Working with over 2,000 customers globally, Dynatrace aims to help some of the world’s biggest brands to tackle cloud complexity and deliver better business outcomes.
Andi Grabner, a self-proclaimed DevOps activist who works for the software intelligence company, is the Director of Strategic Partner Enablement at the firm. He says his mission is helping developers, testers and operations teams become more efficient at their jobs by applying DevOps practices. In an exclusive Q and A with DevOps Online, he discusses how AI and DevOps are coming together and companies can do to make the most of it.
What’s the difference between the traditional monitoring and modern needs?
Businesses need to understand their IT environment and how changes, or performance problems, affect the user experience. When you look back at traditional monolithic architectures, it was a solvable challenge, as the number of moving parts was known. However, today’s enterprise cloud environments are exponentially more dynamic, with more moving parts and a complex web of dependencies that is far more difficult to map and understand. Research has shown that a single web or mobile application transaction now crosses an average of 37 different technology systems or components.
As a result, traditional approaches to performance management have become largely redundant for IT teams, as they struggle to make sense of conflicting insights from countless monitoring tools and dashboards, each covering only a small fraction of the overall distributed system. It’s impossible to monitor modern user experiences with metrics that don’t have the full context from across the entire IT stack, which is why traditional monitoring is so outdated. Software intelligence led approaches that have AI and a common full stack data model at the core can provide instant answers into user experience in real-time and identify the precise root cause of any problems that arise, allowing IT and digital business teams to quickly resolve performance issues.
Why has AIOps become much more important for organisations?
Every company is transforming into a software company, because applications now lie at the heart of every user experience. The way that companies win customers and retain their loyalty lies in their ability to offer seamless digital experiences and bring new features to market. This means that for all businesses, speed is of the essence. If you develop too slowly, the competition will overtake you and steal market share. Organisations have to break up monoliths into smaller focused business applications and services. Leveraging AIOps helps remediate problems quicker and allow for faster development and deployments by removing the fear of failure. Ultimately, the race is on to be able to deploy lots of high-frequency releases at scale without introducing bugs that hinder the user experience, which is why AIOps has become such a hot topic.
What’s the key to ensuring organisations can trust AI?
AIOps is about leveraging the insights that comes from real-time, high-fidelity IT performance, scalability, architectural, user experience and business data that is flowing through the organisation and then combining it with smart auto remediation capabilities to trigger automated responses that improve outcomes for the business. Once you see AI alerting you to problems based on this data, that means that you can trust it to help you to automate traditional operational tasks. The culture is about trusting and leveraging AI so that you can focus on helping your company automate more, increasing the time for innovation and improving the outcomes for customers.
How do you see the role of operations changing in the future?
AIOps is set to cause huge changes within organisations, as infrastructure and cloud orchestration layers provide the requisite ingredients to facilitate autonomous operations and enable self-healing applications. As AIOps becomes the modus operandi for many IT departments, operations teams will become engineers with development skills that can mentor and help development teams architect and build better cloud native applications that can leverage the full potential of AIOps. This change in the operations skillset will help the development team ensure the code they are delivering is performant and build in remediations that kick in should problems occur.