Automation and tools

As discussed previously, automation is the best way to achieve rapid software delivery. It solves the issue of managing microservices. However, automation tools aren't ordinary IT or infrastructure applications such as Active Directory, BIND (DNS), or Sendmail (MTA). In order to achieve automation, we need an engineer who should have both a developer skill set to write code, particularly in scripting languages, and an infrastructure operator skill set with knowledge related to VMs, networks, and storage operations.

DevOps is short for development and operations. It refers to the ability to make automation processes such as CI, infrastructure as code, and CD. It uses some DevOps tools for these automation processes.

Continuous integration tools

One of the popular VCS tools is Git (https://git-scm.com). A developer uses Git to check-in and check-out code all the time. There are various hosting Git services, including GitHub (https://github.com) and Bitbucket (https://bitbucket.org). These allow you to create and save your Git repositories and collaborate with other users over the internet. The following screenshot shows a sample pull request on GitHub:

The build server has a lot of variation. Jenkins (https://jenkins.io) is one of the most well established applications, along with TeamCity (https://www.jetbrains.com/teamcity/). As well as build servers, you also have hosted services, otherwise known as Software as a Service (SaaS), such as Codeship (https://codeship.com) and Travis CI (https://travis-ci.org). SaaS can integrate with other SaaS tools. The build server is capable of invoking external commands, such as unit test programs. This makes the build server a key tool within the CI pipeline.

The following screenshot shows a sample build using Codeship. We check out the code from GitHub and invoke Maven for building (mvn compile) and unit testing (mvn test) our sample application:

Configuration management tools

There are a variety of configuration management tools available. The most popular ones include Puppet (https://puppet.com), Chef (https://www.chef.io), and Ansible (https://www.ansible.com).

AWS OpsWorks (https://aws.amazon.com/opsworks/) provides a managed Chef platform on AWS Cloud. The following screenshot shows a Chef recipe (configuration) of an installation of the Amazon CloudWatch Log agent using AWS OpsWorks. AWS OpsWorks automates the installation of the CloudWatch Log agent when launching an EC2 instance:

AWS CloudFormation (https://aws.amazon.com/cloudformation/) helps to achieve infrastructure as code. It supports the automation of AWS operations, so that we can perform the following functions:

• Creating a VPC
• Creating a subnet on VPC
• Creating an internet gateway on VPC
• Creating a routing table to associate a subnet to the internet gateway
• Creating a security group
• Creating a VM instance
• Associating a security group to a VM instance

The configuration of CloudFormation is written by JSON, as shown in the following screenshot:

CloudFormation supports parameterizing, so it's easy to create an additional environment with different parameters (such as VPC and CIDR) using a JSON file with the same configuration. It also supports the update operation. If we need to change a part of the infrastructure, there's no need to recreate the whole thing. CloudFormation can identify a delta of configuration and perform only the necessary infrastructure operations on your behalf.

AWS CodeDeploy (https://aws.amazon.com/codedeploy/) is another useful automation tool that focuses on software deployment. It allows the user to define the deployment steps. You can carry out the following actions on the YAML file:

• Specify where to download and install the application
• Specify how to stop the application
• Specify how to install the application
• Specify how to start and configure an application

The following screenshot is an example of the AWS CodeDeploy configuration file, appspec.yml:

Monitoring and logging tools

Once you start to manage microservices using a cloud infrastructure, there are various monitoring tools that can help you to manage your servers.

Amazon CloudWatch is the built-in monitoring tool for AWS. No agent installation is needed; it automatically gathers metrics from AWS instances and allows the user to visualize these in order to carry out DevOps tasks. It also supports the ability to set an alert based on the criteria that you set. The following screenshot shows the Amazon CloudWatch metrics for an EC2 instance:

Amazon CloudWatch also supports the gathering of an application log. This requires us to install an agent on an EC2 instance. Centralized log management is useful when you need to start managing multiple microservice instances.

ELK is a popular combination of stacks that stands for Elasticsearch (https://www.elastic.co/products/elasticsearch), Logstash (https://www.elastic.co/products/logstash), and Kibana (https://www.elastic.co/products/kibana). Logstash aggregates the application log, transforms it to JSON format, and then sends it to Elasticsearch. Elasticsearch is a distributed JSON database. Kibana can visualize the data that's stored on Elasticsearch. The following Kibana example shows an nginx access log:

Grafana (https://grafana.com) is another popular visualization tool. It used to be connected with time series databases such as Graphite (https://graphiteapp.org) or InfluxDB (https://www.influxdata.com). A time series database is designed to store data that's flat, de-normalized, and numeric, such as CPU usage or network traffic. Unlike RDBMS, a time series database has some optimization in order to save data space and can carry out faster queries on historical numeric data. Most DevOps monitoring tools use time series databases in the backend.

The following Grafana screenshot shows some Message Queue Server statistics:

Communication tools

When you start to use several DevOps tools, you need to go back and forth to visit several consoles to check whether the CI and CD pipelines work properly or not. In particular, the following events need to be monitored:

• Merging the source code to GitHub
• Triggering the new build on Jenkins
• Triggering AWS CodeDeploy to deploy the new version of the application

These events need to be tracked. If there's any trouble, DevOps teams needs to discuss this with the developers and the QA team. However, communication can be a problem here, because DevOps teams are required to capture each event one by one and then pass it on as appropriate. This is inefficient.

There are some communication tools that help to integrate these different teams. They allow anyone to join to look at the events and communicate. Slack (https://slack.com) and HipChat (https://www.hipchat.com) are the most popular communication tools.

These tools also support integration with SaaS services so that DevOps teams can see events on a single chat room. The following screenshot is a Slack chat room that integrates with Jenkins:

The public cloud

CI, CD, and automation work can be achieved easily when used with cloud technology. In particular, public cloud APIs help DevOps to come up with many CI and CD tools. Public clouds such as Amazon Web Services (https://aws.amazon.com), Google Cloud Platform (https://cloud.google.com), and Microsoft Azure (https://azure.microsoft.com) provide some APIs for DevOps teams to control cloud infrastructure. The DevOps can also reduce wastage of resources, because you can pay as you go whenever the resources are needed. The public cloud will continue to grow in the same way as the software development cycle and the architecture design. These are all essential in order to carry your application or service to success.

The following screenshot shows the web console for Amazon Web Services:

Google Cloud Platform also has a web console, as shown here:

Here's a screenshot of the Microsoft Azure console as well:

All three cloud services have a free trial period that a DevOps engineer can use to try and understand the benefits of cloud infrastructure.