Red Hat Gluster Storage

Improving rsync performance with GlusterFS

Improving rsync performance with GlusterFS

Rsync is a particularly tough workload for GlusterFS because with its defaults, it exercises some of the worst case operations for GlusterFS. GlusterFS is the core of Red Hat Gluster’s scale-out storage solution. Gluster is an open, software-defined storage (SDS) platform that is designed to scale out to handle data intensive tasks across many servers in physical, virtual, or cloud deployments. Since GlusterFS is a POSIX compatible distributed file system, getting the best performance from rsync requires some tuning/tweaking on both sides.

In this post, I will go through some of the pain points and the different tunables for working around the pain points.  Getting rsync to run as fast on GlusterFS as it would on a local file system is not really feasible given its architecture, but below I describe how to get as close as possible.

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Example of using Ansible to update Container Native Storage

Example of using Ansible to update Container Native Storage

Container Native Storage (CNS) is implemented in OpenShift as pods. These pods are created from a template that is built into OpenShift. After an automated install, we want to make sure we have the latest template, and the latest containers when using the Advanced Installer. While typically this is a multi-step manual process, an Ansible Script makes this a lot simpler.

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Monitoring RHGS

Monitoring RHGS

OK so you watched:

https://www.redhat.com/en/about/videos/architecting-and-performance-tuning-efficient-gluster-storage-pools

You put in the time and architected an efficient and performant GlusterFS deployment. Your users are reading and writing, applications are humming along, and Gluster is keeping your data safe.

Now what?

Well, congratulations you just completed the sprint! Now its time for the marathon.

The often forgotten component of performance tuning is monitoring, you put in all that work up front to get your cluster performing and your users happy, now how do you ensure that this continues and possibly improves? This is all done through continued monitoring and profiling of your storage cluster, clients, and a deeper look at your workload. In this blog we will look at the different metrics you can monitor in your storage cluster, identify which of these are important to monitor, how often to monitor them, and different ways to accomplish this.

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