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Cloud container technology is dominating the cloud market as an alternative to conventional hypervisor-based virtualization. Containers are lightweight and offer enhanced portability, allowing applications to move between platforms without developers having to rework or rearchitect apps. But while their benefits have wowed developers, containers still present challenges, such as scalability and management.
The demand for containers has enterprises rolling out various cloud container services. With so many choices on the market, it is hard to decide which container platforms or tools to use. Before you look at options for cloud container technologies, you have to determine if containers are even worth your business' time. These four cloud container tips can help you sort out your options.
Determine if cloud container technology is right for you
Container technology is a fast-growing IT trend, but that doesn't mean it is right for your organization. Containers provide an alternative to server virtualization. However, because containers depend on a single operating system -- and must move to servers with compatible OS kernels -- migrating them poses more of a challenge than migrating traditional virtual machines (VMs).
On the other hand, running on a single OS lowers costs and boosts performance. Containers also remove redundant resources that virtual instances need, which can improve performance. With containers' lightweight design, a server can host more containers and take advantage of their scalability.
If you don't want to choose between containers and hypervisor-based VMs, both options can be used at the same time to tackle specific needs.
Choosing the best cloud container platform
Docker has brought cloud containers into the spotlight. However, before jumping right into the container game, you have to decide what cloud container platform to use. Each container and the applications within it shares the kernel of the host OS. When choosing a platform, consider your server's OS and determine which container platforms will work with it.
Choosing a cloud container platform can be difficult because they function similarly. While you are shopping around, take note of what you need from a container. Compare and evaluate features, such as virtualization capabilities, network isolation and root privilege isolation. Pay attention to resource management features that manage and monitor processor, memory, I/O and storage limits. Once the platform meets your enterprise's specific criteria, evaluate licensing models and costs.
Tools to scale, orchestrate cloud container technology
While cloud container technology is hailed as the new way to run applications, challenges still exist. Scalability remains one of the top struggles. To help deal with scalability issues, you can use certain methods and tools, such as Docker Swarm and Google Kubernetes.
Container orchestration tools mange how container services interact, which can help to improve their scalability. Orchestration tools allow cloud containers to run in clusters, and boost scalability during times of increased workloads. Docker Swarm and Google Kubernetes are two popular container orchestration tools that focus on cluster management and scheduling.
Instead of using third-party orchestration tools, organizations can create a custom container management system. Using automated testing tools, focusing on container security and governance and examining the architecture of container-based applications can also help improve container scalability.
Container monitoring requires a new breed of IT tool
Enterprise IT must use specialized monitoring tools for cloud containers, especially to understand relationships between individual containers. With the large size and scope of many containerized environments, monitoring tools are critical for success.
Docker metrics can tell a developer if a service is up or down, but it does not judge whether application performance is up to snuff. The complexity of containerized environments calls for specialized monitoring tools such as Ruxit, which can understand repetitive behaviors and usage patterns, and Datadog, which can see relationships between a database table scan, Web server connections and cache hits.
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