Applications are the lifeblood of any business. But they’re only as good as their ability to keep running and effectively serve end users and the business.
Downtime, application failures, and the associated scrambling around for a solution is never good. It costs businesses money. Modern Application Performance Management (APM), and observability platforms, enable enterprises to get on the front foot, fix problems before they impact customers and the business, and prioritise actions based on the business impact.
What is Application Performance Management?
First, a definition. APM is a set of tools that allow you to observe and manage all your application environments, the applications, what makes them run, the delivered user experiences and the business outcomes. It identifies the root cause of issues and quickly resolve them via automated or manual responses. It speeds up the time of responding to an application issue that needs attention. If done well, the end user might not even notice there was an issue in the first place.
Most APM solutions allow you to observe the front-end, back-end and infrastructure performance of your application. Front-end monitoring puts you in the shoes of the end user and shows you how they are experiencing the application. Back-end monitoring shows the performance of the services running in your data centers and cloud deployments supporting your applications and keeps it working in the way it should. Both include code-level visibility and the performance of middleware or third-party services integrated into the application. Then there’s infrastructure monitoring. This involves observing the servers, databases, network, and cloud services that the app is using.
All of these aspects of APM are important but they aren’t an exhaustive list of what these solutions can do. They have to be understood in a wider context to be really useful. After all, every business is different so the tolerances and expectations they have will differ from each other. The magic of APM really kicks in when the solution maps the technology stacks needed for the application to perform a specific function and monitor them to identify what normal looks like for monitored business transactions.
Once the system has created a normalcy reference, we call baseline, it can then determine when an application is deviating from it. When an issue is identified, the solution bundles the necessary information into a digestible format and alerts you to the problem so that you, as the IT team, can fix it efficiently. A typical example of this could be if the checkout stage of an ecommerce website has an average response time four times slower than the set baseline. In this instance, IT can quickly explore and address the causes of this delay to remediate the issue quickly, before it affects too many end users and risks shoppers abandoning their cart.
AI enabling proactivity
APM is improving and evolving all the time. One thing that is already clear is that traditional APM software that focuses solely on the manual resolution of issues is on the way out. The volume of data in IT ecosystems is ballooning and so even with real-time insights, IT teams will still struggle without the means of automating the process for finding and understanding the right telemetry data. The sheer quantity of alerts can make discerning the important information from the noise almost impossible, without the tools to highlight priorities and automatically resolve issues where possible.
Artificial intelligence for IT operations, or AIOps, has emerged as a technology that relieves the pressure on IT teams to manually manage systems. Its core elements consist of machine learning, performance baselining, anomaly detection and automated root cause analysis. And with an AIOps platform, you have a comprehensive framework that companies can use to integrate complementary technologies with their APM solution.
AIOps empowers IT teams to solve the right problems, at the right time. For example, if your cloud-based application has been configured well, you could automate the addition of servers to your infrastructure if your applications lack enough compute, storage or network tiers. This ecosystem benefits the APM customer by giving them both visibility and control across the entire IT landscape and the users and the business outcomes.
So far so good. But the only problem is, there’s never only one problem. A single application could have many issues happening at the same time and you can almost never tackle all of them at once. Prioritising so many alerts can be a nightmare. However, more advanced APM solutions can link application performance with business and user metrics. This allows organisations to see which issues are impacting the business the most and put them at the top of their to-do list. Observability solutions which correlate the technology performance with business outcomes will become increasingly important to modern enterprise organisations.
APM makes sense from a financial perspective when you look at both the operational expenses and preventing revenue loss. And there’s a bigger picture too. It keeps the end user fully connected, makes for a smoother customer journey and makes IT increasingly future-proof by reducing the need to use precious developer and ITOps hours on problem-solving, by providing them with the real-time information they need to prioritise and take action.
APM is a catch-all term but businesses should be rigorous in selecting the platform they decide to implement. A system that only offers manual solutions is short-sighted. AIOps based management delivers deeper automation to handle high volumes across technology stacks and sorting priority of actions according to business and user impact help focus teams on most impacting issues at hand. Pursuing the route that best utilises AI and machine learning, will deliver results quickly and by aligning on business priorities, IT teams are in the best possible position to innovate.