How Grepr uses continuous pattern extraction and AI to detect anomalies and build monitoring strategies to prevent failures.
Every AI conversation at the summit dragged a cost conversation behind it, and most teams already knew which one was winning.
Grepr's free tier is live: perpetual, no credit card, 4 TB of logs and 8 TB of traces a month to run on your own data.
Grepr uses distributed stream partitioning and a forgetful Bloom filter to guarantee complete log sets for sampled traces, without exhausting memory or disrupting your existing workflows.
Grepr's semantic pipeline automatically masks variable data, clusters similar messages, and samples or summarizes noisy patterns in real time, reducing log volume by 90% or more without dropping a single message.
Grepr retains all your logs in low-cost storage and backfills exactly what you need into your existing tools the moment an incident hits, so you never lose the data that explains what went wrong.
Discover how Grepr's intelligent log management solution can reduce your logging costs by 90% without sacrificing visibility. Our two-tier storage system uses machine learning to identify patterns and store less critical logs in low-cost storage, while maintaining immediate access to important data. When incidents occur, Grepr's dynamic backfill feature automatically retrieves relevant logs to your existing tools. Implement smarter logging today without changing your workflows or compromising on troubleshooting capabilities.
Storing logs long-term doesn't have to be super expensive. Using a data lake can reduce storage costs by more than 90% while still keeping the logs queryable and immediately accessible.
Observability demands low-latency queries and flexible schemas that most open-source data lake tools can't deliver. Here are six ways Grepr closes that gap.
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