In a world of ever-changing customer choices, only a handful of technology companies achieve customer satisfaction and exceed business expectations every time. Innovative business strategies, supported by careful implementation of DevOps, help these companies achieve measurable and consistent results as they develop, launch, and improve new products. DevOps solutions help enterprises automate their software development and testing lifecycle by standardizing and automating code migration and deployment in many environments. With these solutions, developers can implement continuous feedback loops, reduce response times, and continuously deliver software based on customer feedback and usage patterns. In short, it provides a one-click deployment feature that allows you to push code check-ins to production. This article will help you identify the latest DevOps outsourcing trends that will accelerate the pace of innovation and digital transformation in 2022.
DevOps trends in 2022
Automation
According to this 2021 State of DevOps report, sophisticated enterprises are implementing a wide range of automation modes in their processes. The report also shows that 90% of respondents implementing DevOps best practices previously automated up to manual cycles. To successfully implement infrastructure automation, you need to do the following:
You can comfortably write automation code
Use a version control system such as GitHub to push code from a system administrator or IT operator to a programmer, or instead of the above, use a professional cloud management platform that can automate cloud infrastructure processes to the maximum.
For organizations that are not considered sophisticated, these initiatives are only more urgently accepted. To achieve this, teams need not only to work on automation of the entire pipeline but also the willingness to integrate AI and ML. By applying ML to the deployment lifecycle, organizations can understand where block or capacity issues are occurring. With this knowledge, you can better mitigate the problems you encounter. AI-based predictive analytics can make your DevOps pipeline smarter in two ways:
Predict the problem
Providing possible solutions
Continued cloud adoption
Even before the pandemic made a difference, most organizations had already taken steps to adopt a more cloud-centric infrastructure to support cloud-based workflows and applications. Given the urgent adaptation and need for adaptation in the industry, this change had to happen even earlier than originally planned. However, using the cloud alone does not make a company highly developed. According to the recently released Puppet 2021 State of DevOps report, the majority of DevOps teams are using the cloud, but most teams aren’t using the cloud enough. The results show that:
65% of organizations that are considered to be evolving are using the public cloud. However, only 20% of them are maximizing their potential. For those who want to improve cloud adoption, it can be beneficial to consider different types of clouds. Teams using hybrid or multi-cloud software deployments are 1.6 times more likely to meet their organization’s performance goals than teams using traditional cloud strategies, according to the results of the 2021 Accelerate State of DevOps survey. It turned out to be expensive.
MLOps and ALOps
Companies are constantly collecting/creating data, so this overwhelming amount needs to be intelligently organized and analyzed. Old-fashioned data science solutions can’t keep up with the amount of data generated. That’s where machine learning and artificial intelligence come in. MLOps / AIOps brings CI / CD and automated infrastructure provisioning to machine learning and other AI model learning algorithms. These new techniques provide insights into a vast data pool that automatically provides insights into problems, their causes, and solutions to fix them. Both AIOps and MLOps wrapped platforms are particularly attractive in DevOps spaces because they provide the visibility and automation needed to accelerate processes and reduce inefficiencies.
Prioritizing security
With so many employees working from home over the past year and in the future, organizations are beginning to realize that a secure software supply chain is no longer an option, but a need. And this security cannot simply be added after the fact. Rather, security should be injected as secure code at all layers to quickly identify and mitigate vulnerabilities.
DevOps engineers need to adapt and modify the way they create software to ensure it is safe not only when it is created, but also when it is deployed. Here are some ways to get started with DevOps security prioritization:
Understand your security goals
Use the appropriate cloud vulnerability scanner
Code protection with standardized test
DevOps innovation continues
Regardless of what happens to workers and organizations, DevOps outsourcing will always evolve and swing how. Companies can use innovative technologies to get opportunities to use current challenges as a way to trust skilled workers. Those skilled in the art can ensure that other DEVOs are consistent with many years through the enclosure of these top DevOP trends.
