Configure Distribution Log Based Metric Latency Sli

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An e-commerce organization runs a legacy order processing service that outputs structured JSON logs to stdout. The operations team needs to define a Service Level Indicator (SLI) to track the 95th and 99th percentile latency across different checkout categories without refactoring the application code to add OpenTelemetry or Prometheus metric client libraries.

A sample log payload emitted by the service contains:

{
  "message": "Order processed successfully",
  "transaction_type": "express_checkout",
  "duration_ms": 245.8
}

How should the DevOps engineer configure Google Cloud Observability to generate the required latency SLI metrics?

Deploy the Google-Built OpenTelemetry Collector on the host and configure the transform/aco-gke processor to extract latency histograms from standard output.

Create a counter log-based metric in Cloud Logging with a label extracting jsonPayload.duration_ms and another label extracting jsonPayload.transaction_type.

Create a distribution log-based metric in Cloud Logging, configure the field extractor to extract jsonPayload.duration_ms as the numeric value, and define a metric label extracting jsonPayload.transaction_type.

Export the application logs to BigQuery via a log router sink and configure a scheduled query to calculate percentiles and publish them as custom metrics.

Professional Cloud DevOps Engineer

Configure Distribution Log Based Metric Latency Sli

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