What is Kubernetes Containerization?
Kubernetes containerization is the utilization of the Kubernetes open source tool to automate the deployment, scaling, and management of containers without launching virtual machines for any applications.
What is a Kubernetes container?
A Kubernetes container is a self-contained package that hosts everything needed to run an application (code, files, application and system libraries, etc.) and is developed to function like a ready-to-run software package. It runs an application with the same behavior every time because it has no dependencies and is self-sufficient. Containers are also independent from underlying host infrastructure, making them easier to deploy in different cloud or OS environments.
How does Kubernetes containerization work?
To containerize an application, you must create an abstraction away from any hardware/infrastructure, defining a single image of the software and any dependencies and packaging it all together in one unit. The next step involves orchestrating those containers, arranging them, and scheduling them to optimize resource utilization. Using Kubernetes to manage your containers allows you to automatically fix problems as they crop up, with self-healing, automated rollouts, and rollbacks to accelerate the process of fixing and repairing applications.
What are the advantages of using Kubernetes containerization?
By allowing Kubernetes to manage container orchestration, tech teams can spend less time dealing with infrastructure and configuration and instead focus on developing the products and services customers need. Specific advantages include:
- Speed: With a shared operating system kernel already in the container, there’s no need to boot up every time you run an application, allowing DevOps to build applications faster.
- Simplicity: With a minimalist architecture for each container, a Kubernetes environment simplifies sharing, deployment, updating, testing, and scaling of what are essentially microservices within the containers—leading to easier application building and hybrid cloud enablement.
- Efficiency: Because containers are lightweight and discrete, multiple workloads can run on just one server, allowing resources to be consolidated and requiring fewer dedicated staff.
- Flexibility: Because containers operate independently, they enable easier movement of workloads than traditional workload management, facilitating the transfer of data between platforms, clouds, or at the edge.
- Innovation: Due to Kubernetes’ quarterly schedule of updates, organizations that utilize Kubernetes containerization for their workload management stay on the cutting edge with the latest releases.
Key Kubernetes containerization considerations
While Kubernetes containerization can bring a new level of agility to your organization, there are a few important things to consider, including:
Your IT staff will need a fairly high level of knowledge and experience to handle the complexity of application container orchestration and automation.
Running Kubernetes clusters can quickly rack up high compute and storage costs. Cloud users should assess the amount of money needed for migration and evaluate the value of those costs for container support.
Container nodes can generate a huge volume of telemetry data which requires an entirely different set of tools and management capabilities, including a more complex support ticketing system.
Lack of clear insight
When you abstract from hardware and run hundreds of containers at a time, you run the risk that you won’t see failures immediately and/or have difficulty diagnosing where the problem originated.
Container platforms may have back doors or vulnerabilities that you can’t easily see or control. If you use third-party container images within your system, those also might not have the level of security configuration you need.
HPE and Kubernetes containers
HPE is an industry leader in helping organizations modernize and run containers at scale, whether on-premises, in the cloud, or at the edge. It is a long-time contributor to the open source ecosystem and continues to be actively engaged in the Cloud Native Computing Foundation and Kubernetes communities. Our solutions enable customers to deploy containerized applications for data-intensive workloads such as AI, machine learning, and data analytics, using multiple large-scale Kubernetes clusters running in production of any chosen architecture, including multi-tenant hybrid cloud architecture.
HPE Ezmeral Runtime Enterprise, a hybrid native enterprise grade container orchestration platform built on open-source Kubernetes, allows organizations to use containers across the enterprise—even for applications with monolithic architecture and persistent data storage. With this platform, enterprises can run both cloud-native and non-cloud-native applications using 100 percent open source Kubernetes. By accommodating different deployment models, this platform supports any cloud strategy while ensuring enterprise-class security and reliability.
You can also consume containers as a service with HPE GreenLake in a pay-per-use model in order to get started quickly, scale up or down as needed, and pay only for what you use. Without high up-front expenditures and costly overprovisioning, you can reduce expenses while gaining the efficiency and agility of containers. And since the container platform is managed for you, your developers and IT staff are freed up to focus on more critical tasks within your business operations.