Oodle Metrics

Oodle Metrics — Discovery and Querying

This skill teaches the agent to find metric names, enumerate their labels, and build PromQL queries that return data on the first try.

Prerequisites

brew install oodle-ai/oodle/oodle
oodle configure

Confirm the metrics endpoint works:

oodle metrics list --limit 5 -o json | jq 'length'

Command Execution Order

Before running any oodle command:

1. Check whether the required metric name is already in context.
2. If not, run oodle metrics list --match <prefix> to discover it.
3. Run oodle metrics labels <name> to enumerate labels.
4. Run oodle metrics label-values <name> <label> to enumerate the values you need to filter on.
5. Build the PromQL query using only labels confirmed in step 3 and values confirmed in step 4.

Quick Reference

Common Operations

The 3-step label discovery workflow

Always run these three commands in order before writing a PromQL expression for a metric you have not used before.

# Step 1 — find the metric name
oodle metrics list --match "http_requests" -o json
# returns e.g. ["http_requests_total", "http_requests_in_flight"]

# Step 2 — list available labels
oodle metrics labels http_requests_total
# returns e.g. ["service", "method", "status", "env"]

# Step 3 — list values for a label
oodle metrics label-values http_requests_total service
# returns e.g. ["api", "checkout", "auth"]

# ✅ CORRECT — query built from confirmed labels and values
sum by (service) (rate(http_requests_total{service="api",env="prod",status=~"5.."}[5m]))

# ❌ WRONG — guessing label names; query returns no data
sum by (svc) (rate(http_requests{app="api",environment="production",http_status=~"5.."}[5m]))

Filtering and paging metric lists

# ✅ CORRECT — narrow with --match
oodle metrics list --match "http_requests" -o json

# ✅ CORRECT — page with --limit when sweeping a namespace
oodle metrics list --match "kube_" --limit 200 -o json

# ❌ WRONG — listing every metric in the system, then grepping
oodle metrics list -o json | jq '.[] | select(. | contains("http"))'

Cardinality-aware querying

Before grouping by a label, confirm cardinality is bounded:

# ✅ CORRECT — confirm `service` has <100 values before grouping by it
oodle metrics label-values http_requests_total service | wc -l

# ❌ WRONG — grouping by a high-cardinality label like `request_id` melts the query
sum by (request_id) (rate(http_requests_total[5m]))

Best Practices

Always use --match <prefix> when listing metrics

The metrics namespace can be large; an unfiltered oodle metrics list is slow and noisy.

# ✅ CORRECT
oodle metrics list --match "http_requests" -o json

# ❌ WRONG — returns thousands of results, may time out
oodle metrics list -o json

Run the 3-step discovery workflow before writing PromQL

Guessed label names produce queries that return no data and look like a metric is missing.

# ✅ CORRECT — labels confirmed by step 2, values confirmed by step 3
oodle metrics labels http_requests_total
oodle metrics label-values http_requests_total service
sum by (service) (rate(http_requests_total{service="api"}[5m]))

# ❌ WRONG — writing the query first, then debugging "why is it empty?"
sum by (service_name) (rate(http_request_count{service_name="api"}[5m]))

Always pipe to jq for scripting, never parse table output

Column ordering and widths in table output are not stable.

# ✅ CORRECT
oodle metrics list --match "http_" -o json | jq -r '.[]'

# ❌ WRONG
oodle metrics list --match "http_" | tail -n +2 | awk '{print $1}'

Prefix every counter rate with rate(...[5m]) not rate(...[1m])

[1m] rates are noisy on low-volume series and don't smooth across scrape gaps.

# ✅ CORRECT
sum by (service) (rate(http_requests_total[5m]))

# ❌ WRONG — flapping graphs, false alerts when a single scrape is missed
sum by (service) (rate(http_requests_total[1m]))

Failure Handling

References

• Oodle CLI repo
• Oodle docs
• PromQL reference