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DevOps Automation and DevOps Automation Tool Chain

1. Overview

Improved productivity leading to greater profitability without much disruption is what every organization dreams for. For greater productivity and continuous delivery, DevOps has always been the trusted software development methodology to shorten the application delivery lifecycle.

DevOps has taken the IT world by storms, and has transformed the ways businesses used to work, conventionally. As technical advancements and AI has made their ways into all verticals, DevOps too is not left untouched by the influence. The businesses are automating their DevOps tasks and with DevOps Automation, reaping high returns and great benefits out of their investments.

  1. Overview
  2. DevOps Automation
  3. DevOps Automation Tool Chain

1.1: What is DevOps?

The term DevOps – formed by combining ‘development’ & ‘operations’, is a set of practices aimed at automating and integrating the processes between application development and IT operation teams; so that they can develop, run trials, and release applications fast & reliably.

Plainly put forward, DevOps is a specialized development methodology to speed up the development of applications across an enterprise with high quality. DevOps instead of a new technology or a single person’s role, must be considered as a culture or philosophy that bridges the gap between both the teams that traditionally used to work in silos.

In this practice, the development teams and the operation teams are connected within an environment of agile relationship, for an improved collaboration leading to greater productivity.

1.2: Need of DevOps

There is a common misconception that DevOps is nothing but a new trend or the new style of developing applications. This apprehension is not at all true.

As mentioned previously, the improved collaboration is aimed at faster and better output. The DevOps model is here to stay as the older methodologies like waterfall and agile greatly lack speed. When the development team finishes the task then the operation team takes it up to further levels, without any mutual coordination. When there are combined efforts of both the teams working in parallel – the development cycles are short, innovations are fast, and time to market is less; taking the organization ahead of the competition.

The findings based on a survey report conclude that high performing IT organizations, leveraging DevOps deploy apps 30 times more frequently with 200 times shorter lead times; they have 60 times fewer failures and recover 168 times faster. Another DevOps report has established that teams practicing it have 22% less time wasted on unplanned work, and 50% less time remediating safety concerns.

So, it is easy to conclude that collaboration will lead to improvements in overall organizational competencies; and DevOps will help them in gaining this at the technical and operational levels as well.

1.3: Benefits with DevOps

Out of the various covert & overt benefits with DevOps, the major ones include:

Better time to market: Streamlined workflows and continuous processes shorten the development lifecycle, pushing better products to market in a shorter time span.

Greater resilience against changing business needs: By the time end products reach the market, the developers lose their contact with the major codes. Development and operations team are also out of communication, and when any change is required, it gets too hard to implement. DevOps methodology reduces this problem, greatly.

Better Competencies: Frequent code versioning, faster recovery, bolstered collaboration, greater resilience- all in unison enhance the organizational competencies.

Greater levels of automation: DevOps teams can easily automate several central processes to speed up the entire production cycle, saving lots of efforts and time.

2. DevOps Automation

2.1 Introduction

Automation in the context of DevOps minimizes manual intervention in managing repetitive tasks to facilitate DevOps practices. It even helps realize the full potential of DevOps methodology and ensures that it delivers what is best for the organization.

An organization can run DevOps processes manually but they would require a huge team, lots of time, and greater coordination among team members, which might not be realistic or economically viable in most of the scenarios. Leveraging DevOps Automation tools, the majority of the time-consuming, repetitive tasks across the application deployment lifecycle can easily be automated, reducing time to market.

2.2: DevOps Automation Best Practices

i) Continuous Integration, Continuous Delivery, and Continuous Deployments

CI/CD is the key component of DevOps process that allows faster implementation of changes after thorough testing and deploy successful releases to production continuously.

Together, continuous integration & continuous delivery/deployment:

  • reduces complex branching of an application in development
  • minimizes effort to deploy code
  • speeds up application delivery

Nevertheless, teams can better maintain quality control through automation and bring new features to users with zero application downtime.

ii) Change management

Change management is a crucial part of business processes and automation, with pre-defined guidelines, in the following spheres will offer a greater consistency.

