June Jitters and Observability Theater

If you squint, it all looks so darn promising. AI adoption is rising, observability is everywhere, telemetry is flowing, and vendors are tripping over each other to sell you solutions. But the closer you look, the more obvious it becomes that we’ve mistaken motion for momentum.

The AI arms race is real, but most of us are still firing blanks. This month’s data tells the story: complexity is climbing, trust is falling, and our shiny new tools are outpacing our ability to operationalize them.

AI Everywhere, Value Still Somewhere Else

Let’s start with the hype-to-reality gap.

Fortune reports that only 25% of organizations are seeing real ROI from their AI projects. That’s not “underwhelming”, that’s failure at scale. Expectations were sky-high, but what did we think was going to happen when we handed business users model playgrounds and called it strategy?

Add to that: 69% of employees in AI-heavy orgs now report burnout, decision paralysis, or both. Turns out, adding a chatbot to every workflow doesn’t solve decision fatigue. I know, right? How could that be?? Since chatbots became prevalent we’re often three drinks deep trying to convince a large language model that yes, Chicago is in the Midwest and no, you don’t want to hear about ancient Babylonian culture again. Unless it's commentary from Ea-Nasir, of course. But that's the exception that proves the rule that sometimes, engagement with chatbots is like arguing with a magic 8-ball that read Wikipedia, gaslit your logic, and still expects a five-star rating.

And the worst part? Even when you win… it thanks you for your feedback.

Welcome to the future. You’re not alone, but you are outnumbered.And while generative AI was supposed to free up time, the reality is that most teams now spend more time validating AI output than they ever did creating original content or code.

Observability is Not Insight

Yeah, I know. Yet another “uh, we already knew that” non-insight. But apparently, someone needs to say it again. So hi, I'm someone.

The Dynatrace + EMA OpenTelemetry report confirms what most ops teams already know: telemetry is everywhere, but understanding is optional. 96% say OpenTelemetry is central to their observability plans. But only 8% have actually implemented it end-to-end. It’s the classic case of everyone buying gym memberships and no one lifting weights.

Even worse, 53% of orgs still rely on partial or manually correlated telemetry. That’s not observability. That’s a glorified panic room with dashboards.

And when asked what’s blocking better observability, the top answers weren’t technical. Because they never are, are they? They were staffing, skills, and governance. In other words, your telemetry isn’t broken. Your org chart is.

Regardless, the idea that more metrics equal more clarity is a fantasy. You don’t need 17 panels blinking red, you just need three that matter. If your LLM fails to respond in time, do you know if it’s GPU memory, model queueing, or network flake? If not, your observability stack is just performance cosplay.

Why the 16 Billion Credential Bonanza is Terrifying

Cybernews uncovered 16 billion login credentials across 30 distinct datasets. Some files are fresh, some patched together from older streams, but all weaponizable

These include login URLs and credentials for major platforms like Apple, Google, Facebook, GitHub, Telegram, and more. Malwarebytes humorously points out that if you stacked them on paper, they'd reach 35 miles high above the stratosphere.

Now, if you aren’t afraid of that news, consider the stat from Fortinet, recently covered by TechRadar, revealing that automated AI-powered scanning activity has surged by 16.7% year-over-year, now reaching a staggering 36,000 scans per second. Attackers are aggressively probing RDP, IoT, SIP, and other exposed protocols earlier in the attack lifecycle than ever before.

This isn’t your neighbor’s port scan. This is a relentless, AI-owned wave relentlessly seeking every weak spot before you’ve even finished your coffee. If your perimeter security still thinks it’s 2015, you're lunch.

That’s credential data lake - no, not lake, ocean - isn't just data, it’s a blueprint for credential stuffing farms. AI isn't needed to crack passwords; it's already got the keys. Exploitation starts now.

Less theater, more answers.

This month’s data makes one thing painfully clear: the industry is in a state of strategic overconfidence. We’re adopting AI like it’s a shortcut and observability like it’s a checklist, all while the underlying systems groan under complexity we refuse to confront.

You want real gains? Then stop measuring AI success by feature count and start measuring it by operational reliability. Stop celebrating “telemetry coverage” and start demanding insight-to-action time. If your systems are observable but your operators are still confused, you haven’t solved the problem. You’ve just distributed it.

Until next month, stay informed, stay cool, and most of all, stay safe out there!