What is Kubernetes Autoscaling: Things you need to know
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Scaling means adjusting something up or down to maintain the standard condition. Autoscaling means scaling something automatically. Autoscaling is used to optimize the web cluster machines under human traffic.
As Kubernetes is all about container orchestration, autoscaling has become one of its vital features. A website or web app can’t scale on its own. Kubernetes autoscaling maintains its resources and workloads. It always keeps an optimum condition for the cluster’s nodes and podes. This makes the web faster and also saves your money. But, do you know how Kubernetes autoscaling works?
In this article, we will talk about Kubernetes autoscaling, its types, and how they work. So, without any further delay, let’s begin.
The Beginning of Kubernetes Autoscaling
When a user enters a website or web app, it sends a request to the cloud provider to provide the necessary information. The cloud database then searches for the required information and sends it back to the website interface at the expense of cloud resource performance.
Conventionally, employers have always had to keep a close eye on the traffic. And they set a standard number of nodes to operate the website smoothly.
- When the users’ number increases, employers have to monitor, calculate, and upscale the server.
- When user load decreases, they downscale the resource number.
Manually, this task was lengthy and tiresome. Because
- They always had to monitor the load time.
- They start scaling after the traffic occurs, which results in a slow response.
That is why Google container and cloud engines (GKE & GCE) first introduced the autoscaling feature to Kubernetes. Kubernetes is a container orchestration tool, and autoscaling is a scaling feature. Kubernetes gets the trust of people easily.
Types of Kubernetes Autoscaling
Kubernetes makes it easy to dynamically manage our web apps and web infrastructure. There are three key ways that Kubernetes supports autoscaling. They are
- Horizontal Pod Autoscaler (HPA): It makes replicas of pods in response to app demand.
- Vertical Pod Autoscaler (VPA): It ups and downs the memory resource requests.
