Book Image

Mastering Ceph - Second Edition

By : Nick Fisk
Book Image

Mastering Ceph - Second Edition

By: Nick Fisk

Overview of this book

Ceph is an open source distributed storage system that is scalable to Exabyte deployments. This second edition of Mastering Ceph takes you a step closer to becoming an expert on Ceph. You’ll get started by understanding the design goals and planning steps that should be undertaken to ensure successful deployments. In the next sections, you’ll be guided through setting up and deploying the Ceph cluster with the help of orchestration tools. This will allow you to witness Ceph’s scalability, erasure coding (data protective) mechanism, and automated data backup features on multiple servers. You’ll then discover more about the key areas of Ceph including BlueStore, erasure coding and cache tiering with the help of examples. Next, you’ll also learn some of the ways to export Ceph into non-native environments and understand some of the pitfalls that you may encounter. The book features a section on tuning that will take you through the process of optimizing both Ceph and its supporting infrastructure. You’ll also learn to develop applications, which use Librados and distributed computations with shared object classes. Toward the concluding chapters, you’ll learn to troubleshoot issues and handle various scenarios where Ceph is not likely to recover on its own. By the end of this book, you’ll be able to master storage management with Ceph and generate solutions for managing your infrastructure.
Table of Contents (18 chapters)
Free Chapter
1
Section 1: Planning And Deployment
6
Section 2: Operating and Tuning
13
Section 3: Troubleshooting and Recovery

Benchmarking

Benchmarking is an important tool to quickly be able to see the effects of your tuning efforts and to determine the limits of what your cluster is capable of. However, it's important that your benchmarks reflect the type of workload that you would be running normally on your Ceph cluster. It is pointless to tune your Ceph cluster to excel in large-block sequential reads and writes if your final intention is to run highly-latency sensitive Online Transaction Processing (OLTP) databases on it. If possible, you should try to include some benchmarks that actually use the same software as your real-life workload. Again, in the example of the OLTP database, look to see whether there are benchmarks for your database software, which will give the most accurate results.

Benchmarking...