What Is Kubernetes?
Kubernetes (K8s) is an open-source container orchestration platform that automates the deployment, scaling, and management of containerized applications.
A microservice can be packaged into a standardized container, so it runs the exact same way on any machine. The code lives on a server (or node). Kubernetes is the intelligent system that decides which container goes where, moves them if there’s a server failure, and adds more server resources to scale for high traffic.
What Kubernetes does:
- Self-heals: If a microservice crashes or a server fails, then Kubernetes detects it and automatically restarts a new instance to keep the system running.
- Scales horizontally: If your website suddenly gets a million visitors, Kubernetes can instantly create hundreds of copies of your microservice to handle the sudden load change.
- Discovers services and balances the load: Kubernetes acts like a switchboard, directing traffic to the right microservice, so they can communicate with each other without getting lost.
- Automates rollouts: Kubernetes allows you to update your services one by one. If the new version has a bug, it automatically rolls back to the previous working version.
You want microservices to be lightweight, so that they start quickly. Kubernetes loves lightweight services because it can move them around, turn them off, and restart them in milliseconds, making your entire infrastructure incredibly resilient.
What Is Service Mesh?
A service mesh is a dedicated infrastructure layer that’s built right into your app. It controls how the different parts of your application share data with each other. Think of microservices as the individual workers and Kubernetes as the manager of the warehouse. A service mesh can be thought of as a secure, private radio network that the workers use to communicate with each other safely and efficiently.
As you break a monolithic application down into dozens of Java microservices, communication becomes a mess. You start running into network logic problems. For example, is one service authorized to talk to another service? What happens if the network is too slow for proper communication? How do you encrypt the data that’s traveling between your services?
Without a service mesh, you’d have to write code for security and retries inside every microservice. This becomes tedious and unnecessary. A service mesh pulls that logic out of your code and handles it automatically.
What Is a Kubernetes Service Mesh?
Kubernetes manages your containers (which package your microservices), while a service mesh manages the communication between those containers.
A Kubernetes service mesh is a service mesh (such as Istio, Linkerd, or Cilium) that’s been designed to run inside of a Kubernetes environment. Most modern service meshes are built to integrate perfectly with Kubernetes.
Kubernetes acts as the foundation and provides basic connectivity. It gives every microservice an “address” so they can find each other. The service mesh then lives inside the Kubernetes cluster and adds a layer of communication logic to those connections.
The service mesh helps a Kubernetes Java microservices architecture in a few ways:
- Security: The service mesh forces every service to identify itself before talking to each other, enhancing the security of your application. No service is trusted by default, even if it’s inside your own network.
- Retries: If a microservice is slow to answer another one, the mesh automatically tries the call again. This automatically fixes temporary networking issues.
- Logic: The mesh can make appropriate decisions for your users. For example, it can check if a service is taking longer than a few seconds to respond, trigger an Else condition, and send the user to a maintenance page or alternate route.
- Traffic Splitting: You can deploy a “canary” version of your code to see if it works for a small group of test users before deploying it publicly to all your users.
- Observability: You’ll get a visual dashboard that shows you how your Java services are interacting together.
How Does Azul Prime Help with a Kubernetes Service Mesh?
In a Kubernetes environment, your Java microservices are constantly being moved, scaled, and restarted. When you add a service mesh (like Istio), you add a lot of “network overhead” because every piece of data has to pass through a sidecar proxy—a helper application that runs alongside your main application to handle utility tasks like security, communication, and monitoring.
Azul Prime helps by optimizing the Java Virtual Machine (JVM) itself, making the underlying microservices so efficient that they can handle the extra weight of the service mesh without slowing down.
Here are a few ways that Prime helps you optimize your application:
- Reduce latency: Every time that one service talks to another service through the service mesh, the data has to be encrypted, decrypted, and then routed by the sidecar. Azul’s C4 Garbage Collector eliminates the “stop-the-world” pauses, which keeps the communication steady and predictable throughout the service mesh.
- Boost throughput: Service meshes can require a lot of CPU resources to handle security and traffic routing. Prime replaces the standard Java compiler with the Falcon JIT Compiler, which generates highly optimized machine code. This allows your microservices to process more requests per second, “reclaiming” the CPU resources that the service mesh consumes.
- Scale with faster warm-up times: Kubernetes is designed to scale microservices up and down instantly. However, Java often suffers from a “warm-up” period where it runs slowly until the code is optimized. Azul Prime uses ReadyNow! to “remember” the optimizations from the application’s previous runs. When Kubernetes spins up a new pod to handle a traffic spike in your mesh, the microservice starts at 100% performance immediately, rather than sluggishly warming up.
- Manage costly resources: If your microservices are “heavy” and use a lot of memory, you can’t fit many of them on a single Kubernetes node. Because Prime manages memory more efficiently, you can pack more Java containers onto the same hardware. This reduces your cloud resource costs, even when you’re running a complex, resource-heavy service mesh.
To learn more about how Prime can provide you with a high-performance JVM, see Azul Prime: High Performance JVM.
