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

Example applications and the benefits of using RADOS classes


As mentioned earlier, with RADOS classes, code is executed directly inside the OSD code base and so can harness the combined power of all of the OSD nodes. With a typical client application approach, where the client would have to read the object from the Ceph cluster, run computations on it, and then write it back, there is a large amount of round trip overheads. Using RADOS classes dramatically reduces the amount of round trips to and from OSDs, and also the available compute power is much higher than that single client could provide. Offloading operations directly to the OSDs therefore enables a single client to dramatically increase its processing rate.

A simple example of where RADOS classes could be used is where you need to calculate a hash of every object in a RADOS pool and store each objects hash as an attribute. Having a client perform this would highlight the bottlenecks and extra latency introduced by having the client...