cloud-sql-postgres-health

Usage

All scripts can be executed using Node.js. Replace <param_name> and <param_value> with actual values.

Bash: node <skill_dir>/scripts/<script_name>.js '{"<param_name>": "<param_value>"}'

PowerShell: node <skill_dir>/scripts/<script_name>.js '{\"<param_name>\": \"<param_value>\"}'

Note: The scripts automatically load the environment variables from various .env files. Do not ask the user to set vars unless skill executions fails due to env var absence.

Scripts

get_query_metrics

Fetches query level cloudmonitoring data (timeseries metrics) for queries running in Postgres instance using a PromQL query. Take projectID and instanceID from the user for which the metrics timeseries data needs to be fetched. To use this tool, you must provide the Google Cloud projectId and a PromQL query.

Generate PromQL query for Postgres query metrics. Use the provided metrics and rules to construct queries, Get the labels like instance_id, query_hash from user intent. If query_hash is provided then use the per_query metrics. Query hash and query id are same.

Defaults:

1. Interval: Use a default interval of 5m for _over_time aggregation functions unless a different window is specified by the user.

PromQL Query Examples:

1. Basic Time Series: avg_over_time({"__name__"="cloudsql.googleapis.com/database/postgresql/insights/aggregate/execution_time","monitored_resource"="cloudsql_instance_database","project_id"="my-projectId","resource_id"="my-projectId:my-instanceId"}[5m])
2. Top K: topk(30, avg_over_time({"__name__"="cloudsql.googleapis.com/database/postgresql/insights/aggregate/execution_time","monitored_resource"="cloudsql_instance_database","project_id"="my-projectId","resource_id"="my-projectId:my-instanceId"}[5m]))
3. Mean: avg(avg_over_time({"__name__"="cloudsql.googleapis.com/database/postgresql/insights/aggregate/execution_time","monitored_resource"="cloudsql_instance_database","project_id"="my-projectId","resource_id"="my-projectId:my-instanceId"}[5m]))
4. Minimum: min(min_over_time({"__name__"="cloudsql.googleapis.com/database/postgresql/insights/aggregate/execution_time","monitored_resource"="cloudsql_instance_database","project_id"="my-projectId","resource_id"="my-projectId:my-instanceId"}[5m]))
5. Maximum: max(max_over_time({"__name__"="cloudsql.googleapis.com/database/postgresql/insights/aggregate/execution_time","monitored_resource"="cloudsql_instance_database","project_id"="my-projectId","resource_id"="my-projectId:my-instanceId"}[5m]))
6. Sum: sum(avg_over_time({"__name__"="cloudsql.googleapis.com/database/postgresql/insights/aggregate/execution_time","monitored_resource"="cloudsql_instance_database","project_id"="my-projectId","resource_id"="my-projectId:my-instanceId"}[5m]))
7. Count streams: count(avg_over_time({"__name__"="cloudsql.googleapis.com/database/postgresql/insights/aggregate/execution_time","monitored_resource"="cloudsql_instance_database","project_id"="my-projectId","resource_id"="my-projectId:my-instanceId"}[5m]))
8. Percentile with groupby on resource_id, database: quantile by ("resource_id","database")(0.99,avg_over_time({"__name__"="cloudsql.googleapis.com/database/postgresql/insights/aggregate/execution_time","monitored_resource"="cloudsql_instance_database","project_id"="my-projectId","resource_id"="my-projectId:my-instanceId"}[5m]))