Book Image

Implementing DevOps on AWS

By : Vaselin Kantsev
Book Image

Implementing DevOps on AWS

By: Vaselin Kantsev

Overview of this book

Knowing how to adopt DevOps in your organization is becoming an increasingly important skill for developers, whether you work for a start-up, an SMB, or an enterprise. This book will help you to drastically reduce the amount of time spent on development and increase the reliability of your software deployments on AWS using popular DevOps methods of automation. To start, you will get familiar with the concept of IaC and will learn to design, deploy, and maintain AWS infrastructure. Further on, you’ll see how to design and deploy a Continuous Integration platform on AWS using either open source or AWS provided tools/services. Following on from the delivery part of the process, you will learn how to deploy a newly created, tested, and verified artefact to the AWS infrastructure without manual intervention. You will then find out what to consider in order to make the implementation of Configuration Management easier and more effective. Toward the end of the book, you will learn some tricks and tips to optimize and secure your AWS environment. By the end of the book, you will have mastered the art of implementing DevOps practices onto AWS.
Table of Contents (17 chapters)
Implementing DevOps on AWS
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface
Free Chapter
1
What is DevOps and Should You Care?
4
Build, Test, and Release Faster with Continuous Integration

Metrics


For ingesting, storing and alerting on our metrics, we shall explore another, quite popular open-source project called Prometheus:

 

Prometheus is an open-source systems monitoring and alerting toolkit originally built at SoundCloud.

Prometheus's main features are:

-a multi-dimensional data model (time series identified by metric name and key/value pairs)

- a flexible query language to leverage this dimensionality

- no reliance on distributed storage; single server nodes are autonomous

- time series collection happens via a pull model over HTTP

- pushing time series is supported via an intermediary gateway

- targets are discovered via service discovery or static configuration

- multiple modes of graphing and dashboarding support

 
 --https://prometheus.io/docs/introduction/overview/emphasis>

Even though it is the kind of system that takes care of pretty much everything, the project still follows the popular UNIX philosophy of modular development. Prometheus is composed of multiple components...