Not a decade ago, we in the cloud-native and DevOps communities were busy planting our flags on the summit of observability. We got the three pillars — metrics, logs and traces — stitched into our tech stack, surrounded by a constellation of CNCF projects. Prometheus, Grafana, OpenTelemetry, Fluentd… observability suddenly became foundational to modern software delivery. Conference talks, blog posts and hiring wishlists echoed the refrain: “You can’t manage what you can’t measure.”
And yet, here we are in 2025, drowning in dashboards, buried under a tidal wave of alerts, and still getting blindsided by incidents. We’re observing more, but are we acting any smarter?
It’s time for a reckoning: Observability has plateaued, and the next real leap in platform engineering isn’t gathering more data. It’s transforming that telemetry into trustworthy, meaningful, and — most crucially — automated action.
How We Got Here: The Data Dilemma
Let’s call it like it is: First-gen monitoring was all about green lights and red alerts. If Nagios chirped, someone would SSH in and poke around. As architectures shifted to microservices and Kubernetes, we needed more: not just “Is it up?” but “What the heck is really happening in this web of containers?”
So we built the observability machine. Prometheus fed us metrics, ELK and Fluentd indexed our logs, OpenTelemetry and Jaeger traced the lifeblood of distributed services, and Grafana let us slice and dice it all with gorgeous dashboards.
But success has its own pitfalls. When every team has its own dashboards—and its own take on what “matters”—you get sprawl, siloed insights and a cacophony of noisy alerts.
As the latest Futurum Research reveals, 78% of platform engineers report “alert fatigue” as their number one contributor to on-call burnout. Even more telling, 65% say their mean time to recovery (MTTR) hasn’t materially improved despite investments in “advanced” observability tooling.
The Actionability Cliff: When Data Isn’t Enough
Here’s the uncomfortable truth: Today, observability too often stops at the point of collection.
– Alert Fatigue: Engineers are overwhelmed by pings, the vast majority of which don’t require urgent human intervention.
– Dashboard Sprawl: Everyone’s got panels, but precious few see the business outcomes.
– Correlation Gaps: Logs, metrics and traces still, in 2025, often live in silos — leaving the puzzle piecing to humans.
– Stalled MTTR: Despite growing mountains of telemetry, downtime metrics stubbornly refuse to budge.
It’s not that we can’t gather data — it’s what we’re not doing with all of it. Information *without* action isn’t insight; it’s overhead. This, folks, is the actionability cliff, and too many organizations are teetering on the brink.
The Shift: Observability as the Heart of Platform Engineering
Nowhere does this transition matter more than in platform engineering. Your Internal Developer Platform (IDP), your paved golden path, your promise to developers — it all hinges on feedback loops that are meaningful and automated, not just noisy and pretty.
Developers don’t want to spend their days staring at dashboards or deciphering logs. They want their platforms to tell them, in plain English:
– Did my deployment succeed?
– Is my code causing user pain?
– What should I do—right now—to fix it?
This is where observability must evolve within platform engineering. You don’t just surface issues; you guide action, or even take action automatically. Imagine this: If a canary release fails, your platform rolls it back instantly. If an anomaly pops up in SLO error rates, your platform halts new rollouts, flagging the precise microservice in question, with a prescriptive fix suggested by a model trained on years of incident data.
The latest Futurum Platform Engineering & Observability Study shows the impact:
Organizations adopting “actionable observability” and closing the loop between telemetry and remediation see a 47% reduction in incident response times and a 32% improvement in developer productivity metrics.
Real-World Action: From Watching to Doing
We’re seeing this shift play out, right now:
– OpenTelemetry, 2025: Now equipped with semantic context, OTEL unifies logs, metrics, and traces—making correlation a one-click affair, not a week-long slog.
– Smart Pipelines: Tools like Keptn and Argo Rollouts (with their cloud-native resurgence in 2025) use observability signals to drive automated canary analysis and progressive delivery, reducing human error and toil.
– AIOps Goes Mainstream: AI-driven observability, per Futurum’s 2025 survey, is now in production in over 64% of cloud-native enterprises. These systems automatically spot anomalies, suggest remediations, and trigger workflows—freeing engineers for higher-value work.
Shimmy’s Take: Don’t Just Observe — Act
I’ve been in this industry long enough to remember when “actionable intelligence” was just a dream. For years, collection masqueraded as control; drowning in logs was mistaken for being in command. And sure, the dashboards have never looked better.
But here’s the bottom line: If you’re not automating the next step, you’re just admiring the chaos in 4K. Actionable observability isn’t icing—it’s the whole cake. And platform engineering is the perfect place to bake it in, by design.
Navigating the Risks: Automation With Judgment
Let’s not get carried away by the vision. Too much automation, especially when the system is a “black box,” can create its own disasters:
– False positives can roll back healthy releases or cause unnecessary outages.
– Engineers are slow to trust what they can’t see—or can’t explain.
– Complex incidents still need “human-in-the-loop” judgment.
The goal isn’t to automate humans out of the loop — it’s to automate the noise, so humans can focus on strategy. Per Futurum’s 2025 pulse, leading orgs keep a “human override” option and invest in explainable AI to build trust in automated decisions.
Closing Thoughts: See Less. Do More.
Observability got us the visibility. Platform engineering gives us the opportunity to make that visibility count — by closing the loop from data to action, elevating developer experience, and tying system health directly to business outcomes.
The future isn’t about building *more* dashboards. It’s about building platforms that act when it matters and empower people when it counts.
Because at the end of the day, nobody gets promoted for collecting more data. You get promoted for delivering reliability, velocity and real business value. And, in 2025, that means making observability truly actionable — by design.