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Why are there So Many Monitoring Tools?

I spend a lot of my time at conferences and there’s one question I often hear with increasing frequency: Why are there so many monitoring tools?

Looking around the vendor area at any conference, I see loads of monitoring tools and companies, and attendees are often overwhelmed by the sea of options. How can all of these tools be different and/or better than the other? The problem starts with the way we talk about monitoring.

What does monitoring really mean?

Monitoring is a pretty vague term: I can monitor my deployments, my application performance, and the cupcakes baking in the oven. It’s more important to ask ourselves, “What problem are we trying to solve through monitoring?” I can buy a fire extinguisher because my cupcakes keep burning, or I can buy an oven timer so I remember to take them out of the oven. Simply put: there are a lot of monitoring tools because they solve a wide variety of problems. To differentiate and find value in the tools available, we have to know what problem we’re trying to solve. A lot of us have to address downtime in our systems, so we turn to monitoring solutions after some catastrophic failure. Others turn to monitoring to solve the tricky issue of resource allocation: there are entire consultancies built around which services use the most resources and how we can optimize them. Others still use monitoring data to forecast sales in order to better measure the accuracy and success of their systems.

Monitoring is so important because businesses and technology both survive on the premise that our services are available for as much of the time as possible. System uptime means community engagement and sales and relationships being built. There’s an abundance of monitoring tools because different systems and types of data require different approaches. Let’s talk about how you can start pruning the landscape.

How do I find the right monitoring tool?

To find the monitoring tool that fits your needs, here are a few questions to ask yourself:

What type of data do you want to monitor? Are you gathering metrics, events, logs, user data, a combination of these or something else entirely? Different types of data have different requirements for how we collect, store and analyze them. Look for tools made specifically for your type of data so you spend less time on setup.

What is the source of your data? Is your data being generated by IoT sensors, web browsers, AWS or local servers? When choosing a monitoring tool, make sure it fits easily into the pipelines that already exist. Some tools are made specifically for the cloud while others are made for industrial IoT machinery. If you’re using a combination of data sources, you might have to think about a flexible collection agent.

Do you have performance requirements? If you have limited resources or strict performance requirements, you can’t always instrument your applications with a full suite of monitoring tools. Find out how much work you have to do to optimize the tool. Look for benchmarks, user stories and hardware requirements.

These are just a few questions to get started, and hopefully, researching these will lead you to even more questions. Don’t be afraid to ask companies how their products are different — these are the questions that allow each monitoring company to show you its strengths. Here are a few questions you can start with:

  1. What type of data is the tool built for? Purpose-built solutions that match your data will be an easier transition.
  2. What ecosystem is the tool made to run in? Some tools are built specifically for a cloud-only environment while others are made for bare metal servers.
  3. Do you have an open source version or a free trial? There are a lot of pitfalls when it comes to implementing monitoring solutions, and being able to test them out before any money is involved is so much nicer.
  4. Bonus: I like to ask the person I’m talking to what their favorite feature of the product is. It can be surprising and enlightening!

Get out there and start asking questions.

About the Author

Katy Farmer is a developer advocate at InfluxData. She loves to experiment with code, break stuff and try to fix it. She learned to code at Turing School of Software and Design in Denver, and it gave her the perfect chance to break stuff before she knew how to fix it. She lives in Oakland, CA with her husband and two dogs (at least one of whom talks to her about fun, technical stuff). 

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