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Glossary

Kubernetes Replica

Backend
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

What Is a Kubernetes Replica?

Kubernetes replicas are clones that facilitate self-healing for pods. As with most processes and services, pods are liable to failure, errors, evictions, and deletion. For instance, pods may fail and be subsequently evicted when there is a sudden drop in system resources and an increase in node pressure.

Your Kubernetes orchestrations and deployments require a certain number of pods running in your clusters in order to succeed. If these pods cannot be replaced after failure or eviction, your entire workflow may fail. Before the conception of replicas, Kubernetes administrators were required to manually replace or fix broken and evicted pods.

This ultimately goes against the ethos of Kubernetes – which is one of automation and orchestration. Thus, replicas were introduced to timeously replace failed pods and ensure the integrity of your K8 workflows. However, replicas can’t do this on their own. There must be another layer or process that monitors the replica count. This is where controllers come in.

Controllers are responsible for monitoring and ensuring the integrity of your Kubernetes cluster. If your cluster’s state changes erroneously, the controller will request or make the necessary changes to rectify the issue.

Kubernetes has a variety of controllers, each designed for a separate but specific use case. However, they all share a commonality – they monitor a select group of pods and schedule replacements for failed pods to ensure that the correct number is always running.

The controller types responsible for monitoring and maintaining a balanced number of replicas are known as Replica Sets (or ReplicaSets (RS)). Essentially, they ensure that there are a specified set of identical pods running at any given time.

Older versions of Kubernetes required users to create, access and manipulate ReplicaSets directly. Kubernetes 1.2 introduced Deployments, a new powerful abstraction that could be used to manage replicas. While you can still manually configure and ReplicaSets directly, this is unnecessary and nonoptimal. Deployments offer a far more efficient approach.

How Do Kubernetes Replicas Work?

As mentioned in the previous section, there are two ways to define or configure a ReplicaSet; directly through a YAML configuration file or through a deployment.

The ReplicaSet config file has two important features:

  • Pod Template: A template for new Kubernetes pods.
  • Replica Count: The number of replicas (pods) the controller should always be running.

When you instantiate a ReplicaSet, it creates the desired number of replicas using the pod template. If any of the pods in the group die or get evicted, the ReplicaSet controller creates a replacement. Similarly, if the ReplicaSet discovers an extra pod in the group, it will randomly delete one of the Kubernetes replicas in circulation. This ensures the integrity of the defined pod count. The following ReplicaSet configuration file specifies four replicas:

apiVersion: apps/v1
kind: ReplicaSet
metadata:
  name: my-replicaset
  labels:
    app: myApp
    tier: backend
spec:
  replicas: 4
  selector:
    matchLabels:
      tier: backend
  template:
    metadata:
      labels:
        tier: backend
    spec:
      containers:
      - name: mycontainer
        image: nginx

Comparatively, the configuration file for a deployment isn’t all that different:

apiVersion: apps/v1
kind: Deployment
metadata:
  name: my-deployment
  labels:
    app: nginx
spec:
  replicas: 4
  selector:
    matchLabels:
      app: nginx
  template:
    metadata:
      labels:
        app: nginx
    spec:
      containers:
      - name: nginx
        image: nginx:1.28
        ports:
        - containerPort: 60

It still follows a similar YAML structure. It sets four replicas (.spec.replicas). Whether you’re using a Deployment or direct ReplicaSet to manage your replicas, they essentially work the same. Using the above examples, there will always be four replicas running and waiting to replace any failing pods.

Why Do You Need Kubernetes Replicas?

Technology isn’t infallible. For this reason we have technological fail-safes such as backups. Kubernetes replicas acts as fail-safes for pods. Pods and individual containers are bound to fail from time-to-time.

Kubernetes replicas provide them with the ability to self-heal and thus, improve the overall reliability of your orchestrations. Without replicas, the risk of your deployments failing would increase. You would have to monitor your deployments and orchestrations to manually intervene when a pod or container dies. Managing your clusters would require more work without replicas to pick up the slack.

Additionally, replicating pods and containers can also prevent nodes and instances from overloading. Having multiple versions of containers and pods allows you to distribute traffic among them. This is referred to as load-balancing.

However, if the load does become unmanageable for the number of instances running on your system, replicas can be used to scale it up and ensure that there are enough pods (and containers) in the pool. In fact, Kubernetes features replica autoscaling. Thus, you never have to worry about managing and tracking the load-balancing or reliability of your orchestrations yourself.

Is a Replica the Same as a Pod?

A Kubernetes replica is regarded as an instance or a copy of a Kubernetes pod. It can only truly be considered a pod when it replaces a deleted or evicted pod. Until then, it essentially remains an abstraction. However, the distinction isn’t very important as many replicas eventually become pods.

How Many Replicas Should You Have in Kubernetes?

Some sources suggest that a single replica is sufficient. However, it’s recommended to have at least two to ensure reliability. That said, ensuring that your ReplicaSet doesn’t make an accidental match is far more important, especially when working with multiple ReplicaSets.

Any pod that matches a ReplicaSet’s label selector will be managed by that ReplicaSet, regardless of whether the ReplicaSet created the pod or not. This can be especially problematic for users running two ReplicaSets with similar label selectors but different replica counts. One ReplicaSet may attempt to reduce the number of pods, while the other may try to increase it. As such, you must ensure that all your ReplicaSets have unique label selectors.

As such, it’s important that you keep track of your Deployments and the ReplicaSets they rollout. Kubernetes deployments can be exceedingly complex – especially for large enterprises working with microservices and complicated cloud native applications with IoT elements. Keeping track of all these Kubernetes resources can become challenging over time. Hence, using a comprehensive Kubernetes monitoring tool is no longer just advisable, for many, it’s considered mandatory. Nevertheless, not all Kubernetes monitoring tools are built equally.

Monitoring Kubernetes with Sematext

Sematext Monitoring is an infrastructure monitoring tool with advanced Kubernetes monitoring features that make it easier to keep an eye on the health status of your workloads from deployments to pods, replica sets, and beyond. You can monitor pod, container, and host metrics, as well as collect Kubernetes logs.

Sematext features out-of-the-box dashboards that you can customize to visualize and correlate all the data that you need to ensure the health of your workloads, including container-specific metrics about CPU, memory, disk I/O, network usage on a per-container basis and host-specific metrics, grouping data seamlessly between hosts, containers, and clusters.

You can set up alert rules for each of these metrics and use the anomaly detection feature to be notified whenever something goes wrong within your Kubernetes environment. Multiple notification channels are available for you to choose from, including email, Slack, and PagerDuty. That way, you can intervene immediately after issues are found before they escalate.

Sematext is a one-stop-shop solution regardless of how complex and dynamic your infrastructure is. With service auto discovery capabilities, it easily adapts to your services as they scale up or down. It constantly looks for new apps and services to make sure they are immediately monitored as they come online, without you needing to go through extra configuration steps.

Sematext has a 14-day free trial for you to see how easy it is to use it for Kubernetes monitoring. Try it out yourself or check out the video below if you need more information.

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