Evidence to decision
- Evidence sources
- Evidence types
- Connected evidence
- Investigation
- Decision
PRODUCTION EVIDENCE SOURCES
Connect the systems that explain production.
AutoObserve connects telemetry, infrastructure, cloud platforms, and change systems to build a connected understanding of production — not just a list of integrations.
Evidence sources
- Telemetry
- Infrastructure
- Deployments
- Cloud
- Storage
AutoObserve
Evidence
Identity
Topology
Correlation
Investigation
AIDDE
Production evidence model
How evidence becomes production intelligence.
Every integration exists because it contributes evidence AutoObserve can connect — not because a vendor API is supported.
Telemetry
Tells us what happened.
Runtime
Tells us where it happened.
Deployments
Tell us what changed.
Cloud
Tells us infrastructure context.
Storage
Preserves historical evidence.
Evidence categories
Organized by evidence type, not vendor API groups.
Each category explains why integrations exist — aligned with how AutoObserve connects production understanding.
Telemetry evidence
Provides operational signals.
Enables correlation and performance understanding.
Examples
Runtime evidence
Provides workload identity and topology.
Enables runtime topology and blast-radius reasoning.
Examples
Change evidence
Explains deployments and operational changes.
Enables change-aware root cause analysis.
Infrastructure evidence
Provides infrastructure relationships.
Enables cloud and resource context.
Examples
Evidence storage
Stores evidence for investigation.
Enables long-term investigation and history.
Examples
Evidence contribution
What each integration contributes to production understanding.
Evidence summary first — not a feature checklist. Every row maps a source system to the investigation capability it enables inside AutoObserve.
| Integration | Evidence | Enables |
|---|---|---|
| Metrics · Logs · Traces · Resource attributes | Correlation foundation | |
| Pods · Services · Deployments · Namespaces | Runtime topology | |
GitHubGA | Commits · Pull requests · Deployments | Change-aware RCA |
| Time-series metrics | Performance analysis | |
JaegerPreview | Traces | Request flow |
Argo CDPreview | Deployments · Sync status | Change-aware RCA |
AWSPreview | Resource metadata · Cloud context | Infrastructure relationships |
AzurePreview | Resource metadata · Cloud context | Infrastructure relationships |
Google CloudPreview | Resource metadata · Cloud context | Infrastructure relationships |
ClickHousePreview | Historical evidence | Long-term investigation |
Featured integrations
Four evidence foundations for production understanding.
Each integration answers one engineering question — what evidence it provides and what investigation capability it enables.
Telemetry foundation
GAOpenTelemetry
Build the telemetry foundation for production investigations
Evidence
- Metrics
- Logs
- Traces
- Resource attributes
Enables
Correlation foundation
View integration →
Runtime topology
GAKubernetes
Map workload identity and runtime topology
Evidence
- Pods
- Services
- Deployments
- Namespaces
Enables
Runtime topology
View integration →
Change correlation
GAGitHub
Correlate deployments with production behaviour
Evidence
- Commits
- Pull requests
- Deployments
Enables
Change-aware RCA
View integration →
Performance analysis
GAPrometheus
Add time-series metrics to connected evidence
Evidence
- Time-series metrics
Enables
Performance analysis
View integration →
All integrations
Browse by evidence source
Evidence summary first, technology second. Status reflects what is available to design partners today.
Telemetry foundation
GAOpenTelemetry
Evidence
- Metrics
- Logs
- Traces
- Resource attributes
Enables
Correlation foundation
View integration →
Runtime topology
GAKubernetes
Evidence
- Pods
- Services
- Deployments
- Namespaces
Enables
Runtime topology
View integration →
Change correlation
GAGitHub
Evidence
- Commits
- Pull requests
- Deployments
Enables
Change-aware RCA
View integration →
Performance analysis
GAPrometheus
Evidence
- Time-series metrics
Enables
Performance analysis
View integration →
Request flow
PreviewJaeger
Evidence
- Traces
Enables
Request flow
View integration →
GitOps change events
PreviewArgo CD
Evidence
- Deployments
- Sync status
Enables
Change-aware RCA
View integration →
Infrastructure context
PreviewAWS
Evidence
- Resource metadata
- Cloud context
Enables
Infrastructure relationships
View integration →
Infrastructure context
PreviewAzure
Evidence
- Resource metadata
- Cloud context
Enables
Infrastructure relationships
View integration →
Infrastructure context
PreviewGoogle Cloud
Evidence
- Resource metadata
- Cloud context
Enables
Infrastructure relationships
View integration →
Long-term investigation
PreviewClickHouse
Evidence
- Historical evidence
Enables
Long-term investigation
View integration →
Data acquisition architecture
How evidence flows into AutoObserve.
Each evidence class follows a distinct acquisition path. AutoObserve connects sources into one correlated production model — without replacing the systems you already operate.
Instrument once with OpenTelemetry. Metrics, logs and traces export through your Collector into AutoObserve.
Applications
OpenTelemetry SDK
Collector
Export fork
- Existing backend
- AutoObserve
Runtime architecture
Change architecture
Cloud architecture
Storage architecture