DrDroid
Open Source droidctx — Build infrastructure context for your coding agent

Leverage AI to automate production operations

Deploy agents to detect anomalies, investigate alerts, and resolve known issues without manual interventions or escalations.

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Reduce MTTI

Run complex investigations in minutes, not hours

Debugging requires jumping between 10+ tools and tribal knowledge.

DrDroid runs multi-step investigations automatically — querying logs, metrics, deployments, and configs to pinpoint root cause.

Watch investigation videos
ALERT: 5xx error rate > 5% on checkout-api (us-east-1) Investigating... Agent investigation trail 1 Checked recent deployments Found: checkout-api v3.12.1 deployed 12 min ago via ArgoCD ArgoCD GitHub 2 Queried error logs NullPointerException in PaymentProcessor.validate() — 2,847 occurrences Datadog 3 Compared with previous version diff Commit abc123: Removed null check in validate() for "perf optimization" GitHub 4 Checked downstream impact payment-svc p99 latency up 340%, order-svc queue depth growing Grafana CloudWatch 5 Verified fix path v3.12.0 had no errors — rollback is safe, no DB migrations in v3.12.1 ArgoCD Root cause: Null check removed in commit abc123 (v3.12.1) Recommendation: Rollback to v3.12.0 — safe, no migrations. 3 downstream services affected. 5 tools queried Completed in 2 min 14s Manual estimate: ~45 min No runbooks needed
Increase MTBF

Catch issues before alerts even exist for them

You can't set up alerts for everything — silent failures slip through the cracks.

Write a check in plain English and schedule the agent to run it on a cron. It proactively monitors what you care about — even things you haven't set up alerts for yet.

See how to set this up
Step 1 — Engineer creates a proactive check Check: "payment-svc end-to-end health" "Check payment-svc success rate, p99 latency, error logs for new exception patterns, downstream Redis + Postgres health, and queue depth on payment-worker. Flag if anything unusual." Scheduled: every 30 minutes Too complex for a single alert Requires checking metrics, logs, dependencies & queue together Agent handles it instead Step 2 — Agent runs the check every 30 minutes ✓ 9:00 ✓ 9:30 ✓ 10:00 ✓ 10:30 ✓ 11:00 ! 11:30 Issue found Agent catches silent degradation across multiple signals payment-svc degrading silently Success rate dropped 94.2% → 91.8% (no alert threshold set) New TimeoutException in logs + Redis connection pool at 94% No single metric would trigger an alert — pattern across 4 signals Team fixed it proactively Before success rate hit alert threshold or customers noticed
Reduce MTTD

Cut through noise and identify real issues faster

Too many alerts — most are noise, and real issues get buried.

The agent listens to all your alerts, auto-deduplicates, groups by component and root cause, and escalates by impact — based on your team's escalation policies. It learns over time which alerts are actionable.

See how to set this up
Incoming alerts (last hour) CPU high — checkout-svc CPU high — checkout-svc Disk 80% — logging-node-3 p99 latency — payment-api Memory warn — cache-01 5xx spike — checkout-svc CPU high — checkout-svc Cron missed — report-gen Disk 80% — logging-node-3 Connection timeout — payment-db ... +23 more 34 alerts DrDroid Agent Deduplicate 3x CPU checkout → 1 2x Disk logging → 1 Group by root cause checkout-svc cluster Classify by impact What your team sees P0 checkout-svc degraded CPU spike + 5xx + payment-db timeout Root cause: payment-db connection pool Impact: checkout flow down Page on-call P2 Disk filling on logging logging-node-3 at 80%, trending up Non-urgent — ticket created Suppressed (non-actionable) Cron missed — report-gen (known flaky) Memory warn — cache-01 (auto-scales) 34 alerts → 2 actionable 94% noise reduction Learns over time what's actionable
Upskill & Empower

Share investigation skills across the team

Only senior engineers know how to debug complex issues.

Capture your best engineers' investigation patterns and make them available to the entire team — leveling up everyone's debugging skills.

First time — Senior SRE investigates manually ALERT: payment-svc p99 latency > 2s 1. Check redis-payments-03 pool 2. Verify pool size in Consul config 3. Compare against peak traffic 4. Bump pool to 50, restart pod Root cause: Redis pool exhaustion during peak Took 45 min to resolve DrDroid captures this pattern 2 weeks later Same pattern reappears — Agent runs it automatically ALERT: payment-svc p99 latency > 2s DrDroid Agent (auto) Checked redis-payments-03 pool Confirmed pool exhaustion at peak Bumped pool to 50, restarted pod Resolved automatically No human involved Resolved in 90 seconds
Save $

Identify cost optimizations continuously

Overprovisioned resources and idle infrastructure waste money.

Run automated cost analysis across your infrastructure that surfaces actionable savings — from right-sizing to unused resource cleanup.

See how to set this up
Cost Optimization Report Monthly savings found $4,280 Recommendations 12 Resources analyzed 847 $ Right-size 4 over-provisioned EC2 instances -$1,840/mo $ Remove 3 unused EBS volumes (90+ days idle) -$960/mo $ Switch 2 RDS instances to reserved pricing -$1,480/mo Scanned automatically — updated weekly
Keep Systems Current

Auto-improve alerting and monitoring dashboards

Dashboards and alerts go stale as infrastructure evolves.

Keep your monitoring aligned with reality — automatically retire stale alerts, fix broken dashboards, and generate coverage for new services.

Dashboard & Alert Improvement Before 12 stale alerts (no triggers in 30d) 3 dashboards with missing panels No coverage for new auth-service 5 duplicated alert rules After DrDroid 12 stale alerts retired 3 dashboards auto-repaired auth-service alerts created 5 duplicates merged into 2 Runs weekly — keeps you current

Connects to 80+ tools your team already uses

80+ tools that the Agent knows how to use, from Kubernetes to Grafana to Github to custom internal tools.

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Frequently Asked Questions

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Connect your tools in 15 minutes. See your first automated investigation in under an hour.

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