The way teams deliver and operate software has evolved rapidly over the past decade. As a result, the surface area that IT operators have to manage is expanding just as quickly—in size and complexity.
While change was once considered a liability in the world of infrastructure, it’s now become the basis of competitive advantage.
You’re adopting DevOps practices to ship infrastructure and applications faster and more frequently. You’re modernizing your applications to achieve better velocity, scalability, and performance. You’re moving to the cloud. You’re adopting microservices. You’re running container orchestration systems like Kubernetes.
Rapid, relentless change is now baked into the very fabric of infrastructure management.
More changes to software, more configurations, more alerts, more everything. And at the same time there’s more pressure to detect and resolve problems faster, as well as to ensure the stability and reliability of production systems.
The complexity that we’ve created in the name of speed and scale has resulted in the need to shift left in monitoring strategies. The fact is that in many cases you won’t know how your system is going to behave until it’s in production, and that requires a system that’s observable in production.
This change in approach helps teams to stay on top of their dynamic systems.
The problem is, different teams frequently use different tools to monitor their parts of the stack. One tool for developers, one for IT operators, one for business managers; one tool for logs, one for metrics, one for traces, one for on-prem, one for cloud.
In each case, the tool adopted is no doubt the right one for the team.
But in practice, it also means every team is now dealing with more alerts, more telemetry, and more critical—but fragmented—operational data.
That’s the problem with tool sprawl: fragmented observability is not observability at all.
Each tool only shows you part of the picture, but in reality, the full picture is dynamic. Lines blur between parts of the stack. An application crashes and you need to find out what happened in the code or infrastructure before the damage spreads, but suddenly using disparate point solutions for each system component is costing you time and money.
Your data ends up trapped in silos; every tool has a different vocabulary and so teams are at cross-purposes; and crucially, it hurts your MTTD and MTTR.
The thing is, the costs aren’t just financial. They have a waterfall effect across the business. IT and ops teams spend too much time troubleshooting and not enough innovating. Alignment and collaboration between teams suffers. Employee morale suffers.
The business suffers.
In this guide, we’ll look at all the ways in which tool sprawl can hurt your business. But we’ll also look at the world of possibilities that opens up for your teams when you overcome it.