Observe Inc Highlights Data Lake–Based Observability Strategy and Open-Standards Focus

Observe Inc has shared an update. The company’s CTO and co-founder, Jacob Leverich, appeared on the Data Engineering Podcast to discuss how Observe’s observability platform is built on a data lake architecture designed for real-time, large-scale telemetry. Leverich highlighted the use of open standards, including OpenTelemetry for data collection and Apache Iceberg as an open table format, as well as the use of a curated “context graph” to organize data around real-world use cases for support, engineering, and SRE teams.

For investors, this update underscores Observe’s strategy to differentiate through architecture and open-source alignment rather than purely through application-layer features. The emphasis on a data lake capable of durable streaming ingest, curated columnar datasets to manage scan/read amplification, and correlation across logs, metrics, and traces suggests a focus on scalability and cost efficiency—key decision factors for enterprise observability buyers facing rapid telemetry growth. If successfully executed and adopted, this approach could improve Observe’s competitiveness against established observability vendors by offering longer data retention and potentially lower total cost of ownership. Alignment with widely adopted open standards may also reduce customer lock-in concerns and expand integration opportunities, supporting customer acquisition and retention. However, the post is primarily technical and thought-leadership oriented, and does not disclose concrete financial metrics, customer wins, or pricing details, so the direct revenue impact remains uncertain in the near term.