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Datadog LogsSkill
Summary
Search Datadog logs from an agent and keep the bill under control — query syntax, exclusion filters, log-based metrics, archives and PII scrubbing.
Features
- Log search syntax: tags, attributes, numeric ranges, booleans, wildcards
- Pipeline processors — grok parsing, status and attribute remapping
- Exclusion filters and a jq recipe for finding the noisiest services
- Log-based metrics as a cheaper alternative to indexing
- Archive configuration with rehydration tags
- PII scrubbing at ingestion and in the application
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Description
Log search is the easy part; the reason log platforms hurt is indexing volume. This official Datadog skill covers both, and it is unusual in treating cost as a first-class concern rather than an afterthought.
Searching
The pup logs search surface is documented with a compact syntax table — full-text terms, tag equality (status:error), attribute matching and numeric ranges (@http.status_code:>=400), boolean composition and wildcards — plus the pipeline and processor shapes an agent needs to understand the data it is reading: grok parsers, status remappers and attribute remappers that move user_id to the standard usr.id.
Cost control as the main event
The skill is direct about what to stop indexing. It ships a jq recipe that groups an hour of logs by service to find the noisiest producers, then a table of the usual exclusion candidates — health-check and readiness endpoints, status:debug, static asset requests, heartbeat messages. Where a metric is what you actually wanted, it points at log-based metrics as the cheaper alternative to indexing, with an explicit cardinality warning to group only on bounded values. Archives to S3 or equivalent cover the compliance case at storage prices, with rehydration tags set up front.
Sensitive data
Hash-remapper scrubbing rules handle emails and similar fields at ingestion, and there is a sanitiser pattern for stripping card numbers and national ID numbers in the application before the log ever leaves the process — the right layer for that particular problem.
Honest about the tool's limits
Worth noting: the skill explicitly records where pup has no command, pointing the agent at the Datadog UI or API for log rehydration rather than letting it hallucinate a pup logs rehydrate. Requires the pup CLI, authenticated with pup auth login. MIT-licensed, published by Datadog Labs.
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