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Manage Datadog Error Tracking issues via the API (search, review, resolve, assign)

Track custom actions and attach global context in the Datadog RUM Browser SDK

Query timeseries or scalar data across multiple Datadog products via the v2 query API

Query legacy Datadog timeseries metric data with the Metrics API v1 query endpoint

Create and manage Datadog Service Catalog entries via API to document service ownership, dependencies, and metadata

Configure Datadog Cloud Cost Management to ingest AWS, Azure, and GCP billing data and allocate costs by tag

Use Datadog's ingestion_reason tag to understand why APM traces were sampled and retained

Configure Datadog APM distributed tracing with trace context propagation across services using multiple propagation formats

Ingest Datadog APM traces via the OTLP ingest API and correlate them with Datadog Infrastructure metrics using unified service tagging

Implement DogStatsD custom metrics from an application and verify ingestion in Datadog using metric explorer and tag filtering

Configure Datadog APM trace retention filters and ingestion control

Set up Datadog Watchdog anomaly monitors for automated anomaly detection

Instrument a single-page application with Datadog RUM for session and view tracking

Configure Datadog APM trace ingestion sampling rules and retention filters to control cost without losing critical traces

Configure Datadog SLO burn rate monitors to alert on error budget exhaustion

Manage Datadog log pipelines and processors via the API

Configure Datadog RUM Session Replay privacy level to mask user data

Enable the Datadog Continuous Profiler for a Python or Go application using environment variables and the dd-trace library

Initialize the Datadog RUM browser SDK to capture page views, user interactions, and Core Web Vitals

Configure Datadog Observability Pipelines to sample logs by pattern and reduce ingestion volume before data reaches Datadog

Trigger log rehydration from a Datadog archive stored in S3 to restore historical logs for investigation

Enable Datadog Session Replay and configure privacy masking to protect sensitive user data

Configure Datadog log exclusion filters on an index to reduce indexing volume for high-noise low-value logs

Create Datadog Synthetic API tests programmatically via the API to monitor critical endpoints on a schedule

Configure anomaly detection monitors in Datadog to alert on unusual metric patterns

Create and manage Datadog SLOs programmatically via the SLOs API

Configure Datadog Metrics without Limits to reduce indexed metric volume without losing query fidelity

Create and update Datadog monitors via the API

Submit custom metrics to the Datadog API from an application

Configure Datadog log pipelines and processors to parse and enrich logs