Heroku Cookbook

Heroku Cookbook

By : Mike Coutermarsh

Buy this Book

Heroku Cookbook

By: Mike Coutermarsh

Buy this Book

Overview of this book

Heroku is a Platform as a Service that enables developers to rapidly deploy and scale their web applications. Heroku is designed for developer happiness, freeing developers from doing system administrative tasks such as configuring servers and setting up load balancers. Developers are able to focus on what they do best, building web applications, while leaving the details of deployment and scaling to the experts at Heroku. This practical guide is packed with step-by-step solutions to problems faced by every production-level web application hosted on Heroku. You'll quickly get comfortable with managing your Heroku applications from the command line and then learn everything you need to know to deploy and administer production-level web applications.

Heroku Cookbook

Credits

About the Author

About the Reviewers

www.PacktPub.com

Preface

Free Chapter

Getting Started with Heroku

Introduction

Installing the Heroku Toolbelt

Introducing version control with Git

Deploying a Rails application to Heroku

Deploying a Node.js application to Heroku

Introducing dynos, workers, and scaling

Managing Heroku from the Command Line

Introduction

Viewing application logs

Searching logs

Installing add-ons

Managing environment variables

Enabling the maintenance page

Managing releases and rolling back

Running one-off tasks and dynos

Managing SSH keys

Sharing and collaboration

Monitoring load average and memory usage

Setting Up a Staging Environment

Introduction

Duplicating an existing application

Managing git remotes

Password protection for a Rails app

Deploying with Heroku labs – Pipeline

Deploying from tags

Continuous integration and deployment with Travis CI

Production-ready with Heroku

Introduction

Managing domains from the command line

Configuring DNS with CloudFlare

Setting up SSL with CloudFlare

Enabling preboot for seamless deploys

Enabling custom maintenance and error pages

Setting up a status page

Setting up log draining with LogEntries

Error Monitoring and Logging Tools

Introduction

Checking Heroku's status

Adjusting Rails's logging level

Storing historical logs with PaperTrail

Monitoring for 404 and 500 errors with PaperTrail

Logging slow queries with PaperTrail

Monitoring uptime with Pingdom

Logging errors with Rollbar

Load Testing a Heroku Application

Introduction

Monitoring dyno performance with Librato

Monitoring application performance with New Relic

Learning to load test with Siege

Configuring complex load tests with Siege

Load testing from the cloud with Blitz.io

Testing real-user scenarios with Load Impact

Optimizing Ruby Server Performance on Heroku

Introduction

Setting up and running Unicorn on Heroku

Monitoring and tuning Unicorn's memory usage

Tuning Unicorn's backlog for Heroku

Timing out long requests with Unicorn

Setting up and running Puma on Heroku

Running Puma with Rubinius for parallelism

Optimizing a Rails Application on Heroku

Introduction

Setting up a sample blogging app

Using Heroku Deflater to gzip assets

Serving assets from Amazon Web Services (AWS) Cloudfront

Adding memcached to a Rails application

Adding Redis to a Rails application

Implementing low-level caching in Rails

Caching rendered views

Aborting long requests with Rack::Timeout

Using a follower for read-only DB queries

Using and Administrating Heroku Postgres

Introduction

Creating and sizing a new database

Promoting a Heroku database

Connecting to Heroku Postgres from Navicat

Connecting to Heroku Postgres from psql

Creating a database backup

Restoring from a backup

Creating a read-only follower

Viewing and stopping database processes

Analyzing Heroku Postgres's performance

The Heroku Platform API

Introduction

Making our first API request with HTTPie

Getting started with the Platform API gem

Scaling dynos and workers

Managing configuration variables

Adding and removing collaborators

Creating new Heroku applications

Index

Customer Reviews

5 star

4 star

3 star

2 star

1 star

Monitoring and tuning Unicorn's memory usage

Our main constraint when running multiple Unicorn workers is the memory available on the dyno. A typical application will use somewhere between 50 and 200 MB of memory per process. We want to configure our application to use between 50 to 70 percent of the available memory on a dyno. This gives our processes room to grow while still using most of the resources we are paying for.

In this recipe, we will be learning how to determine how much memory our application uses per Unicorn process. We will then be tweaking our configuration to maximize concurrency within a single dyno.

Note

We want to avoid running too close to 100 percent memory usage. If we run out of memory, our dyno will start using swap. This should be avoided at all costs. Using any swap will greatly decrease the performance of the dyno and response times will skyrocket.

How to do it…

To get started, let's open up a terminal and navigate to the directory with our Unicorn application using...

Heroku Cookbook

By : Mike Coutermarsh

Heroku Cookbook

By: Mike Coutermarsh

Overview of this book

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Heroku Cookbook

Monitoring and tuning Unicorn's memory usage

Note

How to do it…