Containerization has emerged as a popular way to package applications for deployment. Software containers are analogous to shipping containers in that they are self-contained and include everything an application needs in one package called a container.
What is Software Containerization?
A container packages an application’s code, any needed software libraries and a runtime environment into a single entity. IT teams can then deploy these containers and run them on any system with a container engine, regardless of the underlying operating system.
Containerization evolved from server virtualization technologies, but it is not just another type of virtualization. Containerization takes the level of abstraction a step further. Containers are like virtual machines (VMs), but they don’t have a copy of an operating system and are lighter.
Containers have their own file system, CPU allocation, memory and process space. Like VMs, multiple containers running on the same hardware are independent and get abstracted from the hardware and the underlying operating system. This means you can run the same container unaltered on multiple host systems, such as Windows, Linux, Unix, macOS and various public cloud providers.
The following diagram shows the path from traditional monolithic deployment to virtualized deployment and containerization.
Docker is probably the most widely used container platform and runtime engine, but others, such as CRI-O and Podman are also popular. The benefits of containerization make it a popular way for development teams to deploy software.
It is so popular that when combined with how easy it is to create containers, many organizations run into a management issue trying to track the large number of containers that get deployed in DevSecOps and Production environments. Container sprawl became a problem in the same way virtual server sprawl became a problem for virtualization platforms. Kubernetes emerged as a popular solution to tame and manage containers and the sprawl issue.
What is Kubernetes?
Many organizations deploy numerous containers from development to production. These containers are spread across multiple cloud services, private data centers and server farms. Operations teams require efficient tools to manage these containers and verify that the applications are running and available. This process is called container orchestration and Kubernetes delivers what is needed.
Kubernetes is popular with developers and DevSecOps teams due to its extensive features, toolset and support by major cloud service providers. Many cloud providers now offer fully managed Kubernetes services. Kubernetes has revolutionized modern application deployment by transforming how organizations deploy, scale and manage their applications.
Kubernetes provides the following services to help orchestrate containers:
- Rollouts - Describes the target container landscape needed for an application and enables Kubernetes to handle the process of getting there. This includes new deployments, changing existing deployed containers and rollbacks to remove obsolete deployments.
- Service discovery - Automatically expose a container to the broader network or other containers using a DNS name or an IP Address.
- Storage orchestration - Mount storage from the cloud or local resources as needed and for as long as necessary.
- Load balancing - Manage the load across multiple containers delivering the same application to help establish a consistent performance.
- Self-healing - Monitor containers for issues and restart them automatically if required.
- Secret and configuration management - Store and manage sensitive information more securely such as passwords, OAuth tokens and SSH keys. Deploy and update these secrets and application configurations that use them without rebuilding the containers — all without exposing the secrets on the network.
Understanding Kubernetes Architecture
The architecture of Kubernetes is distributed and modular, which makes it possible to manage containerized applications across distributed groups of machines. A Kubernetes cluster comprises a minimum of one Master (control plane) node and several worker nodes, each of which plays an important role in managing the lifecycle of the applications. Note that the term Master node is being phased out, and Control Plane is becoming the official terminology.
Key Components of Kubernetes
Kubernetes deployments use the following components:
- Clusters - The core building blocks of the Kubernetes architecture. Clusters comprise nodes (see below). Each cluster has multiple worker nodes that deploy, run and manage containers and one Control Plane node that controls and monitors the worker nodes.
- Nodes - A single compute host that can be physical, virtual or a cloud instance. Nodes exist within a cluster of nodes (see above). Worker nodes host and run the deployed containers, and a Control Plane node in each cluster manages the worker nodes in the same cluster. Each worker node runs an agent called a kubelet that the Control Plane node uses to monitor and manage it.
- Pods - Groups of containers that share compute resources and a network. Kubernetes scales resources at the Pod level. If additional capacity is needed to deliver an application running in containers in a Pod, then the software can replicate the whole Pod to increase capacity.
- Deployments - Control the creation of a containerized application and keep it running by monitoring its state in real time. The deployment specifies how many replicas of a Pod should run on a cluster. If a Pod fails, the deployment recreates it.
These components split across two primary sections, the control plane and the data plane, which are further subdivided as follows:
Control Plane - This is responsible for decision-making and issuing commands. It usually runs on a separate set of machines to help provide high availability. The key components that run on the Master are:
- API Server (kube-apiserver) - The Kubernetes API serves as the primary interface for managing resources like deployments and Pods by submitting create, update, or delete requests.
