By Lionel Gibbons | September 29, 2017 | Linux Cluster
There are plenty of options for building a Linux cluster, including commercial and open-source software. Of course, there are limitations to the support an open-source community can provide, and not all commercial solutions are up to the task. Many claim that building clusters can be reduced to just a few steps—is that true? With the wide range of requirements, design options, and components that come into play, simplicity is an elusive goal in the real world.
The truth is that when it comes to outstanding cluster design, the devil is in the details, starting with a thorough understanding of the applications, objectives, and constraints. The design process is further complicated by the maze of options available for components used in the design. Consequently, developing a solution that meets your exacting needs can be a real challenge. Even the simplest clusters use a sophisticated mix of technologies, and getting the balance right is both critical and fraught with risk.
Let’s take a look at some of the broad areas of concern that you’ll need to consider when building, managing, and monitoring a Linux cluster from scratch.
With so many options in industry-standard hardware, making the right choice for an ideal cluster configuration is not just a matter of balancing performance and economy. How you plan to use the cluster determines the makeup of each node and the hardware configuration choices. Matching hardware that delivers optimal performance while still delivering the economy of off-the-shelf components is wholly dependent on testing and validation, which can be challenging in its own right.
Choosing the right CPUs, network interfaces, memory, and storage is important, but the GPU may be among the most critical aspects to get right when designing a cluster.
From connection and communication errors with the ricci agent software and the LuCI web interface to the node optimization problems with both bare metal and virtual servers, all but the most experienced administrators will be spending a great deal of time hunting down each problem. Even when you know what you’re doing, it can take a great deal of time to configure and fine-tune a GPU-based Linux cluster.
Cluster problems, by their nature, can be difficult to troubleshoot because of their complexity. While some of the more common challenges of integration are easy to deal with, others are not. For example, cluster administration toolkits often lack the integration frameworks for hardware management, which can leave administrators dealing with the increased cost, time, and potential errors introduced by writing their own integration scripts.
Using standard Linux command line tools to propagate changes to cluster configurations can prove challenging. Having tools designed specifically for managing clusters can simplify the process and make it more transparent, reducing the need for highly experienced administrators with a great deal of Linux expertise.
It can be difficult to ensure that file system partitioning, storage, memory, network, and power configurations match what is used for other nodes on the cluster when adding new servers. Even a small difference can create challenges with cluster discovery.
There can be myriad reasons why the head node cannot connect to cluster nodes. While there are tools for managing such problems, they are often very complex and difficult to use.
With any data center that incorporates clustered infrastructure, there are countless considerations to deal with. It can be an ongoing struggle to stay one step ahead of performance and user challenges. An effective management solution can reduce the effort involved in deploying, configuring, monitoring, and managing all of the servers in your clusters. Cluster management plays a particularly important role when setting up a large cluster with tens or even hundreds of servers. Here automated provisioning is more than a luxury—it’s a necessity.
Because most IT personnel are generalists rather than specialists, you may not have the cluster expertise on staff to handle the challenges of cluster build and management. This is even likelier when it comes to your organization’s hybrid cloud setup, which brings its own challenges.
Having access to a cluster management solution enables you to automate the build, configuration, monitoring, and management of your clusters to ensure that everything is operating the way it should.
Balancing resources between an on-premises, private cloud and the public cloud requires complex decisions about reliability and security, as well as sophisticated cluster configuration and management. Consequently, a cluster management solution that incorporates a management stack can facilitate a dynamic data center that is flexible, agile, and cost-effective. As a bonus, using a good cluster manager saves time and money and reduces errors by making the processes simple, fast, and error-free.