December 2025 Summaries

In 2025, observability teams shifted focus from reducing data to building architectures that could handle growing demands, highlighted by the introduction of Imply Lumi, the industry's first Observability Warehouse. This new data layer allows teams to retain more data, search faster, and reduce costs without overhauling existing tools, providing a foundation for AI/ML workflows. The most-read Imply blogs of the year explored the need for decoupling in observability, similar to business intelligence, to address scalability challenges. The content emphasized the importance of maintaining full-fidelity data retention as AI use cases expand and showcased how integrations with existing platforms like Splunk and Cribl can modernize data layers, allowing organizations to overcome cost and retention trade-offs. Looking forward to 2026, Imply plans to expand integrations and reference architectures, promoting a more scalable, flexible, and cost-effective approach to observability.

Imply Lumi enhances the scalability and efficiency of Splunk by providing a modern, cloud-native data layer that addresses the challenges of handling massive telemetry volumes in observability environments. As traditional index-first architectures struggle with the increasing data growth, organizations face trade-offs like reduced data retention and visibility gaps. Imply Lumi offers a solution by integrating directly with Splunk through Federated Search, allowing users to query extensive datasets without altering existing workflows or dashboards. It decouples compute and storage, enabling cost-effective and faster search performance, while maintaining the familiar Splunk interface. This approach mirrors the architectural evolution seen in business intelligence, where decoupling layers unlocked scalability and predictability. By enabling the affordable ingestion and search of high-volume logs, Imply Lumi expands the data accessible through Splunk, providing deeper visibility and maintaining operational continuity without increasing costs or complicating existing processes.