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An e-commerce company runs a microservices-based checkout system deployed across Google Kubernetes Engine (GKE) and Cloud Run. During peak shopping events, end users report intermittent latency spikes that violate response time Service Level Objectives (SLOs), accompanied by sudden increases in cluster compute consumption. The operations team needs to pinpoint which specific inter-service calls introduce the delays and identify the exact application functions consuming excessive CPU and memory in production.
Which observability strategy should you implement to diagnose these performance bottlenecks?
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