By combining the roles of software development and IT operations, DevOps (opens in new tab) often encompasses so many tools and skills that too many of us get stuck working in a complex and time-consuming environment. Time that could be spent solving problems gets wasted on mundane tasks. By using artificial intelligence (AI), DevOps can automate complicated tasks that are easy for computers but hard (or boring) for humans. AI can also help streamline processes across the software development lifecycle (SDLC), allowing DevOps to focus on the work itself. In this guide, we cover how AI can be used throughout the DevOps cycle to improve productivity and security.

DevOps is a software development and delivery process that helps in emphasizing communication along with cross-functional collaboration between product management, software development, and operations professionals. We've curated a list of the Top 12 DevOps Tools, along with their features, based on our decade-long experience in the IT industry, dealing with infrastructure for the significant part. We've taken great care in selecting, benchmarking, and continuously improving our tool selection. That apart, the article also covers the DevOps transformational roadmap as well as the step by step implementation guide. The popularity of DevOps, in recent years, as robust software development and delivery process has been unprecedented.

Every Site Reliability Engineer (SRE) knows that the more DevOps tools you use to ensure adequate monitoring coverage, the more likely you'll end up overloaded with alerts and data analysis tasks. Paradoxically, this avalanche of alerts and data might actually cause you to miss precisely the issues you are trying to identify. To help in this situation, SignifAI delivers powerful real-time and predictive insights to DevOps teams by correlating their event, log and metrics data using a combination of artificial intelligence, machine learning and the team's own expertise. SignifAI offers 60 integrations right out-of-the-box with technologies like AWS, New Relic, AppDynamics, Nagios and Pager Duty. The available integrations cover the most popular DevOps tools used for infrastructure, application, notification, collaboration and deployment tasks.

Every Site Reliability Engineer (SRE) knows that the more DevOps tools you use to ensure adequate monitoring coverage, the more likely you'll end up overloaded with alerts and data analysis tasks. Paradoxically, this avalanche of alerts and data might actually cause you to miss precisely the issues you are trying to identify. To help in this situation, SignifAI delivers powerful real-time and predictive insights to DevOps teams by correlating their event, log and metrics data using a combination of artificial intelligence, machine learning and the team's own expertise. SignifAI offers 60 integrations right out-of-the-box with technologies like AWS, New Relic, AppDynamics, Nagios and Pager Duty. The available integrations cover the most popular DevOps tools used for infrastructure, application, notification, collaboration and deployment tasks.