Book Image

PostgreSQL High Availability Cookbook - Second Edition

By : Shaun Thomas
Book Image

PostgreSQL High Availability Cookbook - Second Edition

By: Shaun Thomas

Overview of this book

Databases are nothing without the data they store. In the event of a failure - catastrophic or otherwise - immediate recovery is essential. By carefully combining multiple servers, it’s even possible to hide the fact a failure occurred at all. From hardware selection to software stacks and horizontal scalability, this book will help you build a versatile PostgreSQL cluster that will survive crashes, resist data corruption, and grow smoothly with customer demand. It all begins with hardware selection for the skeleton of an efficient PostgreSQL database cluster. Then it’s on to preventing downtime as well as troubleshooting some real life problems that administrators commonly face. Next, we add database monitoring to the stack, using collectd, Nagios, and Graphite. And no stack is complete without replication using multiple internal and external tools, including the newly released pglogical extension. Pacemaker or Raft consensus tools are the final piece to grant the cluster the ability to heal itself. We even round off by tackling the complex problem of data scalability. This book exploits many new features introduced in PostgreSQL 9.6 to make the database more efficient and adaptive, and most importantly, keep it running.
Table of Contents (18 chapters)
Title Page
Credits
About the Author
About the Reviewer
www.Packtpub.com
Customer Feedback
Preface

Performing triage


When things go wrong or begin to look strange to an experienced eye, it is time to investigate. But where do we start?

Is the RAID running in parity mode, thereby drastically reducing the I/O throughput? Is the upstream switch saturated, robbing the database of bandwidth? Are we out of memory and swapping to disk, or are we causing memory reclamation threads to terminate processes? Has the operating system task scheduler gotten overloaded and spiraled into oblivion?

Maybe! We've seen all of these scenarios and many more. We can't fix a problem that we are unable to locate. Any time that we spend analyzing an unlikely path is ultimately wasted, and it only increases downtime. We must take an inventory of the known symptoms and extrapolate this evidence into one or more avenues of investigation.

Anything less is simply guesswork.

Getting ready

We do not need a spreadsheet for this. A computer with a network connection should be enough to quickly rule out several possibilities...