How do you set up cross-platform monitoring for multi-cloud applications?

Cross-platform monitoring is a key practice to ensure unified visibility of applications running across multiple cloud platforms (such as AWS, Azure, GCP, and private clouds). Its importance lies in breaking down data silos caused by cloud vendor lock-in, enabling centralized control and assurance of application performance, resource utilization, and service levels, making it suitable for modern distributed, highly available multi-cloud or hybrid cloud architectures.

The core components include standardized data collection (e.g., using Prometheus, Fluentd, OpenTelemetry agents), unified storage backends (e.g., Thanos, Cortex, VictoriaMetrics), and centralized visualization and analysis platforms (e.g., Grafana). Features emphasize the standardization of metrics, logs, and trace data (e.g., using the OTLP protocol), label consistency (e.g., `cluster`, `region`, `app` labels), and centralized management of alerting policies. It directly impacts SLO achievement and fault localization efficiency, while also enabling unified optimization of resource costs.

Implementation steps include: 1. Define monitoring standards: unify metrics/log formats and labeling specifications; 2. Deploy collection agents: deploy OTel or compatible agents on instances/clusters of each cloud platform; 3. Establish a central aggregation point: configure Thanos Sidecar or OTel Collector to aggregate data into central storage; 4. Configure visualization and alerting: create cross-cloud data sources and dashboards in Grafana, and configure unified alerting rules (e.g., using Prometheus Alertmanager). Typical values include improving Mean Time to Recovery (MTTR), achieving cost transparency, and enabling proactive performance optimization.