  • Version control: Version control, providing a common workflow and code-base for individuals to work on, is crucial for teams to collaborate and help revert changes easily.
  • Change control: On top of version control, having a system to coordinate and make changes reduces the probability of defective code. Effective change control ensures this and encourages a collaborative process.
  • Configuration management: Configuration management enables easy management of complex deployments and manages changes at scale with suitable controls and approvals.

iii) As a Code Model

There are several code models providing a declarative framework for managing different aspects of operating environments. DevOps implements the “as code” principle with varied goals like auditable change trail for compliance, collaborative change process, consistent, testable and reliable way of deploying resources, and as a way to reduce time in learning new technology. The various examples are: ‘Infrastructure as code’, ‘Platform as code’, ‘Configuration as code’, and ‘Policy as code’.

iv) Continuous monitoring

One needs to have information about how the environment operates. Continuous monitoring of performance, app stability and infrastructure throughout the app lifecycle provides operations teams with data to help resolve issues, and debug patch information to the development teams. This also facilitates greater security level.

3. DevOps Automation Tool Chain

3.1: What is a toolchain in DevOps context?

Key DevOps concepts are centered on CI/CD, automation, and collaborative team work. So, there is no single tool that can offer the complete automation of DevOps tasks. Rather, a series of different tools for different applications is used for the purpose. Clubbing all those tools together makes a DevOps Automation toolchain.

To be more precise, a DevOps toolchain is a set of different tools solving a particular problem in unison, and making the product delivery faster and much more efficient.

3.2: Kinds of Tools used in DevOps Automation

As mentioned above, different tools are used for different facets of DevOps automation. As per the DevOps methodologies, the tools are divided into the following categories:

Collaboration

Collaboration is at the heart of DevOps methodology and the need for clear communication between various teams is vital for successful deployment. Various communication/collaboration tools connect and help teams work together across various time zones. Some of the major tools used for collaboration among different teams are Slack, Skype, Campfire, etc.

Planning and Data Access

For better results, the stakeholders, employees, and clients are required to be on the same page with concentric goals. This is only possible with a greater transparency and better accessibility to the data, as and when required. Various CRM applications like Asana, Jira, Clarizen help the teams in this regard.

Source Control

The organizations need a centralized storage for the information and the data can be further classified into different sub-sections for various teams to work on. Source Control tools like Subversion, SVN and others can help in source control of data.

Configuration Management

Configuration Management enables organizations to scale IT infrastructure and software systems without correspondingly scaling administrative staff to manage the same. There are special configuration management tools that automatically configure and update the systems. The various systems that need to be in known, determined states are servers, storage and network & software components. Important configuration management tools are Ansible, Puppet, and Chef.

CI/CD

In the software development phase, the codes developed in forms of small chunks and are then gradually integrated. The codes may perform well individually but have been found to impose issues in integration. Continuous Integration entails two major stages – build and test automation. It enables creation of automated pipelines to push deployment-ready code. Whereas, Continuous deployment /Continuous delivery refers to uninterrupted delivery of software to the end-users. In continuous delivery, developers make a final decision when they need to deploy the new code while in continuous deployment code is deployed automatically and constantly. The various tools available are Bamboo, Jenkins, TeamCity, etc.

Testing

The complete code must be tested before passing into the final end usage. Faster is the feedback loop, quicker is the goal achievement. Tools for such automated testing are Selenium, Telerik, QTP, and TestComplete etc.

Containerization and Orchestration

Containers are used to wrap each bit of code with environmental elements like files and libraries and each container can run across varied operating systems. In a microservice-based architecture, various service elements in the form of containers are interconnected to develop an application. Efficient orchestration is crucial to manage and configure several distinct service elements. Most often containerization and orchestration tools are built into CI/CD pipelines as default tools or can also be plugged in as extensions. Some of the popular tools are Docker, Kubernetes, and OpenShift etc.

Monitoring and Alerting

Ensuring peak app-performance gets bit harder with addition of new features constantly. DevOps, when powered by specific tools with a dedicated interface, enables a better culture of overall observations. Sensu, PageDuty, Tasktop Integration Hub, Librato etc are monitoring and alerting tools.

Database Management

Data is highly valuable to get the important insights and the application development requires a lot of such data and related insights. For this cumbersome, but highly important task, there are several effective tools to ease the data acquisition. For example RazorSQL, TeamDesk etc.