DevOps, Simplified!

Most of the emerging technologies and SaaS based solutions today practice rapid application development ( Read, RAD) for enablement of usecases via agile frameworks fuelled by DevOps, The proven methodology for system development lifecycle. It combines Development + Quality assurance and IT operations as a single seamless function managed by specialized automation, self-service and mostly leveraging varied opensource tools, often called as toolchains. I believe it emerged in 1990s as part of the ITIL process and inherited best practices from PDCA, Lean and/or Agile approaches as well believing in continuous development and integration as a core principle. 

The key purpose of DevOps adoption is fostering tight coupling between IT operations ,software development and quality assurance enabling better communications within the teams and leveraging the cross functional expertise to improve design, development, testing and deployment of software by enabling the following key tenets:

• Stable and on demand operating environments
• Super-fast delivery, reusable configurations and code
• Pre-integrated collaboration of workflows
• Time optimization, particularly in fix/maintain phases embracing failures as learnings
• Ongoing innovation and automation leveraging cross functional expertise

An organization embracing DevOps must begin with developing and fostering the DevOps culture that demands a work methodology based on the development of code that uses new tools and practices and allows teams to work more closely, bringing greater agility to the business and notable increases in productivity.

Why DevOps?

DevOps Model allows developers and Operation engineers to simplify the process and allows them to be more productive via automation, that reduces the number of manual actions, and iteration accelerates the development process thanks to faster end-users feedback and quick fixes. The most important aspect is self-service, that helps accelerate releases by enabling developers to deploy applications on-demand by themselves and testers perform the testing in tandem with the code ready for testing. Broadly, DevOps accelerates time to market and fosters collaboration within the teams to share expertise to implement Continuous Integration and Continuous Delivery. The key reasons for the wide spread adaptation are:

• Predictability & Maintainability - DevOps offers significantly lower failure rate of new releases and makes failovers and fallbacks almost instantaneous thus enriches predictability and lowers disruptions. Effortless process of recovery in the event of a new release crashing or disabling the current system thus guarantees maintainability. Of course, Versioning everything is possible so that earlier version can be restored anytime. DevOps also helps enhance collaborations between development, operations, and quality assurance teams to facilitate continuous integration, testing, and delivery of software thus increasing efficiencies for smother functioning and quicker issue resolutions / bug fixes for quality assurance of the product deliverable.
• Better Time to market, Greater Quality and Scale - DevOps reduces the time to market up to 50% through streamlined software delivery pipeline particularly the case for digital and mobile applications and helps the team to provide improved quality of application development as it incorporates infrastructure issue resolutions by design and allows full spectrum of testing with automation. DevOps tools enable enterprises to automate software development and testing lifecycle by standardizing and automating the movement and deployment of code across different environments with scale on demand.
• Reduced Risk & Resiliency – Since DevOps incorporates security aspects in the software delivery lifecycle helping in reduction of risks across the entire application development and deployment lifecycle providing continuous operational state of the application for stable, secure with auditable changes.
• Cost Efficiency & Agility: adoption of DevOps offers cost efficiency in the application development process which is always an aspiration of organizations and allows the agile programming method with component based approach that can be designed, developed and integrated breaking larger code bases into smaller and manageable chunks with structured codeines and merging strategies.

DevOps Skills

DevOps engineer must be able to understand and use a wide variety of open-source tools and technologies and low code or no code metaphors. Today’s stacks are comprised of dozens of different software, source control tools, databases and automation tools, The technical domains that should converge into a successful DevOps engineer should entail..

• Being an excellent Sysadmin – Breathing opensource and Linux/Unix – Know API ecosystems, integration and configuration management.
• Deploying Virtualization and Containers; Hand-on expertise on networking and storage
• Coding, Testing and Test Automation – Scripting – Full stack developers are definite winners
• Understanding Security aspects of the environments and databases and protection thereof.

The ability to make them all work together is also crucial, making the ability to code and script just as crucial thus blend of development/programming frameworks, IT infrastructure, automation tools and scripting and of course the database skills etc. Apart from other skills necessary for the job are more about mindset and should include:

• Ability to collaborate, communicate, and reach different departments.
• Comfort in a fast-paced, agile and ever-changing environment.
• Years of experience with systems and IT operations, production engineering
• Strong emphasis on business outcomes and acumen a plus

DevOps Stages

Since development, quality assurance and delivery processes are tightly integrated to work together to provide much more than the traditional SDLC, the software development lifecycle, each stage of the DevOps gets awareness and needs active involvement of cross functional skills, processes and tools as they would impact the end objective of delivery and continuous improvement as an ongoing endeavour without compromising on the security of the digital assets such as code repositories and datasets.

Continuous Development

• Create / Code – the stage where planning, design, code development and review, source code management tools, code merging etc is involved.
• The code can be written in any language, but it is maintained by using Version Control tools. Maintaining the code is referred to as Source Code Management,
• The most popular tools used are Git, SVN, Mercurial, CVS, and JIRA. Also tools like Ant, Maven, Gradle might be used in this phase for building/ packaging the code into an executable files for deployments in testing environments.

