Below are the important DevOps best practices that can help you with the successful implementation of DevOps.
- Recognize Your Infrastructure need:
Before constructing the infrastructure, use some time to acknowledge the application and then line up your goals to design your infrastructure and this implementation of DevOps should be business-driven. While considering infrastructure, ensure that you are capturing below aspects:
Components to understand infrastructure
- Cycle Time:
Your software cycle have to be defined in a generic manner where you have to know the limitations, capacity and if there is any downtime then the exact time needs to be addressed.
- Versioning Environments:
While thinking of DevOps, always be ready for an alternative option and versioning your surroundings helps you to roll out/back your strategy. If you are having a various module and tightly coupled, then it needs a clean and clear plan to classify each and every patch and release.
- Infra as a code:
When we consider infra as a code it means a solution to notifying both needs – minimizing cycle time and versioning surroundings can be addressed by monitoring and managing your Infrastructure as code. What you built should scalable for the long run.
- Don’t jump start:
It is not necessary to automate the complete cycle in one shot, always take a small part and apply your philosophy and get this validated. Once you feel your POC is justified, start scaling up now and create a complete pipeline and define a process so anytime you can go back and check what all need to improve and where. All these small successes will help you to get confidence internally in your team and builds trust to the stakeholder and your customers. “DevOps isn’t magic, and transformations never happen overnight”
- Continuous Integration and Continuous Deployment:
If your team is not thinking to implement this continuous integration and continuous delivery, then it is not fair with DevOps. Even I will state the beauty of DevOps is how often your team can deliver without trouble and how much you are automated in this process.
Let’s take a use case: You and your team members are working in an Agile team. In fact, there are different teams and various modules which are tightly coupled in which you are also involved. Every day you work on your stories and at the end of the day, you push your ‘private build’ of your work to verify if it builds and ‘deliver’ it to a team server and same applies to other members.
Which shows; you all integrate your work in the common build space and do integration build. Making these integrations and builds to verify them on a steady, preferably daily basis is what is known as Continuous Integration. Continuous Deployment does not mean every modification is deployed to production as soon as possible.
It means each modification is proven to be deployable at any time. What it chooses is your all validated feature and builds from CI and deploys them into the production atmosphere.
And here we should follow some of the practices.
- a) Keep a Staging Environment that Emulates Production
- b) Constantly deploy in staging then move to production
- c) Automate Testing of Features and Nonfunctional Requirements
- d) Automatically fetch version-controlled development artifacts.
Suggested: Making DevOps applicable for you
- Define Performance and do benchmarking:
Constantly performs some performance testing and get a combined benchmarking report for the latest build shared by your team because this will only validate the quality of your build and the needed infra as well.
We have completed one performance testing a few days before and got results, explaining in details. So we performed some benchmarking for our CFM machines because we are taking a global footprint and at the same time, for us, latency matters and we need CFM in the nearest region. We have confirmed with our current size how many requests we are able to handle and we found we are firing more than 200 RPS (request per second). So we planned to check our build capability and fired a good number of requests and noted the number where our build got crashed and noted the RPS and then we did auto-scaling of CFM. We might have updated our CFM but we thought for auto-scaling because the different requests is an assumption and we don’t want to spend amount for that but at the same time we are prepared to ingest the experimented traffic. And then we found 7 out 2 CFM are only consuming exact or little less number of configuration and request (181 to 191 RPS). So we forward a report to the business team to concentrate on other regions where we were having very less traffic because we were paying the same amount.
We validated our size which gave higher confidence to our development team and we forwarded the report to the business team which helped them to make their marketing strategies, meanwhile, we finished auto-scaling the process as well.