Originally Published in CIOReviewIndia by Anand Kapoor, SVP - Data & Insights at Antuit
Today, there are a plethora of consultants and tools available to help companies and teams implement a DevOps model. To gain the most benefit, development and operations teams must undergo a culture shift and build a close working relationship. Debois believed a collaborative environment enables development to deploy releases faster and with fewer mistakes. From experience, I have learned that the best approach is to embrace DevOps principals rather than fixating on a specific tool or approach.
As DevOps enters its second decade, in 2019, I anticipate the following changes:
DevOps is More than a Tool – It’s a Mindset
From the beginning, DevOps was designed to be more than just a tool. Debois’ goal was to create a new way of thinking and approach for reducing the development life cycle. He believed that by creating a new process for team collaboration and helping different departments work together, they would significantly reduce testing and increase deployment.
The relationships and processes created by DevOps teams are more important than the DevOps tools themselves. Debois understood that the significant value was teams working together to solve problems quickly and efficiently. The internal process brought teams together, not the DevOps tools. For many today, DevOps is a definitive culture.
DevSecOps and DevOps Will Become One
Another change occurring is that at the beginning of the implementation cycle, both application and infrastructure developers are embedding security. Before, security controls were included in the final stages of development which was counterproductive, resulting in delays of the development cycle. Application security was often an afterthought in the development process. Now, containerization and micro-services improve security in the process. As these processes evolve, I believe DevSecOps will become a natural choice for agile, high performing enterprises and synonymous with DevOps.
Artificial Intelligence and Machine Learning in DevOps
Today, using artificial intelligence (AI) to make software processes more manageable is a widely accepted mindset. There are two areas where AI bisects DevOps: the tools and people. Successful DevOps implementations churn out data, lots of data, enabling team members to spend time on more meaningful tasks.
As AI and machine learning (ML) are implemented, teams will have access to better data with the ability to analyse and predict behavioral trends. Project managers are exploring delivery velocity and data that a CI/CD process generates. However, most managers, even today, fail to notice the correlations between the failures and bugs. I think as the processes are automated, DevOps will become more sophisticated.
Force on Site Reliability
Site reliability engineering which, so far, has evolved and runs independently of DevOps. Today, experienced managers are noticing that teams are solving and addressing the same problems occurring in areas of production management. The only difference between the two areas is the method used to address the problem which is often sent to DevOps to solve without involving the developers. I believe as DevOps and the related processes mature, the lines between the two groups will start to blur.
Self-Service in DevOps
As the DevOps mindset becomes part of internal cultures and DevOps matures, teams will start breaking down cost, scope and dependency barriers. AI and machine learning are providing the means to automate the DevOps process which will enable one-touch deployment in the future.
Automated Testing and Quality Assurance
Automated testing for Quality Assurance (QA) is increasing. Companies are discovering how DevOps can make a positive and significant impact on QA testing. Traditionally QA would appear at the end of the development process. However, today the process is different. To ensure a one hundred percent code coverage with automated test cases, it will require the QA manager to align to the DevOps cycle earlier in the development. By adding DevOps earlier in the process through automation, the teams can produce faster deployments.
Better Pay Hikes for DevOps
The demand for skilled DevOps developers and managers continues to increase as more and more companies use the methodology. Most DevOps individuals are experienced coders and can effectively manage infrastructure deployments. With the plurality of skills, most DevOps engineers can command more income in the job market.
Businesses that apply DevOps efficiently will experience an agile and faster software process. Adapting DevOps allows applications and technology solutions to empower businesses with faster and better-quality outputs. Savvy managers are applying the same principles to solve bottlenecks in other processes or expanding the scope to include teams outside of their department to solve more substantial issues.
Key Things to Remember:
- It’s a mindset, not a tool
- Incorporate AI
- Automate everything