- Scheduler (kube-scheduler) - Assigns Pods to worker nodes based on available resources and Pod requirements, optimizing cluster resource utilization.
- Controller Manager (kube-controller-manager) - Operates a group of controllers that monitor the condition of the cluster and implement necessary actions to see if it aligns with the desired state. These include deployment controllers, which maintain the desired Pod replicas, and replica sets, which can verify whether a specific number of Pod copies are running.
- etcd - A distributed key-value store that maintains the shared state of your cluster, ensuring high availability for your control plane components.
Data Plane (Worker Nodes) - The infrastructure nodes that run the containerized applications. They run container engines, manage Pods and handle the actual workload of applications. In addition to the Nodes and Pods outlined above, the Data Plane service also runs:
- Kubelet - Manages the lifecycle of Pods and makes sure the containers are healthy on each node.
- Kube-proxy - Acts as a virtual network traffic director, implementing network policies and enabling communication between Pods across the cluster.
Getting Started with Kubernetes
Various methods are available for setting up, testing and operating Kubernetes in test and production environments. When installing Kubernetes, it’s important to select an appropriate installation type based on factors such as ease of maintenance, security, control, available resources and the level of expertise required to manage a cluster.
A detailed outline of how to get started with Kubernetes is beyond the scope of this article. But the official Kubernetes site has a good Getting Started page that is an ideal jumping-off point for anyone looking to try the container management platform.
Most configuration occurs via a command-line tool that communicates with a Kubernetes cluster control plane using the Kubernetes API. This tool is called kubectl, and the Kubernetes documentation site has a complete outline of how to use the commands and their syntax.
Benefits of Kubernetes
Using Kubernetes to manage your containerization infrastructure offers numerous benefits. It improves scalability, portability, resource efficiency and more. It is an invaluable tool for modern application deployment and management. Here are some of the key advantages of using Kubernetes for container orchestration:
Container Orchestration Benefits
- Automated Deployment and Rollbacks - Kubernetes simplifies application deployment with rollouts and rollbacks for minimal downtime.
- Self-Healing - Kubernetes has an automated system that constantly monitors the containers and restarts them in case of failure, helping deliver enhanced uptime.
- Service Discovery and Load Balancing - Kubernetes simplifies network configuration by managing internal and external container traffic routing. This means you don’t have to worry about complex network configurations, as Kubernetes takes care of them for you.
Scalability
- Horizontal Scaling - Easily scale worker nodes and Pods to match changing app load.
- Autoscaling - Automatically adjust resource allocation based on usage metrics (e.g., CPU, memory) to meet dynamic traffic demands.
Portability
- Cloud-agnostic - A standardized deployment model allows for a smoother application migration across different public clouds (AWS, Azure, Google Cloud) or hybrid setups, preventing vendor lock-in.
- Consistent Environment - Minimizes compatibility issues between development, testing and production environments, maintaining straightforward transitions and reducing errors.
Resource Efficiency
- Bin Packing - Intelligently placing Pods on nodes optimizes resource allocation, reducing the number of required machines.
- Cost Optimization - Effective cost management through resource right-sizing, scalable capabilities and diverse infrastructure options.
Common Use Cases for Kubernetes
Kubernetes is a versatile and effective tool that IT teams can use across a wide range of industries. Its primary strength lies in its ability to manage complex, distributed applications through automation, making it an ideal solution for many scenarios. Here are some common real-world use cases where Kubernetes excels:
Microservices Architecture
Organizations looking to improve scalability and agility by transitioning from monolithic to microservices architectures find Kubernetes invaluable. With microservices, different system components can be independently developed, deployed and scaled, which helps reduce development lifecycle times and improves service reliability.
For instance, many financial services companies use Kubernetes to manage their microservices architectures, which enables them to quickly update parts of their system, such as payment processing and fraud detection, without affecting other services.
Continuous Integration and Continuous Deployment (CI/CD)
The Kubernetes platform enables developers and system administrators to automate application testing, deployment and rollback. This allows for faster development and confirms that applications are highly available and reliable. Tech companies use Kubernetes to streamline their development processes, introduce new features and deploy quick and safe fixes to production environments.
DevSecOps and Agile Development
Kubernetes enables DevSecOps practices by simplifying infrastructure management, application scaling and service updates, aligning with agile development methodologies. For this reason, many organizations use Kubernetes to deliver DevSecOps practices and improve their ability to respond quickly to market changes and customer feedback.
