Linux Foundation PCA Practice Test Questions Answers

According toPrometheus metric naming conventions, a metric name must clearly describewhat is being measuredand include aunit suffixthat specifies the base unit of measurement, following SI standards. For durations, the suffix _seconds is mandatory.

Therefore, the correct and standards-compliant name for a metric tracking HTTP request duration is:

http_request_duration_seconds

This name communicates:

http_request→ the subject being measured (HTTP requests),

duration→ the aspect being measured (the latency or time taken),

_seconds→ the unit of measurement (seconds).

This metric name typically corresponds to ahistogram or summary, exposing submetrics such as _count, _sum, and _bucket. These represent the number of observations, total duration, and distribution across time buckets respectively.

Options A, B, and C fail to fully comply with Prometheus naming standards — they either omit the http_ prefix, use invalid separators (dots), or lack the required unit suffix.

Following Prometheus’smetric naming conventions, every metric should indicate:

Whatit measures (the quantity or event).

The unitof measurement inbase SI unitsas a suffix.

Since the metric measuresresponse size, the base unit isbytes. Therefore, the correct and compliant metric name is:

grpc_response_size_bytes

This clearly communicates that it measures gRPC response payload sizes expressed in bytes.

The _bytes suffix is the Prometheus-recommended unit indicator for data sizes. The other options violate naming rules:

_total is reserved for counters.

_sum is used internally by histograms or summaries.

Omitting the unit (grpc_response_size) is discouraged, as it reduces clarity.

Prometheus collects metrics byscraping an HTTP endpointexposed by the target application. Therefore, theonly essential requirementfor an application to expose metrics to Prometheus is that itserves metrics in the Prometheus text exposition format over HTTP.

This endpoint is conventionally available at /metrics and provides metrics in plain text format (e.g., Content-Type: text/plain; version=0.0.4). The application can run on any operating system, architecture, or network — as long as Prometheus can reach its endpoint.

It doesnotneed to be Internet-accessible (it can be internal) and isnot limited to Linuxor any specific bitness.

In Prometheus, arule groupis a logical collection ofrecording and alerting rulesthat areevaluated sequentiallyat a specified interval. Rule groups are defined in YAML files under the groups: key, with each group containing a name, an interval, and a list of rules.

For example:

groups:

- name: example

interval: 1m

rules:

- record: job:http_inprogress_requests:sum

expr: sum(http_inprogress_requests) by (job)

All rules in a group share the same evaluation schedule and are executed one after another. This ensures deterministic order, especially when one rule depends on another’s result.

Therate()function computes theper-second increaseof a counter metric over a specified range, whilesum by (label)aggregates those rates across dimensions — in this case, the cloud label.

The correct query is:

sum by (cloud)(rate(apiserver_request_total{job="kube-apiserver"}[5m]))

This expression:

Calculates the rate of increase in API requests per second for each instance.

Groups and sums those rates by cloud, giving the total request rate per cloud provider.

Option A incorrectly places by (cloud) after rate(), which is not valid syntax.

Option B returns raw counter totals (not rates).

Option D incorrectly applies rate() after aggregation, which distorts the calculation since rate() must operate on individual time series before aggregation.