Major Trends Driving DevOps Market Growth for Global Companies
Several trends are currently driving global DevOps market growth for global companies. Recently, many leading industry players acquired a variety of DevOps startups, including hybrid cloud, containerization and cybersecurity capabilities. These company acquisitions are ranging from $500M to over $34 Billion dollars from the major tech giants. Of course, these significant investments demonstrate the impact of DevOps on the tech and development industries. If you are in software development industry, you should pay attention to the latest DevOps trends to remain competitive in the market. In this post, we will discuss some major trends driving DevOps market growth for global companies.
Accelerated Security Processes
One major DevOps trend driving market growth is more rapid, accelerated security processes. Since DevOps accelerates software deliveries, security processes are required to move faster to keep up with thousands of new releases. Companies are taking a shared ownership approach to manage authorization, vulnerability management and authentication. Furthermore, a shared ownership allows developers to stay compliant with security policies while developing application components. This way, entire development teams can identify, fix and patch vulnerabilities at multiple endpoints. With these processes in place, you can defend your organization against even the most experienced cyber security incidents. The balance between development agility and security risk management make DevOps increasingly popular at the enterprise level.
Next, the rising usage of containerization solutions is driving DevOps market growth. These solutions offer much faster startup times than physical or virtual development machines. Additionally, containers leave smaller data footprints than non-containerized components. This frees up gigabytes for increased processing power or storage functionalities. Moreover, containers provide direct hardware access. By eliminating extraneous abstraction layers, container solutions accelerate development and processing tasks significantly. These capabilities make containers ideal solutions for IoT applications, big data, and on-prem systems, as well. Surely, advanced functionalities are necessary for DevOps enterprises to remain competitive.
Additionally, many global enterprises drive DevOps market growth with automated CI/CD pipelines. Continuous integration/continuous delivery pipelines automate DevOps processes from code to production. This automation streamlines and secures projects enterprise-wide. Moreover, a DevOps pipeline from JFrog provides comprehensive integrations with a variety of other tools. In fact, the steps within a pipeline can run on multi-architecture and multi-OS nodes. This way, they reduce tech stack bloat by eliminating the need for multiple CI/CD tools. Of course, this bloat reduction leads to increased resource efficiency within DevOps enterprises. Certainly, CI/CD pipelines offer a DevOps trend that accelerates, automates, and facilitates efficient software deliveries.
Application Performance Monitoring
Moreover, an additional DevOps trend encompasses application performance monitoring (APM). Developers use APM platforms to monitor deployments while gaining advanced performance insights. Some of these insights include user interaction checks, and application discovery or tracing. Additionally, many APM solutions use advanced algorithms to provide valuable analytics. Using these analytics, developers can predict and identify various anomalies within containers, databases, and microservices. While predicting and identifying these issues, they also gain more robust customer journey insights. Definitely, application performance monitoring delivers advanced insights to global DevOps companies.
AI and Machine Learning
Meanwhile, many global DevOps enterprises embrace real-world artificial intelligence and machine learning trends. These functionalities are necessary for DevOps enterprises to handle the drastic volume, variety, and speed of current data generation processes. An AI and machine learning DevOps approach allows enterprises to compute and analyze data on any size or scale. These capabilities lead to improved customer experiences, automation, and team collaboration within a DevOps enterprise. Developers leverage large scale data analysis like this for shorter release, bug identification, and issue resolution times, as well. Assuredly, AI and machine learning impact global enterprise DevOps process efficiency significantly.
There are many trends driving DevOps market growth for many global companies. Following the latest trends, you can stay ahead of the competition, continue to scale your business, and optimize your custom software development life cycle (SDLC). For example, the balance between development agility and security risk management make DevOps increasingly popular at the enterprise level. This way, businesses can defend against even the most serious cyber security risks. Additionally, the advanced functionalities of containerization solutions are necessary for DevOps enterprises to remain competitive. Moreover, automated pipelines offer a DevOps trend accelerating software deliveries. Meanwhile, application performance monitoring delivers advanced insights to global DevOps companies. Finally, AI and machine learning impact global enterprise DevOps process efficiency significantly. Of course, development enterprises around the globe embrace these trends to accelerate and automate their releases, while remaining competitive in their markets.
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