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AIOps – The future of DevOps

DigitalOnUs - April 18, 2018 - 0 comments

Technology adds a zing to our lives by improving quality, adding convenience and automating routine tasks. Artificial Intelligence (AI) adds zing to DevOps. AIOps, as we like to call it is set to be the game changer in the DevOps world with increased speed of response, addition of business context and boosting effectiveness of DevOps. For example, we have encouraged DevOps organizations at the leading edge of technology adoption to chase self-provisioning infrastructure for application deployment. Here is how we believe, AIOps will transform DevOps as we know it:

  • Managing a complex DevOps Pipeline – The next generation of enterprise applications run in an environment of multiple cloud services, multiple data sources and integrations with external apps and services. Building DevOps pipelines in such environments can be very challenging. The use of machine and deep learning algorithms adds nuances to managing DevOps pipeline by providing access to right data at the right time based on business context.
  • Revolutionizing decision-making in digital enterprises – AI overcomes the limitations of the human mind when it comes to velocity, speed and volume of Big Data that is streaming through daily operations. From root-cause analysis for quality issues to providing historical context, AI can exempt the burden of troubleshooting and real-time decision-making.
  • Sensible Log Data Entry – IT Operations and DevOps professionals spend considerable amount of time navigating through a sea of log entries to find critical events that triggered a specific event. Real-time and centralized log analytics helps them in understanding the essential aspects of their log data, and easily identify the main issues. With this, the troubleshooting process becomes a walk in the park, making it shorter and more effective, as well as enabling experts to predict the future problems. Many enterprises are already testing AI in enhancing efficiency of data log management.
  • Adaptive Insights –  Machine-learning algorithms make the DevOps practice adaptive to changing goal posts in agile or volatile business scenarios. Not only are insights available in real-time but processes can bend to target specific goals or metrics to amplify or just simply become more efficient.
  • Change the way teams see data – AI is altering the way DevOps organizations are analyzing and seeing data. Teams are shifting to a predictive model that is based on historical trends, business context across times and integrated view of data across DevOps tools. Business KPIs are now tracked along with key DevOps metrics.

The speed at which technology, tools and processes are evolving makes it difficult for enterprises to effectively cope with implementing a strong DevOps strategy. AI is set to transform how teams develop, deliver, deploy, and manage applications by offloading tasks to automation, and enabling humans to address other challenges. This makes it increasingly obvious that AIOps will become the new normal rather than the exception. It is this future that enterprises must recognize and transition to, sooner rather than later. We at DigitalOnUs are ready to help our clients make that transition with tools, technologies and innovations that deliver to scale, speed and quality. We invite you to join us in this synchronous journey of AI in DevOps and transform your business to a level previously unimagined.

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