DevOps is a constantly evolving mindset and system that promotes quicker and higher-quality application development, as well as the swift delivery of new or updated software features to users.
Practicing DevOps fosters seamless and ongoing communication, teamwork, integration, visibility, and openness between application development teams (Dev) and their counterparts in IT operations (Ops).
This strengthened bond between “Dev” and “Ops” influences every step of the DevOps journey: from initial software planning, through coding, building, testing, and releasing, to deployment, operations, and continuous monitoring. This collaboration fuels a continuous loop of customer feedback, driving further enhancements, development, testing, and deployment. Ultimately, this can result in the quicker and more frequent release of necessary feature changes or additions.
Some individuals categorize DevOps objectives into four pillars: culture, automation, measurement, and sharing (CAMS). DevOps tools play a vital role in supporting these goals. They simplify and enhance development and operations workflows by automating tasks that were previously time-consuming, manual, or stagnant, across integration, development, testing, deployment, and monitoring processes.
Why DevOps Matters
In addition to striving to improve communication and collaboration between development and IT operations teams, DevOps places significant emphasis on customer satisfaction and the swift delivery of value. Moreover, it aims to drive business innovation and foster ongoing process enhancements.
The practice of DevOps, including DevOps development services, promotes the expedited, enhanced, and more secure delivery of value to an organization’s end users. This value could manifest in the form of frequent product releases, additional features, or updates. It encompasses the speed at which products or new features reach users’ hands, all while maintaining the requisite levels of quality and security. Alternatively, it may focus on the prompt identification, resolution, and re-release of issues or bugs.
Furthermore, the underlying infrastructure plays a crucial role in supporting DevOps by ensuring seamless performance, availability, and reliability of software throughout its development, testing, and eventual release into production environments.
DevOps Methods
Several common DevOps approaches exist that organizations can leverage to expedite and enhance development and product releases. These approaches encompass various software development methodologies and practices, with some of the most prevalent ones being Scrum, Kanban, and Agile:
- Scrum: Scrum outlines how team members should collaborate to accelerate development and quality assurance (QA) initiatives. It entails specific workflows, terminology such as sprints and time boxes, and designated roles like Scrum Master and product owner.
- Kanban: Originating from efficiency gains in Toyota’s factories, Kanban advocates for tracking the state of work in progress (WIP) on a Kanban board, aiding in visualizing and managing software project progress.
- Agile: Agile methodologies, which emerged earlier in software development, strongly influence DevOps practices and tools. Many DevOps approaches, including Scrum and Kanban, integrate agile principles. Agile practices emphasize adaptability to changing requirements, documenting needs as user stories, conducting daily standups, and integrating continuous customer feedback. Agile also promotes shorter development lifecycles compared to traditional waterfall methods.
DevOps Toolchain
DevOps practitioners often utilize specific DevOps-friendly tools as part of their DevOps “toolchain.” These tools aim to streamline, condense, and automate various stages of the software delivery workflow, commonly known as the “pipeline.” Many of these tools also uphold fundamental DevOps principles such as automation, collaboration, and integration between development and operations teams. Below are examples of tools used at different stages of the DevOps lifecycle:
- Plan: This stage involves defining business value and requirements. Example tools include Jira or Git, which aid in issue tracking and project management.
- Code: Here, software design and coding take place. Sample tools for this phase include GitHub, GitLab, Bitbucket, or Stash.
- Build: This phase entails managing software builds and versions, along with using automated tools to compile and package code for future production release. Examples of tools used include Docker, Ansible, Puppet, Chef, Gradle, Maven, or JFrog Artifactory.
- Test: Continuous testing, whether manual or automated, is conducted in this phase to ensure optimal code quality. Tools commonly used include JUnit, Codeception, Selenium, Vagrant, TestNG, or BlazeMeter.
- Deploy: Tools in this phase aid in managing, coordinating, scheduling, and automating product releases into production. Examples include Puppet, Chef, Ansible, Jenkins, Kubernetes, OpenShift, OpenStack, Docker, or Jira.
- Operate: This phase involves managing software during production. Tools utilized here might include Ansible, Puppet, PowerShell, Chef, Salt, or Otter.
- Monitor: Identifying and collecting information about issues from a specific software release in production occurs in this phase. Sample tools for monitoring include New Relic, Datadog, Grafana, Wireshark, Splunk, Nagios, or Slack.
DevOps Practices
DevOps practices reflect the idea of continuous improvement and automation. Many practices focus on one or more development cycle phases. These practices include:
- Continuous development. This practice spans the planning and coding phases of the DevOps lifecycle. Version-control mechanisms might be involved.
- Continuous testing. This practice incorporates automated, prescheduled, continued code tests as application code is being written or updated. Such tests can speed the delivery of code to production.
- Continuous integration (CI). This practice brings configuration management (CM) tools together with other test and development tools to track how much of the code being developed is ready for production. It involves rapid feedback between testing and development to quickly identify and resolve code issues.
- Continuous delivery. This practice automates the delivery of code changes, after testing, to a preproduction or staging environment. A staff member might then decide to promote such code changes into production.
- Continuous deployment (CD). Similar to continuous delivery, this practice automates the release of new or changed code into production. A company doing continuous deployment might release code or feature changes several times per day. The use of container technologies, such as Docker and Kubernetes, can enable continuous deployment by helping to maintain consistency of the code across different deployment platforms and environments.
- Continuous monitoring. This practice involves ongoing monitoring of both the code in operation and the underlying infrastructure that supports it. A feedback loop that reports on bugs or issues then makes its way back to development.
