feat(monitoring): Add Vertex AI API usage aggregation#86
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This commit introduces functionality to aggregate Vertex AI API usage metrics from Cloud Monitoring on a per-day basis. Key changes: - Created a new `monitoring/ai` package. - Defined data structures (`RawMetric`, `AggregatedDailyCount`) for handling Vertex AI metrics in `monitoring/ai/metrics.go`. - Implemented `FetchVertexAIMetrics` to retrieve metrics (currently using mock data for GCP API calls) and `AggregateMetricsByDay` to process these metrics into daily summaries in `monitoring/ai/aggregator.go`. - Added comprehensive unit tests in `monitoring/ai/aggregator_test.go` to validate the aggregation logic across various scenarios, including empty datasets, single-day and multi-day metrics, and different metric properties. The new functionality provides a way to track daily Vertex AI API executions, which can be useful for cost monitoring and usage analysis.
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This commit introduces functionality to aggregate Vertex AI API usage metrics from Cloud Monitoring on a per-day basis.
Key changes:
monitoring/aipackage.RawMetric,AggregatedDailyCount) for handling Vertex AI metrics inmonitoring/ai/metrics.go.FetchVertexAIMetricsto retrieve metrics (currently using mock data for GCP API calls) andAggregateMetricsByDayto process these metrics into daily summaries inmonitoring/ai/aggregator.go.monitoring/ai/aggregator_test.goto validate the aggregation logic across various scenarios, including empty datasets, single-day and multi-day metrics, and different metric properties.The new functionality provides a way to track daily Vertex AI API executions, which can be useful for cost monitoring and usage analysis.