Let’s state the obvious: change is a constant in IT. The established tools, processes, people, and mindset that we’ve counted on to achieve our goals in IT are changing so rapidly they could be rendered obsolete tomorrow. While this fast-paced environment enables us to thrive, it can also be a double-edged sword.
Application performance management (APM) is a good example.
Across the globe, companies are undergoing digital transformation initiatives to keep pace with market opportunities and customer expectations. To make the transformation, they’re implementing new, ephemeral technologies that will help them move faster, but the very dynamic nature of those technologies and the applications that run on them is adding managerial complexity and increasing the risk for outages.
APM: A Brief Look Back
While deploying and instrumenting an APM tool has never been easy, it used to be clear cut. You knew which applications were critical to your business, so it was easy to decide which ones to instrument. You knew where they were running, so you knew what infrastructure to monitor. And neither your app nor your infrastructure changed very often. So, when something did change, you knew about it (assuming, of course, you had change management processes in place!). If you made a change and broke something, it was relatively easy to find and fix the issue before it caused a massive outage.
Old school APM solutions were built to monitor old school infrastructure and application designs.
But that was then; this is now.
Those same APM solutions aren’t adequately equipped to deal with the modern IT ecosystem—which is highly complex, short-lived (ephemeral), and interconnected. Now, the weakest link in the chain doesn’t just harm the chain, it could damage your entire organization.
APM For Today’s Application Stack
Today’s application stack is hyper-dynamic, featuring technology that’s capable of appearing one minute and vanishing the next. With increased levels of activity coupled with increased interconnectivity between the applications and infrastructure, it’s no longer feasible to pick and choose which apps and infrastructure to monitor. Today’s new demand is to monitor it all. But the challenge is how to accomplish this without the crushing overhead that traditional APM involves.
To be clear, there’s still a place for traditional APM. But incorporating new technologies and adopting modern application architectures requires a more comprehensive and intelligent approach to monitor them.
You’ll need AI-powered APM or artificial intelligence for IT operations (AIOps).
AIOps is a framework that applies various forms of automation and machine learning/artificial intelligence to make sense of large volumes of data, so you can drive intelligent automations and empower operations to move at machine speed.
It’s AIOps’ ability to identify operational patterns that’s driving the evolution of APM.
Each interaction between elements within the stack creates data and patterns that are produced at such high velocity and volume it’s impossible for humans to keep up. But that data is worth its weight in gold – if you know how to mine it – and here’s where AIOps comes into play
- Assumes everything is critical—consolidates app and infrastructure data into an operational data lake
- Leverages machine learning to manage complexity by identifying patterns and establishing contextual relationships within and across infrastructure and application components
- Employs automation to keep pace with change
- Focuses on business outcomes based on contextual relationships
As IT continues to evolve and new technologies emerge that afford companies with greater digital dexterity, APM cannot merely keep pace with the change; it has to be miles ahead. After all, this isn’t your older sibling’s APM anymore – its changed. We’re ready, are you?