DevOps is a buzzword that is often spread. In fact, it is a set of principles designed to streamline and govern the entire development process, from the brains of your programmers to your servers.
Most teams can probably divide their developers into two broad categories:
Developers, who handle updating the code base, fixing bugs, and everything around programming. You can also include other roles, such as web and user interface designers in this category. Generally, this includes anyone involved in the creation of your product.
SysAdmins or the “operations team”. These people manage updating servers with new code, managing both your public and internal server infrastructure, and keeping everything operational.
To put it simply, DevOps consists of integrating these two teams together (hence the coat rack of a name). It won’t make your developers system administrators, or vice versa, but it should help them work together.
Every aspect and every phase is complemented by tools that facilitate this whole process. DevOps is more than just tools and automation, and implementing a set of “DevOps tools” won’t automatically make your team work twice as fast, but those tools are a major part of the process, and it would. difficult to be so effective without some of them.
While there are many other buzzwords under the umbrella of “DevOps,” the basic concept is pretty straightforward. When a team is functioning well, DevOps typically works like this:
To explain, we will start with the monitoring phase. This involves keeping an eye on your servers, monitoring crawls, analyzing logs, and identifying issues with your code base. While a lot of this relates to code, a lot of it also falls on the business side. Are you effectively achieving your goals? Are your customers satisfied? This phase is about finding out what is wrong so that you can set appropriate goals for yourself. Popular monitoring tools include Nagios, AWS CloudWatchand analysis software like Google analytics.
Maybe you get a ticket directly from a customer and start with the planning phase. This is where you’re going to sit down with your core developers and discuss what needs to be done to complete a ticket. If you are using software like Jira, you’ll likely break a big ticket down into individual stories and issues that can be more easily tracked and attributed to individual developers. If you’re planning a code sprint for the next week or two, you’ll want your plan to be clearly defined to reduce the time spent reiterating code.
Rather than testing and building once when it’s all done, in a DevOps environment every developer will ideally submit changes for source code control multiple times a day, whenever issues are resolved or a minor step is taken. reached. This allows the build and test phases to start early and ensure that no developer strayed too far from the head of primary source control. This step is primarily about managing source control properly, so having an efficient git service like GitHub, Gitlab, or BitBucket is essential to ensure that continuous integration works.
You don’t have to deploy every engagement to production right away, but rapid automated deployments are a big part of being able to push fast releases. Plus, it reduces stress on your operations team, allowing them to focus on things more important than manually updating servers with new code.
Once the new changes are deployed, the cycle begins again. This new feature that you added may cause additional hours on the staging database server and may need to be marked for performance review and fixed before deployment to production. If all goes well, DevOps stops being a series of fixed steps and simply becomes a culture that everyone naturally follows.
Continuous integration / Continuous delivery pipelines
Automation and tools are an important part of any DevOps environment. Perhaps the biggest tool to have is a continuous integration / continuous delivery (CI / CD) pipeline. It is an automated process that starts with the source code and manages the process of building, testing, and deploying to servers.
AWS CodePipeline is a good example. Whenever a change is detected in source code control (GitHub, BitBucket, or AWS CodeCommit), it is sent to AWS CodeBuild for building and testing. Alternately, Jenkins is used quite often to handle this phase of construction.
Typically, once the build is complete, you will want to send it to a test environment before going straight to production. Even still, automating deployments to test and production servers will dramatically speed up iteration times. In the AWS pipeline, this is handled by CodeDeploy. Jenkins can also handle the deployment, as well as software such as Ansible.
Overall, a CI / CD pipeline can automate most of the DevOps flow from construction to deployment, making it a crucial part for any team looking to work efficiently.