Honeycomb is an observability platform built around a high-cardinality, high-dimensionality column store.
- Teams model organisations.
- Datasets partition stored data, and may model environments. Note that there's no privilege separation between datasets within a team at this time.
- BubbleUp is the core experience: it surfaces anomalies in dimensions based on a selection made on a histogram.
- Events are structured representations of actions taking place in a system, e.g. web transactions. Everything in Honeycomb is stored as an event.
- Columns available will differ with the type of event.
- Derived Columns allow computing additional values for each event based on that event's other column values.
- Query results represent point-in-time executions of a query.
- Triggers enable notification delivery when query results cross configured thresholds.
- SLOs model expectations of service quality as Service Level Objectives.
- Burn rate alerts behave similarly to triggers, but are based on the depletion rate of the error budget.
- Beelines are proprietary SDKs for ingesting data, deprecated in favour of OpenTelemetry.
- Honeytail ingests log files.
COUNTis the number of events
COUNT_DISTINCT(column)is the number of unique values - for the given field
CONCURRENCYyields the number of matching spans in-progress (as determined by start time and duration) in each time interval.
Pnn(column)computes a percentile.
RATE_SUM(column)computes the rate of change between time buckets.
not-incomma-delimited, no parentheses
trace.trace_idfollow the Traces definitions.
API keys are stored at the team level, and can either be visible to all team members or just administrators.
- Send Events
- Create Datasets
- Manage Queries and Columns
- Manage Markers
- Manage Boards
- Manage Triggers