Monitoring sprawl explained
As it turns out, a website outage is in progress; your customers are unable to log into your web application. The company is, for all intents and purposes, stopped. The engineers present are all trying to pinpoint the root cause of the issue. Because each of them work in a different team and on a different technology stack, they have all brought their own tools to the party. Now, they are trying to correlate the data in their tool with the information in the other tools, in an effort to piece together the complete picture. You wonder how you ever got here. This situation is described with the word "monitoring sprawl."
How does monitoring sprawl arise?
Akin to urban sprawl, monitoring sprawl describes a situation where developments have taken place over time to create a chaotic and haphazard situation without any apparent structure or reason. If your working environment feels the same, you are not alone. Different tools and technologies appear in any growing technology organization. Even if the work they do is, on the surface, very similar, every department has their tooling preferences. These can be personal preferences ("Bob prefers open-source tools") or driven by technology choices ("Microsoft technology is best monitored with Microsoft tools"). Sometimes they may even be driven by rules and regulations or business considerations ("This monitoring tool comes for free with our enterprise license").
Why is monitoring sprawl a problem?
As long as you consider each department in isolation there is nothing wrong with this situation. So what if the database team uses their own monitoring tool that is different from the others? The right tool for the right job, right? Sure, if all you have to worry about is your own piece of the puzzle, then you're fine. This breaks down when you realize that IT systems these days cross silo boundaries and rely on lots of technical components to do their job. If you need to piece together what is going on in your landscape, you'll need to combine and correlate information from your separate silos and separate tools make this job very difficult. Meanwhile, your customers don't care how you've organized your IT systems, they just want your service to work so they can get their job done.
Thinking about a solution
Making sense of complex IT landscapes is a difficult and specialized job that requires piecing together data from the separate technology silos. It requires intimate knowledge of each tool and how the information in there can be extracted. It requires establishing a common vocabulary so that the information from the separate tools can be related to each other. It requires a tool that can scale to handle all the combined information. And it requires a tool that makes it easy to monitor and troubleshoot issues in your IT landscape. Fortunately, we at StackState have already done the hard work for you. We defined a common vocabulary called our data model, so all sources of information speak the same language. We built 80+ integrations with the most common infrastructure and monitoring tools available. StackState's full-stack observability platform is built on scalable open-source technology and scales to enterprise level. And finally our unique GUI and Artificial Intelligence blends Topology, Telemetry and Time to make it super easy and flexible to find what's wrong and what to do about it.
Want to learn more?
If you want to start consolidating your current data into one unified platform, it is crucial to understand your current level of monitoring. In our Monitoring Maturity Model, you will learn your current level of monitoring maturity and how to take your organization to the next level.