Cloud-Native Applications
Kubernetes is ideal for managing cloud-native applications that require elasticity, resilience and portability across cloud environments. It delivers dynamic scaling, self-healing and uncomplicated updates via containers that are independent of the cloud platform in use. For instance, e-commerce platforms can use Kubernetes so that their cloud-native applications can handle variable traffic loads, especially during peak periods.
Supporting Multi-Cloud and Hybrid Cloud Strategies
Besides supporting native cloud applications on a single platform, Kubernetes also aids the multi-cloud and hybrid-cloud deployment models that many organizations prefer. It helps them avoid vendor lock-in and optimize resources across different cloud and on-premises environments.
For instance, businesses can include Kubernetes in their multi-cloud strategies to easily move workloads and applications to alternate services and take advantage of better pricing from cloud providers and retain regulatory compliance and data sovereignty.
Big Data and Machine Learning
Kubernetes is excellent for efficiently managing big data applications and machine learning workflows. It provides scalable processing and storage and can orchestrate complex data pipelines and resource-intensive computations. Many companies and research institutions use Kubernetes to manage their big data analytics and machine learning operations, which enables them to process large datasets and train models more efficiently.
Internet of Things (IoT) and Edge Computing
Kubernetes is frequently used to manage applications at the network Edge closer to IoT devices and end users using modern networking standards such as 5G and Wi-Fi 6. This helps reduce data processing latency and bandwidth usage. For example, manufacturing and logistics companies are deploying Kubernetes at the Edge to process IoT sensor data in real time to optimize operational decision-making and for predictive maintenance to reduce service disruptions.
These examples demonstrate the broad range of applications for Kubernetes, which efficiently manages complex, distributed container systems and enables digital transformation and innovation. If your applications or workloads run on a server, then they can very likely be deployed and managed via containers and Kubernetes.
Best Practices for Kubernetes Implementation
Best practices for any technology constantly evolve, so you should survey the current field of expertise when deploying a Kubernetes or any other technology solution. At the time of writing (March 2024), we can summarize Kubernetes best practices across four categories.
- Security Best Practices
- Scalability Best Practices
- Maintenance Best Practices
- Additional Best Practices
⁃ Principle of Least Privilege - Define precise permissions for users and service accounts using Role-Based Access Control (RBAC) and conduct regular audits to maintain security.
⁃ Vulnerability Scanning - It is important to conduct regular scans of container images to detect vulnerabilities. Additionally, updating base images and libraries is essential.
⁃ Secret Management - Organizations should avoid hardcoding sensitive information in configuration files. Instead, they should use dedicated tools such as Kubernetes Secrets or third-party secret store solutions to store and secure this information.
⁃ Network Policies – It is crucial to segment your cluster with namespaces and implement network policies to isolate critical components and restrict network traffic flow within it.
⁃ Pod Security Policies - To minimize risks, it is crucial to manage privileged container access, container file systems and other security-sensitive settings. This includes controlling access to sensitive features and settings within container environments, such as limiting privileged users and providing permissions for secure file systems.
⁃ Resource Requests and Limits - It is essential to set requests and limits for your containers to prevent overuse and help the scheduler make informed decisions.
⁃ Horizontal Pod Autoscaling (HPA) - Configure the Horizontal Pod Autoscaler (HPA) to scale Pods up or down automatically based on CPU or memory usage. This confirms efficient resource utilization during fluctuating loads.
⁃ Cluster Autoscaler - Cluster Autoscaler can automatically adjust the number of worker nodes in use to balance resource usage in cloud environments.
⁃ Regular Updates - Keeping your Kubernetes control plane, worker nodes and applications up to date with the latest patches for bug fixes and security updates is crucial.
⁃ Monitoring - Use monitoring tools to track cluster health, application performance and resource utilization. Set up alerts to proactively highlight any issues.
⁃ Logging - Use a centralized logging solution that captures and aggregates logs from all Kubernetes components and applications, facilitating troubleshooting and auditing efforts.
⁃ GitOps - Use version control such as Git repositories to manage your Kubernetes cluster configuration, enabling version control and audit trails for all changes made.
⁃ Backup and Disaster Recovery – A robust backup strategy is ideal for your Kubernetes state and persistent data. Regularly test your backup recovery plans to double-check its effectiveness.
⁃ Namespaces - Organize resources and improve security with namespaces and quotas.
⁃ Liveness and Readiness Probes - To properly manage container health and lifecycle in Kubernetes, be sure to define appropriate probes for your containers.
⁃ Cost Optimization - Control your cloud infrastructure costs by using spot instances (if applicable), optimizing storage choices and right-sizing resources.
