initiate metrics#37
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WalkthroughA new function, Changes
Sequence Diagram(s)sequenceDiagram
participant Server
participant Metrics
Server->>Metrics: initiate_metrics()
Metrics-->>Metrics: Increment request count, record zero latency
Server->>Server: Add /metrics route
Server->>Server: Start Uvicorn server
Estimated code review effort2 (10–30 minutes) Possibly related PRs
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Actionable comments posted: 1
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📒 Files selected for processing (3)
server.py(2 hunks)service_client/__init__.py(1 hunks)service_client/metrics.py(1 hunks)
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- GitHub Check: Red Hat Konflux / assisted-service-mcp-saas-main-on-pull-request
🔇 Additional comments (4)
server.py (2)
18-18: Import integration looks good.The addition of
initiate_metricsto the import statement is properly placed and follows the existing import pattern.
549-549: Metrics initialization placement is appropriate.Calling
initiate_metrics()before adding the/metricsroute ensures that metrics are properly initialized before they become available through the endpoint, which aligns with the PR objective.service_client/__init__.py (2)
10-10: Import statement correctly updated.The addition of
initiate_metricsto the import statement properly exposes the new function from the metrics module.
12-12: Public API exposure is appropriate.Adding
initiate_metricsto the__all__list correctly makes it part of the package's public API, allowing it to be imported by consumers likeserver.py.
| def initiate_metrics() -> None: | ||
| """Initiate metrics.""" | ||
| REQUEST_COUNT.labels(tool="").inc() | ||
| REQUEST_LATENCY.labels(tool="").observe(0) | ||
|
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🛠️ Refactor suggestion
Consider improving the metrics initialization approach.
While the function achieves the goal of making metrics available upon startup, there are several concerns with the current implementation:
-
Empty label concern: Using an empty string
""as the tool label may create confusing metrics output and doesn't follow Prometheus best practices for label values. -
Zero latency impact: Recording a 0-second observation in the histogram could potentially skew latency statistics and percentile calculations.
-
Lack of idempotency: The function doesn't prevent multiple calls, which could increment counters unexpectedly.
Consider this improved approach:
def initiate_metrics() -> None:
- """Initiate metrics."""
- REQUEST_COUNT.labels(tool="").inc()
- REQUEST_LATENCY.labels(tool="").observe(0)
+ """Initiate metrics by creating initial metric instances."""
+ # Initialize metrics without incrementing counters
+ # This creates the metric families in Prometheus without artificial data
+ REQUEST_COUNT.labels(tool="__init__")
+ REQUEST_LATENCY.labels(tool="__init__")Alternatively, consider initializing the metrics by simply accessing the .labels() method without incrementing/observing, which creates the metric instances without adding artificial data points.
📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| def initiate_metrics() -> None: | |
| """Initiate metrics.""" | |
| REQUEST_COUNT.labels(tool="").inc() | |
| REQUEST_LATENCY.labels(tool="").observe(0) | |
| def initiate_metrics() -> None: | |
| """Initiate metrics by creating initial metric instances.""" | |
| # Initialize metrics without incrementing counters | |
| # This creates the metric families in Prometheus without artificial data | |
| REQUEST_COUNT.labels(tool="__init__") | |
| REQUEST_LATENCY.labels(tool="__init__") |
🤖 Prompt for AI Agents
In service_client/metrics.py around lines 36 to 40, the initiate_metrics
function currently increments counters and observes zero latency with empty
string labels, which can skew metrics and produce confusing output. To fix this,
modify the function to only access the .labels() method with valid, non-empty
label values to initialize the metrics without incrementing or observing any
values. Also, ensure the function is idempotent by preventing multiple
increments or observations on repeated calls.
2 participants
part of https://issues.redhat.com/browse/MGMT-21159
metrics are published on the first increment or observe, and are unavailable until then.
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