Your Root Cause Analysis is Flawed by Design

There’s a nagging feeling of déjà vu that haunts every network operations leader. You invest significant time and resources to resolve a major performance issue. Your best engineers isolate a culprit—a misbehaving load balancer, perhaps—and after a frantic effort, service is restored. You close the ticket, confident the problem is solved. Then, two weeks later, it’s back. The symptoms are slightly different, the affected application may have changed, but you know, deep down, it's the same ghost in the machine.

This cycle isn't a sign of incompetent teams. It's the result of a fundamental flaw in how we approach troubleshooting. We are victims of a powerful statistical bias, one that ensures we are destined to solve the wrong problems with remarkable precision.

Here’s the issue: We look for answers where it's easiest to look, not where the answers actually are.

Searching for your keys under the streetlight

There's a classic parable that perfectly illustrates this dilemma. A police officer sees a man on his hands and knees under a streetlight and asks what he's doing. "I'm looking for my keys," the man says. The officer helps him search for a while with no luck. Finally, he asks, "Are you absolutely sure you lost them right here?" The man replies, "Oh no, I lost them in the park, but this is where the light is."

This "streetlight effect" is the single biggest source of errors in network root cause analysis today. Your "streetlight" is the infrastructure you own and control. It’s your corporate data center, your LAN, and your managed WAN links. This is the domain you have brilliantly illuminated with an arsenal of sophisticated monitoring tools. It’s where you have logs, metrics, and alerts. It is data rich, familiar, and, most importantly, the only place your teams have the direct power to make a change.

This is where our mental model breaks down. The keys—the true root cause of most modern application issues—are rarely in that well-lit area anymore. They’re lost somewhere in the darkness: The mess of ISP networks and cloud interconnects that you depend on completely, but don’t manage at all.

When an application hosted in the cloud slows down, your monitoring tools, blind to this external world, can only report on the symptoms they see under their light. They might see a spike in latency on your internet edge router or a surge in TCP retransmissions. And so, your team, guided by the available data, declares that the router is the problem. They have found a correlation with absolute certainty, but they have completely missed the causation—a congested peering exchange two countries away.

The inefficiency of finding the wrong answer

This inherent bias leads to a state of operational psychosis. You spend millions on tools and talent to get faster at finding answers, but the answers themselves are flawed. This has two corrosive effects:

• First, it traps your most valuable engineers in a reactive loop. They are not solving problems; they are chasing symptoms. They reboot a device or tweak a policy, the immediate symptom subsides, and they declare the issue fixed. But because the underlying cause in the external network remains untouched, the problem is guaranteed to return. This is why you have that feeling of déjà vu.
• Second, it fuels a culture of blame. When the network team is challenged to prove the network is innocent, the only evidence they can provide is from their own well-lit area. They have no data to definitively implicate an external provider. This lack of evidence makes them the default scapegoat in any cross-domain dispute, forcing them to waste their time defending their turf instead of solving strategic problems.

Engineering a better light

You cannot fix this bias by simply trying harder. You can only fix it by fundamentally changing the way you see. You have to extend the light.

This is the entire premise of network observability. It is a strategic departure from traditional monitoring, designed specifically to eliminate the streetlight effect. It’s about gaining a consistent, evidence-based view of the entire service delivery path, especially the parts you don't own.

Instead of just watching your own devices, observability solutions trace the journey hop-by-hop across the internet, measure the performance within the cloud provider's network, and give you the empirical data to see what’s really going on. They provide the context to know that the spike on your firewall wasn't the cause, but merely a symptom of packet loss occurring three hops away inside a provider's network.

This is how you break the cycle. It allows you to move the conversation from one of blame and guesswork to one of data and shared reality.

So, take a hard look at that recurring problem. Was the cause truly the device your team identified? Or have you just gotten exceptionally good at searching for your keys under the streetlight?

Now’s the time to discover how you can extend your visibility across the complex multi-cloud paths where the real answers lie. Explore what true multi-cloud observability looks like.