Challenges and Solutions
The benefits of using Kubernetes are significant. But we can’t gloss over the challenges many organizations and DevSecOps teams encounter when they first evaluate and deploy containers managed via the platform. Users will face common challenges, but there are always solutions behind those challenges.
Kubernetes Can Be Complex
Kubernetes architecture and concepts, such as Pods and Deployments, can be a steep learning curve for some. If your team is facing this issue with Kubernetes deployment, there are a few things you can do to make it easier:
- Start small by deploying simple applications and gradually building up complexity as you gain more understanding of the process.
- Consider using managed Kubernetes services to simplify the setup and maintenance of your clusters.
- It’s essential to invest in training and get access to the best resources and documentation with examples and tutorials to help your team get up to speed with Kubernetes.
Kubernetes Changes the Security Paradigm
Securing a Kubernetes cluster requires attention to multiple layers, including image security, network policies and access controls. This may be a significant change for some people working in your team. You can counter any misapprehension by promoting and using the following security best practices:
- Implement strict role-based access controls (RBAC) for users and service accounts.
- Regularly scan container images for vulnerabilities.
- Limit Pod-to-Pod traffic using network policies.
- Control privileged container activities using Pod Security Policies.
- Conduct regular security audits and update your systems accordingly.
Increased Network Complexity
Managing networking in Kubernetes can be challenging as it involves various tasks, such as establishing communication between Pods, discovering services and controlling ingress. To solve this problem, it is important to ask if your team members understand how Kubernetes networks function and how to use them.
To become skilled in Kubernetes networking requires a good understanding of services, Pods and ingress resources. Once people have a firm grasp of these concepts, your organization is better placed to choose a networking solution that best suits your needs. Some of the third-party add-on tools for Kubernetes can reduce the network complexity that you have to deal with.
Troubleshooting Distributed Deployments
Analyzing issues in distributed systems spread across multiple nodes and containers requires a shift in troubleshooting approaches. The tools to debug issues in distributed Kubernetes deployments are good. The CLI tool kubectl is very useful when analyzing problems, as are monitoring and logging tools that provide data on the current state of deployed containers and management nodes.
Cost Management
It can be easy to let costs for using Kubernetes balloon at the start if you don’t start small and get a handle on how much storage, bandwidth and compute resources you will need on cloud platforms. Setting limits that restrict unauthorized expansion and using fine-grained cost-tracking tools can prevent the arrival of an unexpected and inflated invoice from an infrastructure provider.
Upcoming Trends in Kubernetes
Kubernetes use will continue to grow as it expands its reach beyond cloud-native applications, edge computing and artificial intelligence/machine learning into more traditional enterprise workloads. More deployment teams will take advantage of the benefits on offer when deciding how to roll out general business applications.
We can expect the broader Kubernetes ecosystem to continue to grow and evolve as more workloads move to containerized deployments and the need to manage the increasing number of containers also grows. The future looks bright and easier to manage when applications use containers that are deployed, monitored and managed via the Kubernetes platform.
Progress Kemp Ingress Controller for Kubernetes
Progress Kemp LoadMaster can help deploy a sturdy Kubernetes infrastructure. The Kemp Ingress Controller provides a straightforward method to automate endpoint configuration by directing external traffic to your Kubernetes Cluster.
With LoadMaster, you won’t have to worry about virtual services and ingress policies as it automatically provisions them through the Kubernetes API and adapts to any changes in your configuration. It routes traffic directly to the Kubernetes Pods and allows microservices containers to be managed alongside traditional monolithic applications. Additionally, it can apply advanced enterprise load balancing services like Web Application Firewall (WAF), Access Management, Global Server Load Balancing (also known as GEO) and L7 Service traffic management.
It is the simplest, most robust and scalable way to publish Kubernetes containers and monolithic applications via a single controller.
Conclusion
Kubernetes makes the use of containers manageable even when the numbers in use hit the hundreds or even thousands. If you are deploying software across multiple platforms in the cloud or on-premises, containers are the modern way to do it and Kubernetes is the way to manage those deployments.
If you haven’t delved into the world of Kubernetes (or containers, for that matter), there are plenty of places where you can try both in the cloud to see if this deployment model could enhance and simplify your application deployments. See the Kubernetes and Docker links in the reference below for jumping-off points.
Visit the Kemp Ingress Controller for Kubernetes page to learn how LoadMaster can help you deliver your containerized infrastructure via Kubernetes.
References
Kubernetes Web Site - https://kubernetes.io
Docker Web Site - https://www.docker.com
Kubernetes: Getting Started - https://kubernetes.io/docs/setup/
