Book Image

Ceph: Designing and Implementing Scalable Storage Systems

By : Michael Hackett, Vikhyat Umrao, Karan Singh, Nick Fisk, Anthony D'Atri, Vaibhav Bhembre
Book Image

Ceph: Designing and Implementing Scalable Storage Systems

By: Michael Hackett, Vikhyat Umrao, Karan Singh, Nick Fisk, Anthony D'Atri, Vaibhav Bhembre

Overview of this book

This Learning Path takes you through the basics of Ceph all the way to gaining in-depth understanding of its advanced features. You’ll gather skills to plan, deploy, and manage your Ceph cluster. After an introduction to the Ceph architecture and its core projects, you’ll be able to set up a Ceph cluster and learn how to monitor its health, improve its performance, and troubleshoot any issues. By following the step-by-step approach of this Learning Path, you’ll learn how Ceph integrates with OpenStack, Glance, Manila, Swift, and Cinder. With knowledge of federated architecture and CephFS, you’ll use Calamari and VSM to monitor the Ceph environment. In the upcoming chapters, you’ll study the key areas of Ceph, including BlueStore, erasure coding, and cache tiering. More specifically, you’ll discover what they can do for your storage system. In the concluding chapters, you will develop applications that use Librados and distributed computations with shared object classes, and see how Ceph and its supporting infrastructure can be optimized. By the end of this Learning Path, you'll have the practical knowledge of operating Ceph in a production environment. This Learning Path includes content from the following Packt products: • Ceph Cookbook by Michael Hackett, Vikhyat Umrao and Karan Singh • Mastering Ceph by Nick Fisk • Learning Ceph, Second Edition by Anthony D'Atri, Vaibhav Bhembre and Karan Singh
Table of Contents (27 chapters)
Title Page
About Packt
Contributors
Preface
Index

Uses cases


As mentioned at the start of the chapter, the tiering functionality should be thought of as tiering and not a cache. The reason behind this statement is that the act of promotions has a detrimental effect to cluster performance when compared with most caching solutions, which do normally not degrade performance if enabled on noncacheable workloads. The performance impact of promotions are caused by two main reasons. First, the promotion happens in the I/O path, the entire object to be promoted needs to be read from the base tier and then written into the top tier before the I/O is returned to the client.

Second, this promotion action will likely also cause a flush and an eviction, which cause even more reads and writes to both tiers. If both tiers are using 3x replication, this starts to cause a large amount of write amplification for even just a single promotion. In the worse case scenario, a single 4 KB access that causes a promotion could cause 8 MB of read I/O and 24 MB of...