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1 # Investigations
2
3 Ask Netdata anything about your infrastructure and get a deeply researched answer in minutes. Investigations turn your question and context into an analysis that correlates metrics, anomalies, and events across your systems.
4
5 ## What Investigations are good for
6
7 - Troubleshooting live incidents without manual data wrangling
8 - Analyzing the impact of deployments or config changes
9 - Cost and efficiency reviews (identify underutilized resources)
10 - Exploring longer‑term behavioral changes and trends
11
12 ## Starting an investigation
13
14 Two easy entry points:
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16 - `Troubleshoot with AI` button (top‑right): Captures the current chart, dashboard, or service context automatically, then you add your question
17 - `Insights``New Investigation`: Blank canvas for any custom prompt
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19 Reports complete in ~2 minutes and are saved in Insights; you’ll get an email when ready.
20
21 ## Provide good context (get great results)
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23 Think of it like briefing a teammate. Include timeframes, environments, related services, symptoms, and recent changes. Example formats:
24
25 ### Example: Troubleshoot a problem
26 Request: Why are my checkout‑service pods crashing repeatedly?
27
28 Context:
29 ```
30 - Started after: deployment at 14:00 UTC of version 2.3.1
31 - Impact: Customer checkout failures, lost revenue ~$X/hour
32 - Recent changes: payment gateway integration update; workers 10→20
33 - Logs: "connection refused to payment-service:8080", "Java heap space"
34 - Environment: production / eks-prod-us-east-1
35 - Related: payment-service, inventory-service, redis-session-store
36 ```
37
38 ### Example: Analyze a change
39 Request: Compare metrics before/after the user‑authentication‑service deploy.
40
41 Context:
42 ```
43 - Service: user-authentication-service v2.2.0
44 - Deployed: 2025‑01‑24 09:00 UTC
45 - Changes: JWT→Redis sessions; Argon2 hashing added
46 - Concern: intermittent logouts; rising redis_connected_clients
47 - Windows: 24h before vs 24h after
48 ```
49
50 ### Example: Cost optimization
51 Request: Identify underutilized nodes for cost savings.
52
53 Context:
54 ```
55 - Monthly compute: ~$12K
56 - Mixed workloads (prod + staging)
57 - Dev envs run 24/7; batch nodes idle 20h/day
58 - Goal: save $2–3K/month without reliability impact
59 ```
60
61 ## Availability and credits
62
63 - Available to Business and Free Trial plans
64 - Each run consumes 1 AI credit (10 free per month on eligible plans)
65
66 ## Related documentation
67
68 - [Custom Investigations](/docs/netdata-ai/investigations/custom-investigations.md)
69 - [Scheduled Investigations](/docs/netdata-ai/investigations/scheduled-investigations.md)
70 - [Alert Troubleshooting](/docs/troubleshooting/troubleshoot.md)