Closing the observability gap for the AI-ready enterprise

The modern enterprise is a digital enterprise.

From the back office to the factory floor, connected systems and digital services form the operational backbone on which all else depends.

So when disruption hits, it can have a huge financial, reputational, productivity, and even compliance impact.

This has raised observability to a board-level issue.

"For a public company, a material cyber incident is a disclosure obligation.

You're on a four-business-day clock from the moment you determine its material," explains NETSCOUT director of enterprise strategy, Jack Callahan.

"So when you have a disruption, whether that's a cyber-attack, a DDoS attack, or someone pushing a bad update to the network, the first executive problem is the same: figuring out whether it’s material." With each technical team pointing fingers at each other, observability becomes the single source of truth that organizations need to identify root cause, accelerate resolution, and improve reliability.

Yet in many enterprises, it’s not having the desired impact.

The long-established data foundation of metrics, events, logs, and traces (MELT) can’t by itself keep pace with the complexity and scale of today’s digital infrastructure.

Organizations have defaulted to gathering more data, increasing sampling, and extending retention.

But they’re not getting better insight.

“Executives who would expect to have a lot of data in front of them with which to make a decision don't always find that that data is as conclusive as they'd want it to be,” Callahan continues.

“And therefore, they’re trusting their gut more than they’d expect, given how much they’re spending.” The costs of this observability debt are building.

One study by NETSCOUT reveals that 81 percent of organizations believe insufficient data increases incident resolution time.