Kubernetes – What It Is and Why It’s Critical for a Performant Distributed Messaging System
Kubernetes and distributed messaging systems go hand in hand. It’s hardly imaginable to see a distributed messaging platform able to meet the performance requirements nowadays without the use of Kubernetes.
Building cloud-native environments without properly distributing and allocating storage and processing power would be disastrous, especially if the platform processes huge workloads and serves hundreds of thousands of clients.
That’s exactly why the containers emerged as the possible solution. However, over time even with containers, distributed systems again had performance and uptime issues. That’s when Kubernetes came to the rescue. Let’s see what Kubernetes is and why it’s critical for the performance of the distributed messaging systems.
Kubernetes started as an in-house project at Google. Back in 2014, the company open-sourced the complete Kubernetes project and made it available for everyone. Kubernetes was under development at Google for 15 years, used for running production workloads at scale. In essence, Kubernetes was created to intelligently utilize the storage and processing power of the available IT infrastructure.
The code name of the project “Kubernetes” originates from Greek – it means a pilot or helmsman. A commonly used abbreviation is K8s – the number 8 stands for the number of letters between the “K” and “s”.
Saying that Kubernetes is an open-source platform barely gives it justice. It’s also a portable and extensible platform developed to facilitate the management of containerized workloads and services. It has support for automation and custom-tailored configuration. The keyword here is “containerized” – let’s see why.
Containers: The Upsides and Downsides
Before we can see why Kubernetes is critical for distributed messaging system performance at a scale, we need to take a closer look at containers. That’s precisely why we emphasized the keyword “containerized” in the previous section.
Unlike Virtual Machines, containers can be decoupled from the underlying infrastructure. You can freely move them across clouds and OS. They have their own share of memory, process space, CPU, and filesystem. They found their use in distributed messaging systems because they offer many benefits.
First, container images are immutable, so you can enjoy faster deployment and efficient rollbacks anytime you need to do them. Containers are portable between cloud and OS. However, the most important benefits for distributed messaging systems include:
- Flexible and distributed microservices – DevOps can deploy and manage containers dynamically;
- Easily isolate resources to meet the requirements of applications use-case volume;
- Maximize the utilization of available resources with high efficiency.
Alright then, if containers are that good, why would anyone need a solution on top of containers? The problem emerges when one of the containers goes down. Do you track the health of all containers manually, or do you outsource this tedious task to an automated system? How do you handle load balancing and track traffic for every deployed container? Kubernetes has the answers to all these questions.
How Kubernetes Boost Performance in Distributed Messaging Systems
With Kubernetes, you have access to a framework that helps you run distributed messaging systems hassle-free. It doesn’t only improve performance but also the resilience and stability of the system. With Kubernetes, you can have custom deployment patterns, prevent failover of a container, or enjoy unparalleled scaling.
DevOps find it particularly useful for canary deployments to compare new versions to a stable one without risking any downtime. Let’s see how Kubernetes boost performance and improve the stability of distributed messaging systems at scale and in real-time.
Improved Load Balancing
The resilience of deployed containers and the performance depends on the load balancing. If traffic to a container is high, it will reflect on the performance. The high traffic can cause a container to fail, which then jeopardizes the performance and stability of the entire system unless it is solved manually.
Kubernetes delivers a new approach to load balancing as it allows automatic load balancing. Kubernetes can seamlessly identify containers with high traffic and automatically distribute the network traffic. Improved load balancing contributes to better performance.
Automated Storage Allocation
Storage distribution in distributed messaging systems plays a vital role when it comes to performance. The crucial data must be stored on SSD drives, while the rarely used data goes to HDD. Now you can do it automatically with Kubernetes.
Kubernetes also allows you to mount additional storage systems easily and overcome the challenges of building big data pipelines. It applies to both cloud and local storage solutions.
Rollouts and Rollback Don’t Affect the Performance
Maintaining a high level of performance while having to change the state of a container is very hard. You need to create a new container with the desired state and move the resources from the previous container to the new one. However, you can’t control the rate of moving resources that can affect the performance of the entire system.
With Kubernetes, you can have unique states for your deployed containers. More importantly, you can change the states of containers while controlling the rate at which the change executes. It enables you to execute rollouts and rollbacks with no impact on the system’s performance.
The Best Use of Your Resources
Furthermore, Kubernetes enables you to deploy containers into your nodes. Since you are working with limited resources, the distributed messaging system’s performance will depend on how efficiently you use the available resources.
Kubernetes enables you to choose which nodes you want to use to run the tasks in the containers. You can specify the memory and CPU power requirements for every container, thus putting your resources to the best use.
Great Self-Healing Capabilities
Without Kubernetes or your action, a distributed messaging system would continue to advertise failed containers to clients. In many instances, failed containers are memory-hungry, and they can starve all other containers on the same server. You can imagine what happens to the distributed messaging system’s performance in this scenario.
You can completely prevent it from happening and maintain the same level of performance because with Kubernetes, you can set the memory limit for containers, automatically restart failed containers, and implement user-defined health checks for each container.
To sum up, Kubernetes tackle all the challenges of container deployment and enable you to drive the current state of a distributed messaging system to a defined one. With Kubernetes, you can maintain solid performance and even improve it by putting it on auto-pilot. Here at Pandio, we specialize in delivering managed Apache Pulsar service leveraging Kubernetes, AI, and ML.
We didn’t choose Apache Pulsar vs Kafka just because it’s cloud-native but also because there are various problems when using Kafka. Find out more about how we can help you benefit from a performant distributed messaging system.