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Tools / Datadog Interview questions

Describe Datadog Incident Management?

Incident Management is Datadog's built-in tooling for declaring, coordinating, and documenting an incident from detection through resolution, without needing a separate standalone tool.

Declaring an incident creates a structured record with severity, an assigned commander, and a live timeline, and can automatically provision a dedicated Slack channel and notify relevant on-call responders.

As responders investigate, relevant graphs, monitor state, and comments get captured on the timeline, which then feeds directly into a postmortem document once the incident is resolved.

Declaring an incident creates a record that includes:
The incident timeline is later used to build a:

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What is Real User Monitoring (RUM) in Datadog? What is Datadog Database Monitoring? What is Network Performance Monitoring in Datadog? What is Datadog Serverless Monitoring? Describe the Datadog Cluster Agent? What is Datadog CI Visibility? What is Datadog Error Tracking? What is Continuous Profiler in Datadog? Describe Datadog Incident Management? What is Datadog Cloud Cost Management? What are API keys and application keys in Datadog? What is the Datadog Terraform provider used for? What is an outlier monitor in Datadog? What is a forecast monitor in Datadog? What is the Datadog Service Catalog? Define OpenTelemetry support in Datadog? What is an Agent flare in Datadog? What is Sensitive Data Scanner in Datadog? Describe Datadog Workflow Automation? What is Application Security Management in Datadog? What is the difference between API keys and application keys? How does the Cluster Agent differ from the node-level Datadog Agent? Why do we use monitor mute/downtime instead of deleting a monitor? What is the difference between Error Tracking and standard log-based error monitoring? How does Datadog's Continuous Profiler collect data without high overhead? When should you use an outlier monitor versus a threshold monitor? What is the difference between a process monitor and a network monitor in Datadog? How does Datadog ingest OpenTelemetry data? Why is Metrics without Limits useful for cost control? What happens when Sensitive Data Scanner detects a match? How does Datadog's Cloud Cost Management attribute spend? When should you use APM trace retention filters versus sampling rules? What is the difference between Service Level Indicators and Service Level Objectives? How does Fleet Automation manage Agent upgrades across a fleet? Why is the Service Catalog important for large engineering organizations? What is the difference between mobile RUM and browser RUM? How does log rehydration work from Datadog archives? When should you use dashboards-as-code instead of the UI editor? Explain the execution flow of a RUM session being recorded and ingested? How can you optimize APM costs using retention filters? How do you troubleshoot a Database Monitoring integration reporting no query metrics? Explain the internal working of Cloud Workload Security (CWS)? How can you optimize Kubernetes monitoring using the Cluster Agent's Cluster Checks? Explain the lifecycle of an incident in Datadog Incident Management? Which is better for reducing MTTR: Watchdog RCA or manual root cause analysis, and why? How do you troubleshoot missing spans from an OpenTelemetry-instrumented service? Explain the execution flow of Sensitive Data Scanner across logs and APM? How can you optimize serverless monitoring for Lambda cold starts? Explain the internal working of Datadog's remote configuration feature? How do you troubleshoot inconsistent cost attribution in Cloud Cost Management?
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