This article will outline some recommended practices for utilizing Kubernetes (K8s).
K8s, the most used container orchestration solution, is the de facto standard for the contemporary cloud engineer to master. K8s is a famously complicated system to use and manage, so having a thorough understanding of what you should and should not do and what is feasible will provide a solid foundation for your implementation.
These guidelines address typical concerns across three main categories: application development, governance, and cluster setup.
Best Kubernetes Practices:
Use Namespaces
Namespaces in K8s are crucial for organizing objects, creating logical divisions inside the cluster, and ensuring security. A K8s cluster has three namespaces by default: default, kube-public and kube-system.
RBAC may regulate access to specific namespaces to limit a group's access to control the blast radius of any errors. For instance, a group of developers may only have access to the dev namespace and not the production namespace. Restricting separate teams to distinct namespaces might be advantageous for preventing duplication of effort and resource conflicts.
LimitRange objects may also be defined against namespaces to provide the default container size for containers deployed inside the namespace. ResourceQuotas may also restrict the overall amount of resources used by all containers inside a Namespace. Network policies may be applied to namespaces to determine pod-to-pod traffic.
Utilize Readiness and Life Probes
Readiness and Liveness tests are health examinations. These are other essential notions that must be used in K8s.
Readiness probes guarantee that requests are only sent to a pod when it is prepared to fulfill them. If it is unavailable, queries are sent elsewhere. Specifying the readiness probe for each container is essential since K8s does not provide default settings. For instance, if a pod requires 20 seconds to start and the readiness probe is absent, all traffic forwarded to the pod during startup time would fail. Readiness probes should be independent of other services, such as a backend database or cache service, and not account for any dependencies.
Liveness probes determine whether an application is active so that it may be marked as healthy. For instance, a specific route of a web application may be checked to confirm that it is responsive. If not, the pod will not be deemed healthy, and the probe failure will prompt the kubeletto to launch a fresh pod, which will be retested. This probe is used as a recovery mechanism if the process becomes inactive.
Use Autoscaling
Autoscaling may be used to dynamically alter the number of pods (horizontal pod autoscaler), the number of resources required by the pods (vertical pod autoscaler), and the number of nodes in the cluster (cluster autoscaler) based on the demand for the resources.
Based on CPU demand, the horizontal pod autoscaler may also scale a replication controller, replica set, or stateful set.
Scaling also presents issues, such as avoiding permanent data storage on the container's local filesystem, since this would prohibit horizontal autoscaling. A PersistentVolume might be utilized instead.
The cluster autoscaler is beneficial when the cluster's workloads are very varied and need fluctuating quantities of resources depending on demand. Automatically removing empty nodes is also an excellent approach to saving money!
Use Resource Requests and Limits
It is setting resource requests and limitations (minimum and maximum number of resources that may be utilized in a container) that prevent a container from the beginning without the needed resources allocated or the cluster from running out of available resources.
Without limitations, pods may use more resources than necessary, reducing the overall number of available resources and perhaps creating issues for other applications on the cluster. The scheduler may need help to position new pods if a node crashes correctly, and new pods may not be able to be put on the node.
If the program cannot be granted sufficient resources without requests, it may fail to start or behave erratically.
In millicores and mebibytes, resource demands and restrictions dictate the amount of CPU and memory available. Note that if your process exceeds the memory limit, the process is terminated. Thus it may only be suitable in some situations to specify this value. The process is throttled if your container's CPU use exceeds the allowed maximum.
Deploy Your Pods Across Multiple Nodes as Part of a Deployment, DaemonSet, ReplicaSet, or StatefulSet.
A pod should never be operated independently. Instead, they should always be part of a Deployment, DaemonSet, ReplicaSet, or StatefulSet to increase fault tolerance. The pods may then be spread over many nodes using anti-affinity rules in your deployments to prevent all pods from running on a single node, which might result in downtime if that node were to fail.
Use Multiple Nodes
Running K8s on a single node is not recommended if fault tolerance is desired. Utilize several nodes in your cluster to distribute workloads among them.
Implement a Role-based Access Control (RBAC)
Utilizing RBAC in your K8s cluster is required for system security. Users, Groups, and Service accounts may be granted access to conduct allowed operations on a specific namespace (a Role) or the whole cluster (ClusterRole). Each position may have several permissions. RoleBinding or ClusterRoleBinding objects bind the specified roles to the users, groups, or service accounts.
