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AutoObserve
Design Partner

INFRASTRUCTURE EVIDENCE

Google Cloud Add GCP infrastructure context to evidence.

GKE, Cloud Run and Cloud SQL metadata explain where production runs in Google Cloud. AutoObserve maps resource relationships onto telemetry identity — alongside Cloud Monitoring and your existing stack.

Evidence
Resource metadata · Cloud context
Source
GCP Asset Inventory
Enables
Infrastructure relationships
Status
Preview
See the evidence received ↓View architecture →

Read integration docs →

Google Cloud

  1. Resource metadata

  2. AutoObserve

  3. Infrastructure context

  4. Investigation

WHY THIS INTEGRATION MATTERS

GCP context connects telemetry to cloud reality.

When checkout-api degrades, project, region and backing Cloud SQL instance matter. GCP infrastructure evidence adds that layer to connected investigations.

  • Resource relationships

    Map services to GKE workloads, Cloud Run services and databases.

  • Cloud identity

    Enrich telemetry with project and resource identifiers.

  • Infrastructure change

    Correlate Cloud Audit Log events with production behaviour.

  • GKE bridge

    Pair GKE cluster metadata with Kubernetes runtime evidence.

EVIDENCE RECEIVED

Resource metadata and cloud context from Google Cloud

GCP Asset Inventory metadata becomes infrastructure evidence — linked to service identity and runtime topology.

  • Resource metadata
  • Cloud context

  1. Discover

    Inventory GKE, Cloud Run and database resources in scope.

  2. Map

    Link GCP resources to Kubernetes and telemetry identity.

  3. Correlate

    Join infrastructure context with metrics, logs and traces.

  4. Investigate

    Start incidents with GCP relationships already resolved.

HOW AUTOOBSERVE USES THIS EVIDENCE

Evidence becomes infrastructure investigation context.

Cloud Monitoring is not replaced — GCP metadata is connected. AutoObserve treats cloud resources as one evidence class in a multi-signal investigation.

Provides

  1. Resource metadata
  2. Cloud context

AutoObserve creates

  1. Infrastructure relationships
  2. Cloud identity
  3. Resource topology
  4. Change correlation

Google Cloud is where it runs. AutoObserve is how you connect it.

CONNECT GCP INFRASTRUCTURE

Ingest GCP metadata alongside telemetry.

Asset Inventory, Audit Log and GKE paths feed the same evidence model — scoped to projects you operate.

Query GCP Asset Inventory for connected resource metadata.

  1. GCP APIs

  2. AutoObserve connector

  3. AutoObserve

QUICK START

Connect Google Cloud infrastructure evidence

Configure service account access and project scope, then verify checkout-api resolves to GCP context.

  1. Configure GCP access

    Grant read-only roles for target projects and enabled APIs.

    Integrations reference →

  2. Link GKE runtime

    Connect GKE clusters for combined cloud and Kubernetes context.

    Deploy on Kubernetes →

  3. Verify infrastructure context

    Confirm checkout-api resolves to project and backing resources.

    Architecture overview →

WHAT SUCCESS LOOKS LIKE

GCP context resolved. Infrastructure ready.

Success means services map to GCP resources — not merely that service accounts are configured.

  • Resources discovered

    checkout-api backing stores appear in infrastructure context.

  • Project resolved

    Production project appears on service identity.

  • Cross-signal correlation

    GCP metadata aligns with telemetry during incidents.

REAL INCIDENT

Same checkout spike — service identity in focus.

The canonical checkout-api degradation with identity context highlighted — the resource linkage that grounds telemetry in Google Cloud infrastructure.

  1. Metric

    14:31:00

    Checkout latency +184%

Walk through the evidence chain · 1/6

Evidence step 1 of 6

TROUBLESHOOTING

Common Google Cloud integration failures

  • Problem

    No resources discovered

    Likely cause

    Service account lacks asset viewer or container viewer roles.

    Resolution

    Verify IAM roles and enabled APIs for Asset Inventory and GKE.

    Verify

    checkout-api backing resources appear within one sync window.

  • Problem

    Resources present but not linked to services

    Likely cause

    GCE/GKE labels do not match telemetry service.name.

    Resolution

    Align GCP labels with Kubernetes labels and OTel resource attributes.

    Verify

    Cloud SQL instance links to checkout-api in investigation context.

  • Problem

    Stale resource metadata

    Likely cause

    Asset export interval too long or project scope too broad.

    Resolution

    Narrow scope to production projects and reduce sync lag.

    Verify

    Resource state matches production during incident window.

PRODUCTION INTELLIGENCE

How Google Cloud contributes to production understanding

GCP infrastructure evidence enables resource relationship reasoning inside connected production intelligence.

EvidenceEnables
Resource metadataInfrastructure relationships
Cloud contextProject scope
Audit Log eventsInfrastructure change correlation

DESIGN PARTNERS

Validate this evidence source with your production stack.

Design partners connect real evidence sources and validate investigation workflows before GA — with direct engineering access.

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