Book Image

The DevOps 2.2 Toolkit

By : Viktor Farcic
Book Image

The DevOps 2.2 Toolkit

By: Viktor Farcic

Overview of this book

Building on The DevOps 2.0 Toolkit and The DevOps 2.1 Toolkit: Docker Swarm, Viktor Farcic brings his latest exploration of the Docker technology as he records his journey to explore two new programs, self-adaptive and self-healing systems within Docker. The DevOps 2.2 Toolkit: Self-Sufficient Docker Clusters is the latest book in Viktor Farcic’s series that helps you build a full DevOps Toolkit. This book in the series looks at Docker, the tool designed to make it easier in the creation and running of applications using containers. In this latest entry, Viktor combines theory with a hands-on approach to guide you through the process of creating self-adaptive and self-healing systems. Within this book, Viktor will cover a wide-range of emerging topics, including what exactly self-adaptive and self-healing systems are, how to choose a solution for metrics storage and query, the creation of cluster-wide alerts and what a successful self-sufficient system blueprint looks like. Work with Viktor and dive into the creation of self-adaptive and self-healing systems within Docker.

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Table of Contents (18 chapters)
Preface
Preface
Overview
Get in touch
Free Chapter
1
Introduction to Self-Adapting and Self-Healing Systems
Introduction to Self-Adapting and Self-Healing Systems
What is a self-adaptive system?
What is a self-healing system?
What now?
2
Choosing a Solution for Metrics Storage and Query
Choosing a Solution for Metrics Storage and Query
Non-dimensional versus dimensional metrics
What now?
3
Deploying and Configuring Prometheus
Deploying and Configuring Prometheus
Deploying Prometheus stack
Designing a more dynamic monitoring solution
Deploying Docker Flow Monitor
Integrating Docker Flow Monitor with Docker Flow Proxy
What now?
4
Scraping Metrics
Scraping Metrics
Creating the cluster and deploying services
Deploying exporters
Exploring exporter metrics
Querying metrics
Updating service constraints
Using memory reservations and limits in Prometheus
What now?
5
Defining Cluster-Wide Alerts
Defining Cluster-Wide Alerts
Creating the cluster and deploying services
Creating alerts based on metrics
Defining multiple alerts for a service
Postponing alerts firing
Defining additional alert information through labels and annotations
Using shortcuts to define alerts
What now?
6
Alerting Humans
Alerting Humans
Creating the cluster and deploying services
Setting up Alertmanager
Using templates in Alertmanager configuration
What now?
7
Alerting the System
Alerting the System
The four quadrants of a dynamic and self-sufficient system
8
Self-Healing Applied to Services
Self-Healing Applied to Services
Creating the cluster and deploying services
Using Docker Swarm for self-healing services
Is it enough to have self-healing applied to services?
What now?
9
Self-Adaptation Applied to Services
Self-Adaptation Applied to Services
Choosing the tool for scaling
Creating the cluster and deploying services
Preparing the system for alerts
Creating a scaling pipeline
Preventing the scaling disaster
Notifying humans that scaling failed
Integrating Alertmanager with Jenkins
What now
10
Painting the Big Picture – The Self-Sufficient System Thus Far
Painting the Big Picture – The Self-Sufficient System Thus Far
Developer's role in the system
Continuous deployment role in the system
Service configuration role in the system
Proxy role in the system
Metrics role in the system
Alerting role in the system
Scheduler role in the system
Cluster role in the system
What now?
11
Instrumenting Services
Instrumenting Services
Defining requirements behind service specific metrics
Differentiating services based on their types
Choosing instrumentation type
Creating the cluster and deploying services
Instrumenting services using counter
Instrumenting services using gauges
Instrumenting services using histograms and summaries
What now?
12
Self-Adaptation Applied to Instrumented Services
Self-Adaptation Applied to Instrumented Services
Setting up the objectives
Creating the cluster and deploying services
Scraping metrics from instrumented services
Querying metrics from instrumented services
Firing alerts based on instrumented metrics
Scaling services automatically
Sending error notifications to slack
What now?
13
Setting Up a Production Cluster
Setting Up a Production Cluster
Creating a Docker for AWS cluster
Deploying services
Securing services
Persisting state
Alternatives to CloudStor volume driver
Setting up centralized logging
Extending the capacity of the cluster
What now?
14
Self-Healing Applied to Infrastructure
Self-Healing Applied to Infrastructure
Automating cluster setup
Exploring fault tolerance
What now?
15
Self-Adaptation Applied to Infrastructure
Self-Adaptation Applied to Infrastructure
Creating a cluster
Scaling nodes manually
Creating scaling job
Scaling cluster nodes automatically
Rescheduling services after scaling nodes
Scaling nodes when replica state is pending
What now?
16
Blueprint of a Self-Sufficient System
Blueprint of a Self-Sufficient System
Service tasks
Infrastructure tasks
Logic matters, tools might vary
What now?
17
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Creating a Docker for AWS cluster

In the book, The DevOps 2.1 Toolkit: Docker Swarm (https://www.amazon.com/dp/1542468914), I argued that the best way to create a Swarm cluster in AWS is with a combination of Packer (https://www.packer.io/) and Terraform (https://www.terraform.io/). One of the alternatives was to use Docker CE for AWS (https://store.docker.com/editions/community/docker-ce-aws). At that time Docker for AWS was too immature. Today, the situation is different. Docker for AWS provides a robust Docker Swarm cluster with most, if not all the services we would expect from it.

We'll create a Docker for AWS cluster and, while in progress, discuss some of its aspects.

Before we start creating a cluster, we should choose a region. The only thing that truly matters is whether a region of your choice supports at least three Availability Zones (AZ). If there's only...

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