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Third-party Kubernetes tools hone performance for database containerization

Kubernetes tools look to carve out a market niche in database containerization with performance monitoring and quality-of-service management features.

Enterprise IT shops that want to modernize legacy applications or embark on a database containerization project are the target users for Kubernetes tools released this month.

Robin Systems, which previously offered its own container orchestration utility, embraced Kubernetes with hyper-converged infrastructure software it claimed can optimize quality of service for database containerization, AI and machine learning applications, as well as big data applications, such as Spark and Hadoop. Turbonomic also furthered its Kubernetes optimization features with support for multi-cloud container management. Turbonomic's Self-Managing Kubernetes tool could also help with database containerization, because it takes performance and cost optimization into account.

The products join other third-party Kubernetes management tools that must add value over features offered natively in pure upstream Kubernetes implementations -- a difficult task as the container orchestration engine matures. However, the focus on database containerization and its performance challenges aligns with the enterprise market's momentum, analysts said.

"For many vendors, performance is an afterthought, and the monitoring and management side is an afterthought," said Milind Govekar, analyst with Gartner. "History keeps repeating itself along those lines, but now we can make mistakes faster because of automation and worse mistakes with containers, because they're easier to spin up."

While early adopters such as T-Mobile already use DC/OS for database containerization, most enterprises aren't yet ready for stateful applications in containers.

"Stateless apps are still the low-hanging fruit," said Jay Lyman, analyst with 451 Research. "It will be a slow transition for organizations pushing [containerization] into data-rich applications."

Robin Systems claims superior database containerization approach

Now, we can make mistakes faster because of automation and worse mistakes with containers, because they're easier to spin up.
Milind Govekaranalyst, Gartner

Robin Systems faces more of an uphill battle against both pure Kubernetes and established third-party tools with its focus on big data apps and database containerization. Mesosphere has already targeted this niche for years with DC/OS. And enterprises can also look to Red Hat OpenShift for database containerization, given the platform's maturity and users' familiarity with Red Hat's products.

Robin Systems' founders claimed better quality-of-service guarantees for individual containers and workloads than OpenShift and DC/OS, because the company designed and controls all levels of its software-defined infrastructure package, which includes network and storage management, in addition to container orchestration. It guarantees minimum and maximum application performance throughout the infrastructure -- including CPU, memory, and network and storage IOPS allocations -- within one policy, whereas competitors integrate with tools such as the open source Container Network Interface plug-in, OpenShift Container Storage and Portworx persistent storage.

Control over the design of the storage layer enables Robin's platform to take cluster-wide snapshots of Kubernetes deployments and their associated applications, which isn't possible natively on OpenShift or DC/OS yet.

Plenty of vendors claim a superior approach with their Kubernetes tools, and many major enterprise IT shops have already chosen a strategic Kubernetes vendor for production application development and deployment.

However, companies such as John Hancock also must modernize a massive portfolio of legacy applications, including IBM DB2 and Microsoft SQL Server databases in versions so old they're no longer supported by the original manufacturers.

John Hancock, a Boston-based insurer and a division of financial services group Manulife Financial Corp., is conducting a proof of concept with Robin Systems, as it mulls database containerization for IBM DB2. The company wants to move the mainframe-based system into the Microsoft Azure cloud for development and testing, which it sees as simpler and more affordable than its current approach to managing internally developed production apps with Pivotal's PaaS offering by a separate department.

"It's not going to fly if [a database containerization platform] will take four people eight months to get working," said Kurt Straube, systems director for the insurance company. Robin's hyper-converged infrastructure approach, which bundles networking and storage with container and compute management, might be a shortcut to database containerization for legacy apps where ease of use and low cost are paramount.

Turbonomics Kubernetes tool
Turbonomic's Kubernetes tool manages MongoDB performance.

Turbonomic targets container placement

While Robin Systems' platform approach puts it squarely into competition with PaaS vendors such as Red Hat OpenShift, Pivotal Container Service (PKS) and Mesosphere's DC/OS, Turbonomic's product spans Kubernetes platforms such as Amazon Elastic Container Service for Kubernetes, Azure Kubernetes Service, Google Kubernetes Engine and PKS.

Turbonomic's Kubernetes tool optimizes container placement across different services.* This fills a potential need in the market, and it keeps Turbonomic out of direct competition with established Kubernetes tools.

"There are many PaaS vendors that can manage Kubernetes clusters, but what they can't do is tell a user how to optimize the number of containers on a cluster so that the right resources are available to each container," Gartner's Govekar said.

A number of tools manage VM placement between multiple cloud infrastructure services, such as the Open Service Broker API. However, "many of these tools don't do a great job from a performance optimization standpoint specifically," Govekar said.

* Information updated after publication

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