Decoupled Observability stacks Free Teams

"In 2026, Eric Tschetter, chief architect at Imply, predicts the end of the all-in-one observability black box. AI is driving massive growth in logs, metrics, and traces, pushing tightly coupled, monolithic observability platforms past their architectural limits. Organizations are hitting a breaking point. They can't scale their current observability stacks without tradeoffs: either lose visibility by offloading or sampling data, or absorb runaway infrastructure and licensing costs just to keep data searchable."

"Forward-thinking teams are already rethinking their architecture from the ground up, pulling the data layer apart from the tools that sit on top of it. We've seen this before in business intelligence (BI). Over the last 40 years, BI evolved from tightly coupled stacks-where collection, storage, compute, and visualization were shipped together-to decoupled, three-layer architectures that gave teams more flexibility and control. That shift is why teams today mix and match tools like Tableau with Snowflake or Databricks with Power BI without moving data or rewriting workflows."

"Decoupling the stack separates the collection and routing layer from the data and visualization layers so each can scale independently. This allows teams to expand retention (without proportional indexing costs), improve search speed (without re-architecting dashboards), modernize backend engines (without retraining users), and adopt new tools (without getting trapped into a single vendor's ecosystem). Teams already offload portions of observability data into cloud object storage to control costs."

AI is driving massive growth in logs, metrics, and traces, exceeding the architectural limits of tightly coupled, monolithic observability platforms. Organizations face tradeoffs: offload or sample data and lose visibility, or accept runaway infrastructure and licensing costs to keep data searchable. Forward-thinking teams are decoupling the data layer from tooling, mirroring a four-decade BI shift from integrated stacks to three-layer architectures. Decoupling separates collection/routing from storage and visualization so each layer can scale independently. This enables longer retention without proportional indexing costs, faster search without re-architecting dashboards, backend modernization without retraining users, and tool choice without vendor lock-in.

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