Scalability: You can scale microservices independently, making it easier to scale up or down as needed.
- Resilience: If one microservice fails, the other microservices can continue to operate, making microservices-based applications more resilient to failure.
- Agility: You can develop and deploy microservices independently, making it easier to change the application without impacting the entire system.
Why Scale Microservices?
There are several reasons why you need to scale your microservices. These include:
- Handling increased traffic: As your application becomes more popular, you may need to scale microservices to handle more traffic.
- Improving performance: Microservices can be scaled independently, so you can scale up specific microservices that are becoming bottlenecks.
- Increasing reliability: If one microservice fails, the other microservices can continue to operate, making your application more reliable.
- Reducing costs: By scaling microservices efficiently, you can optimize resource use and reduce infrastructure costs.
To illustrate the usefulness of a microservices architecture, imagine that you’re operating an e-commerce application that needs to scale up during the holiday season to handle increased traffic or a social media application that needs to scale up during a major event like the World Cup or an election.
How to Scale Microservices
There are two main ways to scale microservices:
- Horizontal scaling: This involves adding more microservice instances to handle the increased load. It’s the most common type of scaling for microservices. You can add new containers or virtual machines to distribute the load across multiple instances.
- Vertical scaling: This involves increasing the resources (CPU, memory, etc.) of an existing microservice instance to handle additional load. While it can provide a short-term performance boost, it has limits. In the long term, it’s more cost-effective to use horizontal scaling.
Here are some tips for scaling microservices effectively:
Monitor your microservices performance
It’s important to monitor the performance of your microservices to ensure they’re scaling effectively. You can use various tools to monitor microservices performance, such as Prometheus and Grafana.
Use a microservices management platform
A microservices management platform can help you manage your microservices’ deployment, scaling, and monitoring. Some popular microservices management platforms include Kubernetes and Istio. The next section will discuss how you can manage scaling with Kubernetes.
Design your microservices for scalability
When designing your microservices, you should keep scalability in mind. You should design your microservices to be loosely coupled and stateless. Doing this makes it easier to scale your microservices horizontally.
Scaling microservices can be a complex topic, but it’s crucial to running a successful microservices-based application. By following the tips above, you can ensure you are effectively scaling.
Scaling Microservices with Kubernetes
Kubernetes is a container orchestration platform you can use to manage the deployment, scaling, and networking of microservices. Kubernetes makes it easy to scale microservices horizontally by adding or removing instances of microservices as needed.
You can use a HorizontalPodAutoscaler (HPA) to scale microservices with Kubernetes. An HPA is a Kubernetes object that monitors the metrics of a microservice and automatically scales the number of instances of the microservice based on those metrics.
Some common target metrics include CPU usage, memory usage, and request latency. It will start monitoring the target metric for the microservice. If the target metric exceeds or falls below the specified thresholds, the HPA will scale the microservice up or down accordingly.
For example, you could create an HPA for a microservice that sets the target CPU usage to 80%. If the CPU usage of the microservice exceeds 80%, the HPA will scale the microservice up by one replica. If the CPU usage of the microservice falls below 80%, the HPA will scale the microservice down by one replica.
Scaling Microservices with Docker Swarm
Scaling microservices with Docker Swarm is an alternative to Kubernetes for managing containerized applications. Docker Swarm provides a simpler, more lightweight orchestration solution, making it well-suited for smaller-scale deployments.
To scale microservices with Docker Swarm, you can use a service. A service is a Docker Swarm object that defines a set of containers that should be running. Docker Swarm automatically scales the number of containers in a service based on the demand for the service.
To create a service, you need to specify the following:
- The name of the service
- The image of the container that you want to run
- The number of replicas of the container that you want to run
- The ports that you want to expose on the container
Once you have created a service, Docker Swarm will start deploying the containers in the service to the Docker hosts in the cluster. Docker Swarm will also monitor the demand for the service and scale the number of containers in the service accordingly.
For example, you could create a service for a microservice that sets the number of replicas to 3. Docker Swarm will then run three instances of the microservice on the Docker hosts in the cluster. If the demand for the microservice increases, Docker Swarm will automatically start new microservice instances. If the demand for the microservice decreases, Docker Swarm will automatically stop microservice instances.
Scaling with Docker Swarm offers a simpler and less complex orchestration solution than Kubernetes. It’s well-suited for smaller projects and teams that want to leverage containerization and basic orchestration capabilities without the added complexity of Kubernetes. However, Kubernetes may offer more advanced features and scalability options for larger and more complex microservices architectures.
Potential Issues with Scaling
Scaling microservices can bring about several potential issues and challenges that you should carefully manage to ensure the stability and performance of your application. Here are some common issues to be aware of when scaling microservices:
- Complexity: Scaling microservices can be more complex than scaling monolithic applications because you need to manage the scaling of each microservice individually.
- Interdependencies: Microservices may be interdependent, so you need to ensure that you are scaling all the dependent microservices together.
- Data consistency: Maintaining consistency across microservices can be challenging, especially when distributing your data. Inconsistent data can lead to application errors and unexpected behavior.
- Monitoring and debugging: As the number of microservices grows, monitoring and debugging become more challenging. You need effective tools and practices to trace requests and diagnose issues.
Tools for Scaling Microservices
Scaling microservices requires a combination of well-chosen tools and practices. Here’s a list of tools to help you manage your microservices architecture.
Containerization and Orchestration
- Kubernetes: Container orchestration platform for managing, scaling, and deploying microservices.
- Docker: Containerization platform for packaging microservices and their dependencies.
Security and Identity Management
- OAuth 2.0 and OpenID Connect (OIDC): Standards for secure authentication and authorization in microservices.
- Keycloak: An open-source identity and access management solution.
Deployment and Configuration
- Helm: A package manager for Kubernetes applications.
- Kustomize: A standalone tool to customize Kubernetes objects through a kustomization file.
Monitoring and Observability
- Prometheus: A popular open-source monitoring and alerting toolkit designed for reliability and scalability.
- Grafana: A visualization and monitoring tool often used with Prometheus.
- Jaeger: A distributed tracing system for monitoring and troubleshooting microservices.
Logging and Log Analysis
- ELK Stack (Elasticsearch, Logstash, Kibana): A popular stack for centralized logging and log analysis.
- Fluentd: An open-source data collector for a unified logging layer.
Although using a microservices architecture can make it harder to maintain data consistency and introduces monitoring and debugging challenges, it’s ultimately beneficial due to its scalability and resilience. With the right tools, you should be able to effectively manage your microservices architecture and build high-performing, scalable applications.
You can learn more about microservices and scalability by reviewing the following resources: