Features
With a one-line config change, Grepr lowers your observability costs and improves your MTTR. Keep your dashboards, alerts, workflows and data right where they are.
Compatible with Datadog, Splunk, Sumo Logic, OpenTelemetry and others.
Grepr's patent-pending machine learning technology automatically compresses messages. A one-line config change turns it on. Your original data is sent to low-cost queryable storage, so you maintain visibility. Anomalous and unique data is always sent unaggregated with low latency.
Grepr's patent-pending machine learning technology automatically compresses messages. A one-line config change turns it on. Your original data is sent to low-cost queryable storage, so you maintain visibility. Anomalous and unique data is always sent unaggregated with low latency.
With Grepr, you can search across all of your observability data in one place using relational queries. Our dynamic context-based backfilling ensures that engineers have the troubleshooting data they need when they need it. Load whatever data you need in the shape you need back to the tool you like to work with.
With Grepr, you can search across all of your observability data in one place using relational queries. Our dynamic context-based backfilling ensures that engineers have the troubleshooting data they need when they need it. Load whatever data you need in the shape you need back to the tool you like to work with.
Grepr reduces noise and data overload by summarizing repeated log messages, and aggregating "normal" hosts and containers. Quickly find interesting data in your observability tool and compare to group behavior.
Grepr reduces noise and data overload by summarizing repeated log messages, and aggregating "normal" hosts and containers. Quickly find interesting data in your observability tool and compare to group behavior.
Your alerts and dashboards are unaffected by Grepr. We automatically parse your existing alerts and dashboards, and we bypass summarization for any data that they need.
Your alerts and dashboards are unaffected by Grepr. We automatically parse your existing alerts and dashboards, and we bypass summarization for any data that they need.
Have your cake and eat it
Grepr aggregates data using our unsupervised machine learning and automated real-time log pattern discovery. This means that not only can we handle the big hitters, but also the long tail of unique patterns. As you modify your services, Grepr automatically evolves with your needs.
Grepr aggregates data using our unsupervised machine learning and automated real-time log pattern discovery. This means that not only can we handle the big hitters, but also the long tail of unique patterns. As you modify your services, Grepr automatically evolves with your needs.
Grepr only aggregates and summarizes messages that repeat beyond a configurable threshold. Before then, messages are forwarded with a few seconds of latency. You'll always have a sample of unsummarized messages to compare against.
Grepr only aggregates and summarizes messages that repeat beyond a configurable threshold. Before then, messages are forwarded with a few seconds of latency. You'll always have a sample of unsummarized messages to compare against.
Automatic log aggregation
Aggregate metrics, traces, and other data arriving from healthy hosts or containers. Pass through data for unhealthy hosts or containers unmodified for troubleshooting.
Aggregate metrics, traces, and other data arriving from healthy hosts or containers. Pass through data for unhealthy hosts or containers unmodified for troubleshooting.
Use powerful rules and anomaly detection to tell Grepr when an object such as a host or a container is "abnormal". We use standard rules available in every observability toolset as well as powerful machine-learning techniques to detect issues.
Use powerful rules and anomaly detection to tell Grepr when an object such as a host or a container is "abnormal". We use standard rules available in every observability toolset as well as powerful machine-learning techniques to detect issues.
The right data, in the right place, at the right time
