Summary: A multi-cloud monitoring strategy is essential for building unified observability across AWS, Azure, and GCP. This playbook outlines how to centralize metrics, logs, dashboards, and alerts while optimizing cost and compliance coverage across all major cloud providers.
1. Purpose
This playbook defines a standardized, multi-cloud monitoring strategy that streamlines observability operations across AWS, Azure, and GCP accounts. A consistent strategy improves visibility, accelerates root cause analysis, and enhances security posture by aligning telemetry and audit practices across environments.
2. Scope
This guidance applies to cloud operations teams managing hybrid or distributed workloads. It includes foundational metrics (CPU, memory, disk), infrastructure observability, application telemetry, log collection, alert routing, and dashboard federation using tools such as CloudWatch, Azure Monitor, and Google Cloud Operations Suite.
3. Definitions
- Metrics Federation: Aggregating and unifying telemetry from multiple clouds into a central view.
- Centralized Logging: Consolidating logs from distributed services into a unified analysis platform.
- Landing Zone: A secure, centralized environment that houses shared services including observability and IAM roles.
- Multi-cloud monitoring strategy: A deliberate approach to monitoring and analyzing resources, logs, and metrics across multiple cloud providers using a unified architecture.
4. Prerequisites
- Agents deployed: CloudWatch Agent, Azure Monitor Agent, and GCP Ops Agent
- IAM roles/service principals for secure telemetry sharing
- Log destinations and sinks configured across cloud platforms
- Integrated alerting tools (e.g., PagerDuty, Slack, Opsgenie)
5. Multi-Cloud Monitoring Architecture
- AWS: Use CloudWatch cross-account dashboards and CloudTrail logs centralized to a monitoring account
- Azure: Route diagnostics to Log Analytics and analyze via Azure Workbooks
- GCP: Set up Aggregated Sinks and centralized dashboards in Cloud Monitoring
This multi-cloud monitoring strategy enables centralized visibility, cost optimization, and consistent security monitoring across cloud platforms without vendor lock-in. Use cloud-native tools wherever possible to minimize costs, but augment visibility using a centralized platform like Grafana, Datadog, or New Relic to unify metrics and logs from all providers.
6. Cross-Platform Log Centralization
- Enable log forwarding and data normalization:
- AWS: CloudWatch Logs → Kinesis → S3 → Elasticsearch
- Azure: Event Hub or Log Analytics → Azure Data Explorer or SIEM
- GCP: Pub/Sub → BigQuery or Elastic Stack
- Normalize log formats using Fluent Bit or Logstash for compatibility
- Retain logs for compliance using centralized storage tiers and ILM (index lifecycle management)
- Tag logs by cloud, region, and service for traceability and filtering
7. Centralized Alerting and Dashboards
- Use Grafana, Datadog, or New Relic to display multi-cloud views
- Define alert thresholds for service health, uptime SLAs, and cost spikes
- Route alerts through centralized channels (e.g., Teams, email, PagerDuty)
- Automate alert policy deployment using IaC frameworks like Terraform or Bicep
8. Cost, Compliance & Audit Metrics
- Monitor log ingestion volumes and associated costs with usage dashboards
- Use audit logs to track IAM activity, API calls, and resource changes
- Apply retention policies to avoid excessive storage costs
- Visualize compliance status across accounts using dashboards
9. Multi-Cloud Observability Architecture Walkthrough
This architecture diagram illustrates how a well-structured multi-cloud monitoring strategy integrates observability layers across AWS, Azure, and Google Cloud. Each cloud provider contributes native tools such as CloudWatch, Azure Monitor, and GCP Cloud Monitoring. Logs, metrics, and traces from all platforms are aggregated and forwarded to a centralized observability layer using log forwarding agents, event streaming, and APIs.
At the top of the diagram, tools like Datadog, Splunk, New Relic, and Grafana unify telemetry into dashboards and alerting systems that provide real-time visibility. The lower section showcases integration methods such as Fluent Bit, Pub/Sub, Event Hub, and Kafka, used to normalize and transmit telemetry between providers and third-party systems. This enables consistent monitoring, rapid troubleshooting, cost tracking, and compliance enforcement across a multi-cloud architecture.
10. Implementation Checklist
- ☑️ Agents running in every cloud account and region
- ☑️ Unified dashboard accessible by SecOps and SRE teams
- ☑️ Alerting pipeline routed to on-call responders
- ☑️ Logs searchable and retained to meet compliance
- ☑️ Costs visualized and tagged by service, team, and cloud
11. Real-World Use Cases
- Incident Reduction: A SaaS provider reduced detection time by 50% by aggregating logs into Grafana Cloud
- Audit Readiness: A federal contractor used centralized IAM logs to pass a FedRAMP audit
- Cost Savings: A startup avoided $4K/month in logging fees by optimizing GCP and CloudWatch ingestion rates
- Multi-cloud normalization: An eCommerce company used Fluent Bit to unify logging across Azure and AWS into a shared SIEM