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If you intend to use Amazon Web Services (AWS) for remote computing and storage, Python is an ideal programming language for developing applications and controlling your cloud-based infrastructure. This cookbook gets you started with more than two dozen recipes for using Python with AWS, based on the author’s boto library.
You’ll find detailed recipes for working with the S3 storage service as well as EC2, the service that lets you design and build cloud applications. Each recipe includes a code solution you can use immediately, along with a discussion of why and how the recipe works. You also get detailed advice for using boto with AWS and other cloud services.
This book’s recipes include methods to help you:
* Launch instances on EC2, and keep track of them with tags
* Associate an Elastic IP address with an instance
* Restore a failed Elastic Block Store volume from a snapshot
* Store and monitor your own custom metrics in CloudWatch
* Create a bucket in S3 to contain your data objects
* Reduce the cost of storing noncritical data
* Prevent accidental deletion of data in S3
List of contents
Preface;
Conventions Used in This Book;
Using Code Examples;
Safari® Books Online;
How to Contact Us;
Chapter 1: General Info;
1.1 A Quick Note About Python;
1.2 Installing boto;
1.3 Getting Started with Amazon Web Services;
1.4 Using boto with Eucalyptus;
1.5 Using boto with Google Cloud Storage;
1.6 Finding Available Regions for AWS;
1.7 Enabling Debug Output with boto;
1.8 Controlling Socket Timeouts in boto;
Chapter 2: EC2 Recipes;
2.1 Launching an Instance;
2.2 Keeping Track of Instances with Tags;
2.3 Accessing the Console Log;
2.4 Uploading Your Own SSH Keypair;
2.5 Synchronizing SSH Keypairs Across EC2 Regions;
2.6 Associate an Elastic IP Address with an Instance;
2.7 Attach a Persistent EBS Volume to an Instance;
2.8 Back Up Your EBS Volumes;
2.9 Restore a Volume from a Snapshot;
2.10 Clone an Existing Instance;
2.11 Find All Running EC2 Instances;
2.12 Monitoring the Performance of Your Instance;
2.13 Getting Notifications;
2.14 Storing Custom Data in CloudWatch;
2.15 Executing Custom Scripts upon Instance Startup;
Chapter 3: S3 Recipes;
3.1 Create a Bucket;
3.2 Create a Bucket in a Specific Location;
3.3 Store Private Data;
3.4 Store Metadata with an Object;
3.5 Computing Total Storage Used by a Bucket;
3.6 Copy an Existing Object to Another Bucket;
3.7 Modify the Metadata of an Existing Object;
3.8 Find Out Who Is Accessing Your Data;
3.9 Reduce the Cost of Storing Noncritical Data;
3.10 Generating Expiring URLs for S3 Objects;
3.11 Preventing Accidental Deletion of Data from S3;
3.12 Hosting Static Websites on S3;
3.13 Uploading Large Objects to S3;
About the author
Mitch Garnaat is a software developer at Eucalyptus Systems where he is responsible for the development of tools to make it easier to create and manage cloud computing resources. Previously, as a Principal Engineer at Xerox PARC he was the co-inventor and lead developer of DocuShare, a web-based document management product from Xerox. He is the creator of boto, an open source Python library for cloud computing.
Summary
If you intend to use Amazon Web Services (AWS) for remote computing and storage, Python is an ideal programming language for developing applications and controlling your cloud-based infrastructure. This cookbook gets you started with more than two dozen recipes for using Python with AWS, based on the author's boto library.
