From RV Tank Levels to Application Monitoring: A Journey into Observability

It was 5:30 AM when our daughter's voice pierced through the pre-dawn quiet of our temporary RV home. "Why is water backing up into the shower?" It's not exactly the wake-up call I was hoping for while we navigate life during home repairs after a flood. As I stumbled out of bed, my mind immediately went to where any self-respecting IT professional would: troubleshooting mode.

First step: check the system status. In RV terms, this means manually activating the tank level indicators. Lo and behold, our grey water tank was showing full. For the uninitiated, the grey tank handles all the wastewater from sinks and showers – everything except the toilet (that's the black tank, and trust me, you don't want to mix those up).

Standing there in my pajamas, I couldn't help but channel my inner Cousin Eddie from "Christmas Vacation." You know the scene – him emptying his RV's tanks into the storm drain while wearing his bathrobe, cheerfully waving to the neighbors. "Merry Christmas! The grey tank's full!" In this case, our hoses are plumbed into the appropriate sewer line and it's a pretty civilized process, but this early morning adventure got me thinking about observability in our systems – both mechanical and digital. Here I was, a technology professional with years of experience managing complex infrastructure, caught off guard by something as basic as a full water tank. The irony wasn't lost on me.

Living in an RV has been a humbling experience, forcing me to think about systems I'd previously taken for granted. In our house, I never had to worry about water tank levels or power consumption from a limited electrical system. The infrastructure just... worked. Until it didn't, courtesy of Helene.

What struck me most was the complete lack of automation or proactive notifications about these critical systems. There was no alert when the tank reached 80% capacity, no trending data showing our average daily water usage, no predictive analytics suggesting when we might need to plan a trip to the dump station. Instead, we had to actively remember to check these systems regularly, adding more cognitive load to an already stressful situation.

Sound familiar? If you're managing application infrastructure, it should. This is exactly the kind of situation we work to avoid in our technical systems through proper observability practices. Yet here I was, living with the equivalent of manual polling and reactive monitoring in our temporary home.

The parallels to application infrastructure are striking

Just as our RV's basic tank level indicators only show current state (and not very accurately at that), many organizations still rely on simple up/down monitoring of their systems. They only know there's a problem when the metaphorical shower starts backing up – when users are already impacted.

The manual process of checking tank levels is like logging into different systems to check various metrics. Sure, it works, but it's inefficient and prone to human error. What happens when you forget to check? Or when you're not around to check?

The lack of historical data means we can't identify patterns or predict issues before they become problems. Are we using more water on certain days? Is the tank filling faster than usual, potentially indicating a leak? Without proper observability, we're just guessing.

This experience has reinforced several key principles about observability that apply whether you're managing RV systems or infrastructure:

Proactive vs. Reactive: Don't wait for the shower to back up. Implement comprehensive monitoring that alerts you to potential issues before they impact users. This means moving beyond simple metrics to understanding the full context of your system's behavior.

Automation is Key: Manual checks don't scale, whether it's RV tanks or microservices. Automate your monitoring and alerting systems to reduce cognitive load and ensure consistent oversight.

Historical Context Matters: Point-in-time measurements only tell part of the story. Collecting and analyzing historical data helps identify trends, predict future issues, and understand what "normal" looks like for your system.

User Experience is Everything: Just as our daughter didn't care about tank levels until her shower was affected, your users don't care about your metrics – they care about their experience. Focus your observability efforts on metrics that directly impact user experience.

As we continue our temporary RV adventure, I'm seriously considering adding some sensors and automation to our tank monitoring system (most likely hacking it myself with Home Assistant). But more importantly, this experience has reminded me why we invest so heavily in observability for our technical infrastructure. Because whether it's grey water or application traffic, knowing what's going on in your systems – and knowing before things go wrong – is crucial for maintaining a smooth operation.

Now, if you'll excuse me, I need to go check those tank levels again. Some metrics you just can't automate... yet.

Author's Note: As someone currently displaced from their home, our hearts goes out to those affected by the recent Los Angeles wildfires. While our situation is temporary, many families have lost everything. If you're able to help, please consider donating to the Red Cross at redcross.org/donate or your preferred charity to support those impacted by these devastating fires.

Update: Additional was to help can be found in this article: https://lnkd.in/g_keUvKq

F5 Employees can make matching contributions here: https://lnkd.in/g9gzg34h