DevOps, and managed DevOps, can be difficult to define with the clutter of marketing jargon and buzzwords. To the dismay of technology journalists, there will never be a single definition. At its core, however, DevOps is a cultural shift toward eliminating IT silos while automating repetitive tasks, and it has increasingly grown in popularity due to its promise of increased development speed, faster product releases, and IT collaboration. What does it mean to define DevOps for your organization? Let’s review.
To start, you and your team should sit down and discuss your current IT processes. Figure out what works and what doesn’t. Look for areas you can improve and where those improvements align with DevOps. You need to fully understand what tools your IT teams are using and how much time they spend on certain processes. From there, you’ll discover where your DevOps journey should begin.
Integrating DevOps starts with absolute knowledge of your current systems. Teams may be using different processes and solutions. It’s important to standardize these, as data silos can have a detrimental impact on a business. The recent Forbes article “Why Data Silos are Bad for Business” provides helpful context: “Any time data is touched by a human, objectivity decreases. Machine data is objective. It provides a single version of the truth – one the entire enterprise should share. But it’s impossible to have that one version of the truth if the data is in silos.” Ultimately, data can only be useful if it is collected across the enterprise, and that won’t be accomplished if it’s in silos.
However, standardizing data, while a key priority, is likely not your only priority when implementing a DevOps approach. That’s where a standardized set of best practices can really come into play.
As a combination of cultural philosophies, practices, and tools, DevOps is not defined by any one quality, but rather, as a collection of best practices working together to boost efficiency, agility, and scalability. Let’s review the AWS DevOps best practices as a central frame of reference to draw upon.
Continuous integration: A software development practice where developers regularly merge their code changes into a central repository, after which automated builds and tests are run. You can set up a continuous integration workflow with AWS CodePipeline, which lets you build a workflow that builds code in AWS CodeBuild every time you commit a change.
Continuous delivery: A software development practice where code changes are automatically built, tested, and prepared for a release to production. AWS CodePipeline and AWS CodeBuild also help implement this.
Microservices: Microservices architecture is a design approach to build a single application as a set of small services. Each service is built around a single business purpose and can communicate with other services through a well-defined interface. Services such as Amazon Elastic Container Service (Amazon ECS) allow you to easily run and scale containerized applications on AWS.
Infrastructure as Code: A practice in which infrastructure is provisioned and managed using code and software development techniques, such as version control and continuous integration. AWS CloudFormation provides a common language for you to describe and provision all the infrastructure resources in your cloud environment.
Monitoring and Logging: A practice in which organizations monitor metrics and logs to see how application and infrastructure performance impacts the experience of their product’s end user, shedding insight into the root causes of problems or unexpected changes. Amazon CloudWatch provides you with data and actionable insights to monitor your applications, understand and respond to system-wide performance changes, optimize resource utilization, and get a unified view of operational health.
At the end of the day, collaboration drives DevOps. DevOps tooling and automation of the software delivery process ultimately brings together the responsibilities of development and operations, and in doing so, speeds up the communication process between teams.
Implementing DevOps is never as easy as it sounds. Successful implementation in a timely manner requires a lot of expertise. Additionally, new challenges and constant maintenance require a watchful eye, but who’s going to manage all of this?
Many organizations turn to managed DevOps to accomplish their goals. For example, Mission helps translate business objectives into a technology roadmap. We design, build, and manage elastic technology environments while also implementing infrastructure automation and deployment. Defining DevOps for your organization doesn’t have to be a solo expedition.
Free AWS Consulting - leverage best practicesSchedule Appointment
Content Editor and Writer - DevOps, Cloud, and Network Monitoring