5 DevOps Trends to Follow in 2019


By Anastasia Stefanuk | DevOps is a specialized space that has grown over the years. What started as a theoretical approach to unifying resources, practices, and tools for application development, is now an essential business approach to application and systems development. Software developers, DevOps engineers, release managers, and security officers are only some of the individuals that make up a DevOps team.


The growth of DevOps has brought about interesting changes in the tech space. Here are some of the prevailing trends that not only seek to incorporate modern tools into your approach, but can also improve your team’s performance across the board.


DevOps Trends to Anticipate in 2019


1.   Implementing Microservices


Microservices, or microservice architecture, is a method of structuring and developing an application using a collection of standalone deployable application services. These services are usually lightweight and serve specific functions.


Using microservices enables continuous development and delivery of scalable and agile applications. Implementing this kind of approach goes a long way toward streamlining development, production processes, and timelines. Using microservice architecture also opens up the possibility of re-using them for multiple development avenues.


2.   Faster Growth with AI and Machine Learning


Incorporating AI and ML can be the key to optimizing DevOps processes. These technologies can assist with deployment risk and impact prediction, as well as automation shortcuts and bottleneck identification.



The predictive capability of AI and ML can help identify and address potential problem areas in the development process. They can also help to analyze customer communication and feedback, giving businesses and developers a better understanding of the impact of the application or system. 



Increased collaborative development with other experts, like data scientists, also results in the use of such technologies. Business insights provider Gartner forecasts that at least 40% of new applications development projects by 2020 will include AI co-developers on their development teams.


3.   Strong Focus on Automation


Automation has played a large role in every industry, and DevOps is no different. Automation saves time spent on routine or redundant tasks, enhancing efficiency and reducing turnaround time. 



Automation can be utilized throughout the overall DevOps lifecycle in the following ways:


1.     Continuous Business Planning


2.     Collaborative Development


3.     Continuous Testing


4.     Continuous Release and Deployment


5.     Continuous Monitoring


6.     Collaborative Customer Feedback and Optimization


The best place to start with automation is to apply it where it is most useful and effective in the overall lifecycle–namely, the most repetitive, tedious, and time-consuming processes.


4.   Application of DevOps Assembly Lines


Application development has now expanded beyond Continuous Integration (CI) Pipelines. Where before developers were focused on streamlining activities and tasks into a single pipeline, they are now looking gravitating toward an ‘assembly line’ type of development process.



With the numerous tools used to manage the wide array of activities that go into application development, keeping track of and maintaining linkages between these tools becomes challenging. Assembly lines link together and automate processes conducted by various teams; such as CI from development teams, versioning and approval from release managers, testing automation for quality control, security updates from security operations, and others.


5.   Adoption of Container-based Tools


The problem of data locality will be felt in the following years, especially with the increasing amount of legislation reinforcing geographical bounds on local data. As a result, applications, critical data, and systems will have to be deployed across multiple geographical areas. This increases the complexity of deployment processes and development methodologies.



Container-based tools are among the most popular approach to address the issue. Containers are standalone applications, containing both code and dependencies. Moving and deploying enterprise systems across various environments and geographical areas are more manageable and efficient with the use of containers. Tools such as Docker, Kubernetes, Apache Mesos, BlockBridge, and ClusterHQ help DevOps teams, testers, and other key players to manage the various aspects of container management.



Other relevant trends to look forward to in 2019 are serverless technologies and reinforcement of digital security.


Going Serverless


With the adoption of technologies such as containers and cloud computing services, developers and businesses are now also incorporating serverless computing technologies. Serverless computing technologies give developers and businesses the option to use cloud-hosted features on an on-demand basis, only using and paying for functions or applications when they need it. This reduces the redundant use of servers and optimizes the use of resources.



The most popular examples of server-less computing are Amazon Web Services’ AWS Lambda, Microsoft Azure Functions, and Google Cloud Functions.


Strengthening Security


With the increasing number of reported cases of data breaches and compromised systems all over the world, security has been and will be a priority for companies. As more and more operating standards and laws are established across the globe (such as the GDPR for example), systems and digital security will become paramount.



There are some aspects of digital security that developers need to account for. Having security planned for and built into the system from the beginning instead of an added feature later on is one of them, as it could save time and energy. Data encryption, data tagging, and data management have key roles in strengthening security. Refining and strengthening security later on is achievable with automation, microservices, encryption key management services, and other DevOps tools.



Application development processes and DevOps methodologies grow and adapt along with the evolution of technology. As demand for applications increases and becomes more complex, different styles and approaches are needed to take this space further.



Modern tools and methodology such as AI and ML in DevOps, enhanced digital security, server-less technology, and containers are but a few of the modern tools that enhance DevOps implementation.  Tools or approaches may differ, but the goal for application and DevOps services remains the same, and it is to be able to provide quality applications and systems that meet the needs of its users.



About the Author

Anastasia Stefanuk is a passionate writer and a marketing manager at Mobilunity. The company provides professional staffing services, so she is always aware of technology news and wants to share her experience to help tech startups and companies to be up-to-date.




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