When looking to implement a scalable solution to automate key steps in your organization’s processes and workflows, Kubernetes is an invaluable tool. While it is a virtually unknown service to the layman, the tech-savvy will almost certainly perk up at the mention of it.
In this advanced Kubernetes tutorial, we will look at a range of higher level Kubernetes (often abbreviated to k8s) functions to see how running operations in containerized environments can improve the efficiency of your application usage.
Kubernetes is used to run collections of applications in containerized environments. By creating closed environments to complete app functions, you avoid the risk of harming your regular systems in the case of a bug or mishap from the apps that you are running.
By using containers, you also reduce the amount of CPU required to run your applications. You are essentially breaking the workload down into units that use the minimum CPU seconds required instead of running everything through your full server.
But what is a containerized environment? It is simply an application which runs in a container. In Kubernetes, containers run in atomic units called pods with their own IP address which in turn run on nodes which can be either physical machines or virtual machines.
That’s a very abbreviated breakdown of the ideas behind K8s. From these basics, more complex ideas and operations are used to make your applications run smoothly with the ability to scale up or down automatically.
New to Kubernetes? Read this first: A Comprehensive Guide to Kubernetes
The strength of K8s comes from the ability to connect pods and nodes running collections of applications. Networking operates on several levels.
When utilizing Kubernetes, every pod that you set up has its own unique IP address. Each pod holds containers which can communicate with each other. Additionally, those pods can network together in a cluster through a container network interface (CNI). Kubernetes clusters using CNIs instead of network address translations allows you to implement different networking configurations based on the needs of a cluster.
Due to scaling or redeployment, the IP addresses of individual pods can change. Kubernetes abstracts those IP addresses behind a service resource. That abstraction creates a virtual IP that serves as a virtual endpoint — creating the ability to balance loads and navigate service discovery while managing inter-service communication.
No Kubernetes network guide would be complete without looking at network policies. Network policies establish the access pathways used to transmit information from pod to pod and cluster to cluster. These policies are implemented via labels and namespaces. They are crucial tools for administrators seeking to ensure that communications are effective and secure.
Ingress controllers provide HTTP and HTTPS routing, which give external access to internal services. An ingress controller helps establish rules for routing and sets parameters for information traffic based on a request’s hostname or path.
K8s requires persistent storage solutions as data generated by pods is lost as soon as the pod is deleted or shut down. In order to retain all the important information and data your clusters have generated, several contingencies have been developed.
In the context of Kubernetes, a volume is a persistent directory that is accessible by a container in a pod. It can contain data, but does not necessarily need to. The key strength of a volume is that it lasts beyond the lifespan of a terminated pod — this allows data storage and state maintenance.
Persistent volumes exist and are managed independently of individual pods. They can be created statically or provisioned dynamically. Persistent volumes are basically abstractions that can match available volume with the storage requirements of the applications running within your k8s. They are quite versatile and can be utilized across several different environments.
Some applications run stateless operations, but others — such as databases — require managed and preserved states. StatefulSets is a tool that gives identifiers to each pod so that it maintains its identity and state across its operations. StatefulSets allow individual pods to be associated with their own persistent volumes to retain data and handle things like rolling updates without sacrificing reliability and high availability
Because it is important to follow resource management best practices, you need to understand resource requests and limitations in Kubernetes. Limiting the amount of CPU and memory allocated to a container keeps your operations running smoothly.
Affinity and anti-affinity features are used in scheduling operations. Affinity commands ensure workloads that require certain types of nodes are completed on those nodes. Conversely, an example of effective use of anti-affinity would be establishing configurations that prevent replicas of the same app from running on the same node.
There are a few ways in which affinity works. Rules are established that determine which nodes can be accepted to pods to perform specific tasks. In some cases, this means that a node will not be selected for scheduling if it does not meet all the rules and criteria. Or it can mean that nodes will be sought out for selection based on the criteria they meet.
Taints and tolerations are important to understand as part of an advanced Kubernetes tutorial. They work as a fine-tuned facilitator of affinity and anti-affinity rules. Taints use key, value, and effect tags to prevent nodes from accepting pods that do not match to those elements. Meanwhile, tolerations allow pods onto nodes if they match the node’s taints. These tools allow workloads that require specific conditions to run with correct resource allocation and effective scheduling.
One of the greatest strengths of Kubernetes is the ability to scale up or down automatically, depending on the workload. There are a few different ways that K8s handles autoscaling.
These two autoscalers focus on different vectors to ensure that your operations are running optimally. Horizontal Pod Autoscalers scale the number of pods up or down in a deployment according to metrics like CPU or memory usage. Vertical Pod Autoscalers adjust the resources supplied to running pods — so if a workload needs more resources over time, those resources can be allocated automatically.
Cluster Autoscaling involves dynamically provisioning and sending unused pods to new nodes if higher volume is needed or scaling down the number of nodes in a cluster when they are underutilized. This capability ensures optimal usage of clusters by matching the amount of pods and nodes in use to the workload at hand.
Deploying K8s workloads across geographic areas protects your operations from downtime due to location-specific problems such as power outages or damage to servers from natural disasters. Multi-zone deployment refers to clusters that span several zones in one region while multi-region deployment spreads cluster workloads across regions around the world. This ensures your high-availability setup remains highly available no matter what problems arise in a specific location.
When you have automated machines performing high-volume, important work, you need to be certain that your data is secure. Keeping sensitive information away from users and applications that should not have access is an absolute necessity.
RBAC in Kubernetes regulates access to the Kubernetes API based on user roles. Administrators define permissions that limit the actions some users can take based on their role and level of clearance. Basically, your RBAC configuration ensures that users and, indeed, even certain applications only have the access to clusters that they absolutely must have in order to complete their tasks.
Pod security policies set requirements for which pods will be accepted into your system. If a pod does not meet the defined conditions for a workload, it will not be allowed to contribute to that workload. Through these policies, compliance can be enforced by ensuring that confidential information never makes its way to vulnerable pods.
With all the functions in play with Kubernetes, a tool that helps the user manage traffic, security, and observability for microservices can prove invaluable. Istio is an open source service mesh that serves in your architecture as a proxy that intercepts traffic and routes it to optimal functions. Istio helps with service discovery, load balancing, and circuit breaking, for example. Having a Kubernetes Istio integration for your workloads helps improve security and effectively troubleshoot problems maintaining the integrity of your microservices architecture programs.
Sometimes you need to incorporate tools that are not available in the base version of Kubernetes. In order to ensure your workloads are completed as efficiently as possible, you may find yourself seeking options for custom resources that integrate with your APIs.
Custom resources make your Kubernetes operations more modular. Your cluster admins can use dynamic registration to allow your custom resources to kick in or shut down as needed. And a custom resource can be updated independently of the rest of the applications in a cluster or pod.
In order to best utilize custom resources, installing Kubernetes operators is a recommended course of action. Operators follow K8s principles to mimic the patterns of human users. This allows for a greater range of automation while ensuring your processes stay within the established parameters of your chosen Kubernetes operational patterns.
Even though this has been a more advanced Kubernetes tutorial — digging into more high level tools and concepts than an introductory tutorial would — we have barely scratched the surface of what skilled developers can do with K8s.
The experts at TEAM IM have extensive experience optimizing Kubernetes operations. Whether you want to improve your use of Kubernetes for automated scaling, improved security, increased automation opportunities, or any other feature, TEAM IM can help you get started.
Take advantage of the incredible functionality Kubernetes provide. Reach out to TEAM IM to learn more.