RBAC roles should be configured to provide permissions following the concept of least privilege, i.e., only necessary rights should be granted. For instance, the administrator's group may have access to all resources, but the operator's group may be able to deploy but not read Secrets.
Host Your Kubernetes Cluster Externally (Use a Cloud Service)
It may be challenging to host a K8s cluster on your hardware. As platform as a service (PaaS), cloud services provide K8s clusters, such as AKS (Azure Kubernetes Service) on Azure and EKS (Amazon Elastic Kubernetes Service) on Amazon Web Services. Taking advantage of this means that your cloud provider will control the underlying infrastructure, and scaling chores, such as adding and deleting nodes, can be accomplished much more quickly, allowing your engineers to manage what is running on the K8s cluster.
Upgrade Your Kubernetes Version
In addition to offering new functionality, new K8s versions also provide security and vulnerability patches, making it essential to run the most recent K8s on your cluster. Support for earlier versions will likely be inferior to that of current versions.
However, care should be used while migrating to a new version since some features may be deprecated and new ones introduced. Before updating, you must also ensure that the applications already operating on your cluster are compatible with the latest version.
Monitor Your Cluster's Audit Logs and Resource Logs
Monitoring the components of the K8's control plane is essential for controlling resource use. The control plane is the heart of K8s; these components keep the system operational and are thus necessary for the proper functioning of K8s. The control plane consists of the Kubernetes API, kubelet, etcd, controller-manager, kube-proxy, and kube-DNS.
Control plane components may provide metrics in a manner that Prometheus, the most popular K8s monitoring tool, can use.
Utilize automated monitoring solutions as opposed to manually handling warnings.
Audit logging in K8s may be enabled when launching the kube-apiserver to conduct a more in-depth analysis using your chosen tools. The audit.log contains a record of all API calls made to the K8s API and should be reviewed often for any potential cluster concerns—the audit policy.YAML file defines the default Kubernetes cluster rules and may be modified as needed.
A log aggregation tool, such as Azure Monitor, may transport logs from AKS to a log analytics workspace for further Kusto query examination. Cloudwatch may be used on AWS. Such as Dynatrace and Datadog, third-party solutions can provide more robust monitoring capabilities.
Lastly, a retention time should be established for the logs, often between 30 and 45 days.
Utilize a Version Management System
Configuration files for K8 must be managed using a version control system (VCS). This allows many advantages, including enhanced security, an audit record of modifications, and increased cluster stability. Changes should be subject to approval gates so the team may peer-review them before committing them to the main branch.
Use a Workflow Based on Git (GitOps)
Successful K8 deployments need consideration of your team's workflow practices. Using a git-based process allows automation via CI/CD (Continuous Integration / Continuous Delivery) pipelines, which increases the effectiveness and velocity of application deployment. CI/CD will also give a deployment audit record. Git should be the only source of truth for all automation and will allow unified cluster administration for K8s.
Cut Down on the Size of Your Containers
Smaller image sizes will accelerate your builds and deployments and minimize the number of K8s cluster resources containers need. Whenever feasible, unnecessary packages should be deleted, and compact OS distribution images, such as Alpine, should be prioritized. Smaller photos may be retrieved quicker and need less storage space than bigger ones.
This strategy will also give security advantages since hostile actors will have fewer possible attack avenues.
Label Your Objects to Organize Them
K8s labels consist of key-value pairs associated with objects to organize your cluster's resources. Labels should be relevant information that offers a framework for tracking how various K8s system components interact.
The official K8s documentation suggests the following pod labels: name, instance, version, component, part-of, and managed-by.
Labels may also be used similarly to tags in a cloud environment to monitor business-related information, such as object ownership and the environment to which an item should belong.
Also encouraged is the use of labels to specify security criteria, such as compliance and secrecy.
Utilize Network Policy
Network policies should be used to limit traffic between objects in a K8s cluster. All containers may communicate in the network by default, which poses a security concern if bad actors get access to a container and can traverse cluster objects. Like security groups in cloud platforms that limit access to resources, network policies may regulate IP and port-level traffic. Typically, all traffic should be blocked by default, followed by the implementation of allow rules to permit needed traffic.
Employ a Firewall
In addition to employing network rules to control internal traffic on your K8s cluster, you must install a firewall in front of your K8s cluster to restrict external API server requests. Whitelisted IP addresses and open ports should be controlled.
Key Elements
Following the best practices outlined in this article while developing, deploying, and managing your Kubernetes cluster will set you up for success on your modern application journey!
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