We use machine learning to perfectly structure and detect anomalies across logs and metrics (streamed or static). Each log line is schematized by event type, with parameters captured into their own typed columns and optimized for query. The schema is self-managed across software versions. Does not require software changes, scripting or pre-training.
Machine learning finds anomalies in logs and metrics that accurately catch new "unknown" faults. This also massively reduces the amount of log data you need to look at to find root cause. And because we have a perfectly structured foundation, it actually works!
We make it dead simple to build accurate and durable signatures to auto-detect known issues (even for issues that exhibit themselves as a very complex series of events). The process takes just a few clicks and starts by selecting the relevant events. You can then set: the event order, the time period for the events to occur, the specific event types that must occur, and variable values and constraints within the events. Now if the problem happens again, you'll be automatically notified and taken straight there.
We've achieved the impossible - a familiar and intuitive event viewer, with super-powers that make it let you easily interact with your data (all made possible because we've perfectly structured the underlying data sets). Here are just some of the things you can easily do:
- Select any metric or string and instantly see it charted (and of course no human had to build a parsing expression to do this)
- Get rid of spammy events with just a click
- Filter so you see only specific event types
- See data from multiple sources interleaved in time series order (and then click back to just one source)
- Navigate directly to any known issue, anomaly or exception (or any user defined "track")
- Create navigable visualizations from event types, strings, metrics (with or without constraints)
- And a whole lot more...
We make it easy to share your current view and the steps you’ve taken to get there. This makes collaboration with other developers and testers.
For the power user we offer a CLI that gives you fine-grained access to the underlying structured log, metric and anomaly data. This includes the ability to perform SQL queries of arbitrary complexity and query our dictionary of events.
We have built a SaaS platform that’s intuitive and easy to use. Integration with your application is as simple as two kubectl commands for Kubernetes, or a single CLI command for other environments. No software changes or additional instrumentation required. We adhere to industry best practices for security including encryption of all data in-flight and at rest as well as secure separation of all user data.