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Implementing Cloud Design Patterns for AWS

You're reading from   Implementing Cloud Design Patterns for AWS Create highly efficient design patterns for scalability, redundancy, and high availability in the AWS Cloud

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Product type Paperback
Published in Apr 2015
Last Updated in Feb 2025
Publisher
ISBN-13 9781782177340
Length 228 pages
Edition 1st Edition
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 Young Young
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Young
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Table of Contents (13) Chapters Close

Preface 1. Introduction FREE CHAPTER 2. Basic Patterns 3. Patterns for High Availability 4. Patterns for Processing Static Data 5. Patterns for Processing Dynamic Data 6. Patterns for Uploading Data 7. Patterns for Databases 8. Patterns for Data Processing 9. Patterns for Operation and Maintenance 10. Patterns for Networking 11. Throw-away Environments Index

Web storage archive pattern


The next pattern will aim at a smaller subset of archival as compared to the previous monitoring integration pattern. While the previous pattern was a more theoretical approach to the larger aggregation and archival schema, sometimes it is relevant to only archive certain files. One choice might be to dump the database to the filesystem. This may not be the best choice for all use cases but it is still a common approach.

A much more common practice is to rotate files, such as logs, out of the server and into a permanent store as they grow over time. There are plenty of ways to do this, such as remote syslog, or some log services such as Loggly or Logstash. It is such a common practice that there are literally hundreds of third-party solutions to choose from.

To demonstrate this, we will use logrotate which is included in nearly every major Linux distribution. Logrotate will handle the file rotation, compression, and synchronization with Amazon S3. The configuration...

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