Imply has launched Lumi Loglake, an interactive log search tool for object storage that drastically cuts observability and SIEM infrastructure expenses.
Founded in 2015, Imply builds real-time analytics software based on Apache Druid. Its three founders — CEO Fangjin Yang, CTO Gian Merlino and Chief Experience Officer Vadim Ogievetsky — are the original creators of Druid. Positioned as a data layer for observability, security and AI, the company is now developing a lakehouse architecture for unstructured logs, enabling direct log search within object storage environments.
Imply Chief Architect Eric Tschetter stated: “AI is generating more telemetry than organizations can afford to index. Lumi Loglake enables teams to retain, search and investigate this data without the cost and complexity of always-on indexing architecture. By bringing interactive log search directly to open storage, Loglake leverages lakehouse economics and flexibility to operationalize log data.”
Traditional observability architectures require logs to be cataloged, structured and indexed before searchability. At AI-scale data volumes, this forces SIEM teams to pre-determine log retention and indexing scopes in advance, creating heavy operational overhead and uncontrollable costs.
Observability and security teams analyze unstructured machine data, where investigations start without prior knowledge of critical fields, patterns or events. Lumi Loglake lets users search and examine unstructured logs in-place across AWS S3, Delta Lake and Apache Iceberg, with no data catalogs, schema definitions or data rehydration workflows required.
Lumi Loglake decouples compute from object storage, letting users scale telemetry retention independently of compute costs. Compute resources spin up dynamically based on query activity, eliminating always-on indexing infrastructure while maintaining instant access to historical telemetry data.
The solution allows SIEM teams to retain far more log data in low-cost object storage and conduct instant searches, applying targeted indexing only when necessary. Imply confirms customers can cut software costs by 70%+ and hardware costs by 40%+ by migrating data from persistent indexed storage to open object storage like Amazon S3.
Instead of storing massive datasets in Splunk’s indexing tier, enterprises can archive historical telemetry on S3 while retaining full SPL query compatibility and native Splunk event support. The same stored datasets support cross-platform queries without duplication: SPL for Splunk, Spark SQL for Databricks, LogQL for Grafana, and ANSI SQL/JDBC for AI and BI platforms.
Lumi Loglake is generally available now and showcased at the Databricks Data + AI Summit. Further details are available in blogs by Imply Senior Product Marketing Director Matt Morrissey.
Beijing Qianxing Jietong Technology Co., Ltd.
Sandy Yang/Global Strategy Director
WhatsApp / WeChat: +86 13426366826
Email: yangyd@qianxingdata.com
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