The observability industry reached an inflection point in 2025. As costs spiraled and complexity mounted, organizations found themselves trapped between two impossible choices: accept eye-watering bills for telemetry they didn’t need or fly blind through increasingly complex infrastructure.

At Apica, we saw this crisis coming years ago. That’s why we built our entire approach around two core principles: OpenTelemetry as the foundation, and intelligent data processing at the edge through our Flow pipeline. While the industry is now scrambling to address the “economics problem” that has plagued observability, these principles have guided our architecture from the start.

The Cost Crisis Is Real, and It’s Getting Worse

The numbers tell a sobering story. Up to 84% of observability users struggle with costs and complexity, according to Gartner. Organizations routinely face surprise bills exceeding $130,000 per month. As Tom Wilkie, CTO at Grafana Labs, puts it in a recent article in The New Stack: “The core issue is that the economics of observability have been upside-down for years. Costs grow linearly with telemetry volume, but the value doesn’t.”

This isn’t just a pricing problem; it’s an architectural one. The traditional “big data lake” model encourages teams to ingest everything, index everything, and retain everything. You pay for volume, not insight. And as your infrastructure scales, your observability costs scale even faster.

Why We Chose OpenTelemetry Early

When we architected our platform, we made a deliberate choice to embrace OpenTelemetry as our instrumentation standard. Not because it was trendy, but because we understood what the industry is only now beginning to accept: vendor lock-in and proprietary agents were killing observability adoption.

OpenTelemetry solves the fundamental interoperability problem. As Bob Quillin, founder and CEO of ControlTheory notes in the same The New Stack article referenced above, “Using an open source tool built on these standards allows for a less commercial, more authoritative conversation about the broader problems in the industry.”

For our customers, this means:

Freedom from vendor lock-in. Your instrumentation isn’t tied to any single vendor. You can route telemetry wherever it delivers the most value.

Lower barriers to entry. Teams no longer wrestle with vendor-specific SDKs or proprietary collection agents. OpenTelemetry works consistently across languages and environments.

Future-proofing. As OTel continues to mature and gain adoption, you’re invested in an open standard rather than a proprietary ecosystem.

But here’s what the industry is still learning: OpenTelemetry solves instrumentation and interoperability. It doesn’t solve the cost problem. That requires something more.

Flow: Intelligent Processing Before Ingestion

This is where Apica Flow fundamentally changes the equation. While traditional observability platforms charge you to ingest, index, and store everything, Flow processes and optimizes your telemetry data before it ever reaches storage or analysis systems.

The architecture is elegantly simple: distill data at the edge, send only what matters, and let intelligence run alongside your existing tools rather than trying to replace them.

With Flow, you can:

Reduce telemetry volume by 80-90% without losing visibility. Through intelligent filtering, sampling, and aggregation, you eliminate noise while preserving critical signals.

Route data based on value, not volume. Different telemetry has different value. High-cardinality data for debugging goes to one destination. Long-term trend data goes to cheaper storage. Critical alerts get processed in real-time.

Maintain context across the pipeline. This is crucial for AI-powered analysis. As David Jones, VP of NORAM Solution Engineering at Dynatrace observes: “AI without context amplifies uncertainty rather than reducing it.” Flow preserves the semantic context your teams need to actually understand what’s happening.

Control costs predictably. When you process data before storage, your costs scale with insight, not ingestion. You can see exactly what you’re sending where and optimize accordingly.

The Real Promise: Cost That Scales with Value

Bill Hineline, Field CTO for Chronosphere, identifies the core problem clearly: “The resulting surprise bills and increased operational overhead have created the impression that observability itself was a bad investment, when in reality the investment was poorly governed.”

This is where OpenTelemetry plus intelligent pipelines changes everything. You get:

  • Vendor flexibility through open standards
  • Cost predictability through edge processing
  • Operational clarity through intelligent filtering
  • Value optimization by sending the right data to the right destination

As Wilkie notes, “It’s when you pair OTel with intelligent systems—which can reduce data by 80 to 90% while increasing the value of what remains—you start to flip the equation so that cost scales with value, not telemetry volume.”

AI Needs Good Data, Not Just More Data

Much of the AI hype in observability has missed a fundamental truth: AI is only as good as the data you feed it. Throwing an LLM on top of unstructured, high-volume telemetry doesn’t create insight, it creates confusion.

Flow addresses this by ensuring the telemetry reaching your AI systems is already high-quality, well-structured, and contextually relevant. When you reduce volume by 80-90% while increasing data quality, AI can actually deliver on its promise.

This matters especially as organizations adopt AI-powered development tools. As Quillin observes, “As more code is created by AI, the complexity of logs is not getting simpler, necessitating a step back to look at the fundamentals of how data is analyzed.”

Looking Ahead: Observability That Actually Works

OpenTelemetry won’t “save” observability on its own. Standards solve interoperability, not economics. But when you combine OTel’s vendor neutrality with intelligent pipeline processing, you get something powerful: observability that’s both comprehensive and sustainable.

At Apica, we’ve been building toward this future for years. While the industry debates whether observability has failed (it hasn’t, the business model did), we’ve been focused on delivering what customers actually need:

  • Freedom to choose where and how they analyze data
  • Control over costs through intelligent processing
  • Visibility into what telemetry is valuable and what isn’t
  • The ability to scale infrastructure without exponentially scaling observability bills

As Hineline notes, “When OpenTelemetry is treated as foundational plumbing across the enterprise, observability platforms can deliver more consistent, out-of-the-box insights without relying on heavily customized dashboards.”

That’s the future we’re building. Not observability for the expert alone, but observability that works for everyone in your organization, powered by open standards and intelligent processing.

Because the goal isn’t to collect more data. It’s to get more value from the data you actually need.

Learn more about how Apica Flow and our OpenTelemetry-native approach can help you take control of observability costs while improving visibility across your infrastructure.