What Is Microservices?
Microservices is a building-block approach to software development. Traditional software development is a monolith style, where you build one giant block of code. Instead, a microservices architecture is made up of many small, independent services that communicate with each other to form a complete application. Each service has its own job, like handling payments or managing a user profile, and it acts independently so you can update it, scale it, and isolate any bugs.
What Are the Different Types of Microservices Tools?
Building and maintaining a microservices architecture is like managing a small city. These tools help you handle transportation through your city (networking), waste management (logging), city research (monitoring), and even law enforcement (security).
We’re going to categorize some of the most popular tools by the problems they solve:
- Containerization and orchestration: Containers act like shipping boxes for your microservices. They help you move your microservices around, so that you can run each microservice on any machine. Orchestrators act like the cranes and operational procedures that stack the containers.
- API gateways: These gateways act as the front door for your application. Instead of communicating to 50 different microservices, a client app interacts with the gateway, which routes their request to the right microservice.
- Communication and messaging: Microservices use these tools to communicate with each other without getting tangled or getting the messages crossed.
- Monitoring and logging: A microservices application could have hundreds of log files. These tools combine the logs and monitoring data to show you one big picture of what’s happening across your microservices.
Microservices Containerization and Orchestration Tools
Containers act as the packaging for your microservices, bundling the code with all its dependencies into containers, to allow you to run your microservices the exact same way in any environment. Orchestration tools serve as the brain that manages these containers at scale.
Some standard tools include:
- Docker: The standard container for code, which allows you to run the code the same way on any machine.
- Kubernetes: Created by Google, it’s the leading orchestration tool to automate deploying, scaling, and managing your containers.
- Managed services: Each cloud platform hosts its own managed service to handle the heavy lifting of managing Kubernetes for you. This includes Amazon EKS (Elastic Kubernetes Service), Microsoft AKS (Azure Kubernetes Service), and Google Cloud GKE (Google Kubernetes Engine).
Microservices API Gateways
API gateways manage communication with the APIs across all of your microservices. You can use a gateway to route your users’ client apps directly to the microservices they need to use.
Some standard tools include:
- Kong: A high-performance, open-source gateway that includes a large ecosystem of plugins.
- Apigee: Google Cloud’s enterprise-grade tool provides deep analytics and security for your APIs.
- Managed services: Each cloud platform hosts its own managed service to act as an API gateway that scales automatically. This includes AWS API Gateway, Microsoft Azure API Management, and Google Cloud API Gateway.
Microservices Communication and Messaging Tools
Communication and messaging tools connect your microservices together to keep them in constant communication.
Some standard tools include:
- Message brokers: Apache Kafka and RabbitMQ allow microservices to send messages to each other, even if the receiving service is currently busy or offline.
- Service mesh: Istio or Linkerd manage the complex web of service-to-service communication. These tools handle encryption and automatic retries.
- Managed services: Each cloud platform hosts its own managed services to handle messaging across your solution. Simple queues include AWS SQS, Azure Queue Storage, and Google Cloud Pub/Sub. Enterprise Pub/Sub solutions include Amazon SNS, Azure Service Bus, and Cloud Pub/Sub. Event streaming examples include Amazon Kinesis, Azure Event Hubs, and Cloud Pub/Sub. Managed Kafka services include Amazon MSK, Azure HDInsight, and Google Cloud Managed Service for Kafka.
Microservices Monitoring and Logging Tools
These monitoring and logging tools act as the eyes and ears of your distributed system, providing you with visibility and insights into the health and behavior of all your microservices.
Some standard tools include:
- Prometheus and Grafana: Prometheus collects the data, and Grafana turns it into real-time dashboards.
- ELK stack (Elasticsearch, Logstash, Kibana): Search and analyze millions of log lines.
- Distributed tracing: Jaeger and Honeycomb can follow a single user request as it travels through multiple services.
- Managed services: AWS provides the CloudWatch ecosystem. Microsoft provides the Azure Monitor suite with Azure Monitor, Log Analytics, and Application Insights. Google provides the Cloud Operations suite, which includes Cloud Logging, Monitoring, Trace, and Profiler.
How Azul Prime Helps Microservices Tools
Azul Prime is a high-performance Java Virtual Machine (JVM) that’s designed to resolve the performance and cost bottlenecks that occur when running Java microservices in the cloud. Standard microservice tools manage the outside of the container (such as containerization, orchestration, messaging, and monitoring), but Azul Prime optimizes the code execution inside your containers.
Here are a few ways that Azul Prime helps you optimize your Java code for microservices tools:
- Enhance container orchestration: Orchestration tools like Kubernetes rely on horizontal scaling, where they spin up new copies of a service when traffic spikes. However, standard Java has a “warm-up” period where it runs slowly before it reaches its peak speed. Azul’s ReadyNow! and Cloud Native Compiler allow new microservice instances to start immediately at full speed, making your Kubernetes autoscaling much more responsive and reliable.
- Improve communication and messaging: Microservices communicate constantly. Java’s Garbage Collection regularly pauses the application to clean up memory, which causes jitter and latency spikes. Azul’s C4 (Continuously Concurrent Compacting Collector) is a pauseless garbage collector that ensures messaging tools like Apache Kafka or Cassandra maintain consistent, high speeds even under heavy loads.
- Optimize monitoring and logging: Many alerts in Prometheus or Datadog are triggered by temporary Garbage Collection pauses (such as “Service unreachable” errors). By eliminating these pauses, Azul clears the noise out of your monitoring dashboard so you can focus on real, critical issues. Azul integrates directly with observability tools like Dynatrace, New Relic, and Grafana.
To learn more about how Azul Prime can provide you with a high-performance JVM, see Azul Prime: High Performance JVM.
