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Effectively manage containers and improve workload performance

Containers are increasingly popular, so it's vital that admins understand the tools available and learn how to manage containers before deploying them in production environments.

Container technology gives IT administrators the ability to increase efficiency in their virtual environments. With container management tools and best practices, admins can monitor application workloads, and they can also decrease cost and labor for their organizations.

Before implementing container management software, admins should take a close look at what features vendors offer and consider how this technology will affect job roles. Though container management tools offer many benefits, they can also pose challenges. 

Important container management features

Admins must explore their options before deciding which container management software to implement in their environments. When evaluating different products, admins should deliberate on specific features and functionality such as container creation, role-based access control and virtual network and application management.

The ability to manage a virtual network is especially important because containers act independently of one another. If an admin wants two containers to communicate, that admin must establish a network path between the two, which is difficult if the software doesn't already have this capability.

Pros and cons of container management software

Containers are popular among admins because of their ability to enable application portability, but just as the benefits are apparent, so too are the disadvantages. Different container management tools, such as Kubernetes, Rancher, Portainer and Kitematic, all offer distinct capabilities, but they have their drawbacks.

For example, Kubernetes is widely known and used among admins because of its ability to assist with load balancing and resource throttling. But its most evident disadvantage is a steep learning curve. Also, by adding other products on top of existing container management software, admins might experience reduced performance due to increased queries.

Tools to manage Windows and Hyper-V containers

Tools such as Docker CLI, Windows PowerShell, RunHCS and third party GUI-based services can help admins maintain and manage containers.

Docker CLI is often the go-to tool for admins managing Windows container tasks, especially if they are already familiar with Linux Docker command-line tools. Docker CLI also works with PowerShell. PowerShell offers very similar commands and removes the added complexity found in Docker, enabling admins to easily write a container script and run it as needed.

If admins are looking for a third-party GUI alternative, Windows Server Container Manager is a viable option for container management.

Hyper-V container and VM management best practices

Admins with little or no container experience should test them in a lab environment before deploying them in production.

Admins must also understand management best practices to avoid potential mistakes and prioritize their time efficiently. Although container and VM management software operate independently of one another, they both still rely on a primary host.

Admins with little or no container experience should test them in a lab environment before deploying them in production. Once admins have an understanding of containers, they can explore different container and VM management software options. For VMs, many admins prefer a GUI-based management tool, such as System Center Virtual Machine Manager. Admins can also manage containers through the use of a GUI-based tool, such as Datadog. Admins who prefer an open source platform for their container management needs should look at the Docker Monitoring Project.

Container implementation changes job roles

With a new focus on containers, technicians are beginning to see less emphasis on infrastructure configuration and more on container skills. Because container management tools offer technicians a means to create, manage and maintain workloads with little hands-on interference, they might not have as much granular control over system configurations as they had before.

In place of that work, admins will appoint their technicians to focus more on a data analyst role, for example. This is because much of the tasks technicians were given, such as configuration, monitoring and remediation, are being executed by containers and orchestration tools.

As a result, AI and machine learning are becoming more prevalent in data centers, meaning the need for expertise on traditional server virtualization software is decreasing.

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