Continuous Testing

• Testing – continuous testing tools that provide quick and timely feedback on business risks. This is the stage where the developed software is continuously tested for bugs
• Automation testing tools like Selenium, TestSigma, TestNG, UFT, Appium, Bamboo, JUnit, Cucumber etc allow QAs to test multiple code-bases thoroughly in parallel to ensure that there are no flaws in the functionality, the environments used for testing are quickly provisioned and leverage containers or virtual instances for rapid and automated deployments.
• This entire testing phase can be automated with the help of a Continuous Integration tool called Jenkins. Automation testing saves a lot of time, effort, and labour for executing the tests instead of doing this manually. The build lifecycles, automation servers, code branching, merging etc are managed by opensource tools like Ant, Maven, GitHub as required.

Continuous Integration

• This stage is the core of the entire DevOps life cycle in which the developers require to commit changes to the source code more frequently. This may be on a hourly, daily or weekly basis based on the release strategy.
• Every commit is then built and this allows early detection of problems if they are present. Building code not only involves compilation but it also includes code review, unit testing, integration testing, and packaging
• The code supporting new functionality is continuously integrated with the existing code. Since there is a continuous development of software, the updated code needs to be integrated continuously as well as smoothly with the systems to reflect changes to the end-users, there is also an ecosystem of tools—Jenkins, Ansible, Gitlab CI, Travis CI, and numerous others have sprung up to help organizations create their own pipelines.

Continuous Deployment

• This is the stage where the code is deployed to the production servers. It is also important to ensure that the code is correctly deployed on all the servers. This process deploys the code on the production servers. It is also crucial to ensure that the code is properly deployed on all servers. The role of microservices and micro codes is becoming inevitable here since it allows granular scaling and updates and deployment of logical application modules independent yet interwoven to work and scale seamlessly.
• Configuration management is the operation to release server installations, schedule upgrades, and keep all instances compatible with configurations, responsible for establishing and maintaining consistency in an application’s functional requirements and performance and on demand deployment of the code on the prescribed environments.
• Since the new code is deployed on a continuous basis, configuration management tools play an important role in executing tasks quickly and frequently. Some popular tools that are used here are Puppet, Chef, SaltStack, and Ansible etc.

 Continuous Monitoring

• This is a very crucial stage of the DevOps life cycle where you continuously monitor the performance of your application. provides useful information that allows us to ensure maximum productivity and uptime of operation. The operations team obtains accurate testing tools to locate and correct the bugs/flaws in the software.
• The feedback or the corrective information is processed to recognize the proper functionality of the application and root cause of any issue is determined in this phase. It maintains the security and availability of the services and triggers actions required for correction
• This practice involves the participation of the Operations team who will monitor the user activity for bugs or any improper behaviour of the system and environments the toolchains operate upon, there are many popular tools used such as Nagios, Monit, Collectd, ELK Stack ( combination of Elastic search, Logstash and Kibana) etc along with paid ones like Splunk NewRelic, and Sensu etc.

DevSecOps, NoOps, AIOps and way forward..

Since the automation and innovation are aspirational, more and more relevant streams are getting unified under the DevOps Model and branching out broadening the scope of DevOps in line with the market dynamics often known as security as a code. DevSecOps focuses on the integration of security at every phase of the software development lifecycle, from initial design through integration, testing, deployment, and software delivery is automated and tightly integrated in the workflow.

Whereas, NoOps focuses on the deployment by design without need of any manual efforts as an end to end automated workflow from code commit to deployment thus enriched form of continuous delivery and deployment spanning from software to underlying infrastructure such as allocating an instance, loading the OS, and other architectural software components like application servers and databases, setting up the networking layer, building the application from the latest source in the code repository, deploying it in the configured machine. While containers are fast replacing the virtual environments in NoOps making the DevOps more agile, deployments are controlled by APIs to spin the containers, configure load balancers or scale the web services or data nodes etc. Changing the very paradigms of the development methodologies and metaphors.

Worth mention the AIOps, could be another topic to elaborate, focuses on artificial intelligence to improve IT operations and continuous monitoring via specialized AI based correlation engines that could correlate alerts to determine a root cause, pinpoint broken configurations and workflows etc.

In Summary, DevOps is the strategy for assimilating cultural philosophies, best practices, and supporting tools that increases ability to deliver applications and services at a higher velocity, agility in evolving and improving products than the traditional software development and infrastructure management approaches and thus helps sustain the digital agenda bringing in a holistic approach to the complete software delivery mechanism.

While few relate DevOps only to automation, in reality it goes so much beyond the erstwhile domain enabling other information technology areas and practices; hyper automation for better performance in the face of digital economy challenges and opportunities resulting in competitive edge and commercial advantage in the overall digital transformation agenda. Coupled with emerging technologies that drive integration, automation, self-service provisioning, cloud adoption with auto scaling / healing capabilities the DevOps ecosystem has today become a role model for modern, open source and distributed ways of computing practices. In a nut shell, crowdsourced innovations ( read, open source), sophisticated automation within a continual cycle of discovery, design and delivery with real time measurement to deliver business benefits remains the key mantra for DevOps, isn’t it?

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May 2021. Compilation from various publicly available internet sources, authors views are personal.

#DevOps #SoftwareEngineering #SDLC #Agile #DevSecOps #NoOps #AIOps #automation #automatedtesting #AI #ELK #Jenkins #GIT #CICD