Log in
Kubernetes (K8s) is a container orchestration platform for building, testing, modifying, and scaling container-based applications.
With multiple “flavors” to choose from and the ability to operate both on-premises and in the cloud, K8s has become the de facto standard. According to recent data, Kubernetes is in the top spot in containerization management, with a more than 95% market share.
If you’re considering K8s for your enterprise environment or want to expand the scope of your Kubernetes deployment, here are four training essentials and eight best practices.
4 Essential Training Topics for Kubernetes Success
Whether this is your first time using Kubernetes or bringing new team members up to speed on container management, starting with the basics is essential.
Just as staff need AWS Data Science, Google Analytics, or Power BI training courses to leverage these solutions effectively, bringing users up to speed with key Kubernetes training topics is critical. These include:
1. Containerization Orchestration Fundamentals
Containers are common. Solutions like Docker, Podman, and OpenVZ allow companies to create and deploy virtual containers for storage, data processing, or application development.
Kubernetes helps you collectively manage these containers to maximize their efficiency. This process is known as orchestration. Standard orchestration functions include enabling cross-container communication, ensuring container security, and scaling container clusters.
2. K8s Terminology
Key Kubernetes terminology includes:
- Pod — A pod consists of one or more containers. They are the smallest unit of execution in K8s.
- Node — A node is the physical server or virtual machine (VM) that hosts a pod.
- Cluster — A cluster is a group of nodes, typically managed by a master node.
- Etcd — The master node contains etcd, often called Kubernetes source of truth. Any changes made in K8s are stored in etcd as JSON.
- API server — The API server enables communication with the Kubernetes API. It can be used by users, programs, and the kubectl command-line interface (CLI).
- Controller manager — The controller manager tells K8s controllers to create accounts, access APIs, and connect services to pods.
- Scheduler — The scheduler distributes work across nodes and calculates resource requirements to determine when pods should operate and which nodes should run these pods.
3. Possible deployment paths
With K8s, multiple deployment paths are possible. You may deploy Kubernetes locally on physical or virtual machines, run the solution in the cloud, or combine both.
Eight Best Practices to Streamline K8s Deployment
Once staff have a solid grasp of the basics of Kubernetes, the next step is deployment. However, given the scope and scale of K8s, teams can quickly become overwhelmed.
Here are eight best practices to help streamline deployment.
1. Pick the Right Flavor
Along with different deployment options, Kubernetes offers multiple “flavors,” each with benefits.
- Local Options: KIND (Kubernetes in Docker) and Docker Desktop are excellent choices for development and testing. These lightweight tools allow teams to experiment and fine-tune configurations before scaling to production.
- Cloud Native Services: Cloud providers like Google Kubernetes Engine (GKE), Amazon Elastic Kubernetes Service (EKS), and Azure Kubernetes Service (AKS) provide fully managed environments that simplify infrastructure management. These options reduce operational overhead by handling updates, monitoring, and scaling.
- Enterprise Solutions: Red Hat OpenShift and VMware Tanzu offer additional layers of automation, monitoring, and compliance. These tools are suited for organizations with complex multicluster environments or strict regulatory requirements.
Carefully evaluate your workload, team expertise, and deployment goals to select the best flavor for your use case.
2. Use Kubernetes Namespaces
Namespaces act as virtual partitions within a Kubernetes cluster. These logical separations allow you to organize resources effectively, manage multiple projects within the same cluster, and isolate workloads as necessary.
For example, you might create separate namespaces for development, testing,g, and production environments to avoid resource conflicts. Namespaces also help enforce resource quotas, making allocating CPU, memory, and storage fairly across teams or applications easier. This level of organization becomes vital as clusters grow in size and complexity.
Define Resource Limits
Resource limits are a crucial safeguard for optimizing cluster performance. By setting both minimum and maximum resource limits for CPU and memory, you can prevent one application from consuming all available resources and affecting the performance of others.
For instance, you might configure a resource request to guarantee a minimum CPU level for a critical application while setting a limit to prevent overconsumption during peak loads. These configurations are particularly valuable in multitenant environments, where fair resource distribution is key to maintaining smooth operations.
4. Consider Rolling Updates
Rolling updates are a powerful strategy for minimizing application downtime during deployments. Instead of updating all container instances simultaneously, this approach replaces them incrementally.
If an application spans five pods, Kubernetes can take down one pod at a time, replacing it with a new version while keeping the others running. This allows uninterrupted service for end users and provides a rollback mechanism if something goes wrong with the latest deployment. Integrating rolling updates into CI/CD pipelines is highly recommended for safer and more efficient implementations.
5. Implement Role-Based Access Control (RBAC)
RBAC is a security feature that enables granular access management in Kubernetes. By defining roles and assigning them to users or groups, you can control who can perform specific actions on resources within the cluster.
For example, a developer might be able to modify deployment configurations in the development namespace but restricted from making changes in production. RBAC reduces the risk of accidental misconfigurations and strengthens security, making it an essential practice for any Kubernetes environment.
6. Set up Pod Disruption Budgets (PDBs)
PDBs define the minimum number of pods that can run during planned maintenance or unexpected disruptions. By configuring PDBs, you can maintain application availability during these events.
For instance, if an application requires at least three replicas to function correctly, a PDB can be set to allow only one pod to be disrupted at a time. This ensures that user requests are handled even when disruptions occur, keeping critical services available.
7. Leverage Custom Resource Definitions (CRDs)
CRDs let you define custom resources and controllers by extending the Kubernetes API. In practice, this allows trained staff to build application-specific workflows. This feature is handy for organizations with unique application workflows or requirements.
An example is creating a custom resource type to manage specific configurations, such as database connections or application secrets. This level of customization empowers teams to automate repetitive tasks, streamline complex workflows, and enhance efficiency in managing Kubernetes environments.
8. Empower Kubernetes With Service Options
Solutions such as Azure Kubernetes Service (AKS) can leverage K8s in the cloud. Beyond managing containers, however, your team can extend the Kubernetes impact with additional service options.
For example, Azure Container Instances provide a lightweight alternative to Azure VMs, while the Azure Service Fabric lets you create and manage stateful services. This fabric powers various Microsoft services, including Power BI, Cosmos BD, and Dynamics 365.
Making the Most of Kubernetes
Kubernetes is a powerful, flexible platform for container management. However, make the most of this solution.
Whether you host K8s on-premises, leverage cloud vendor offerings, or use enterprise-grade management tools, comprehensive training and targeted best practices help streamline deployment and maximize K8’s impact.
The post Kubernetes Is Taking Over: Deploy Smarter With 4 New Techniques appeared first on The New Stack.
