Remove call to metrics.WithResourceAttributesAsTags()

[mackjmr]

What does this PR do?

Removes call to metrics.WithResourceAttributesAsTags() which is a no-op. This option is picked up here: https://github.com/DataDog/datadog-agent/blob/main/comp/otelcol/otlp/internal/serializerexporter/factory.go#L60.

This option will been removed from pkg/otlp/metrics in this PR: DataDog/opentelemetry-mapping-go#219

Motivation

This was flagged here: open-telemetry/opentelemetry-collector-contrib#29702

Additional Notes

Possible Drawbacks / Trade-offs

Describe how to test/QA your changes

Reviewer's Checklist

• If known, an appropriate milestone has been selected; otherwise the Triage milestone is set.
• Use the major_change label if your change either has a major impact on the code base, is impacting multiple teams or is changing important well-established internals of the Agent. This label will be use during QA to make sure each team pay extra attention to the changed behavior. For any customer facing change use a releasenote.
• A release note has been added or the changelog/no-changelog label has been applied.
• Changed code has automated tests for its functionality.
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• If applicable, the k8s/<min-version> label, indicating the lowest Kubernetes version compatible with this feature.
• If applicable, the config template has been updated.

[pr-commenter]

Bloop Bleep... Dogbot Here

Regression Detector Results

Run ID: 3594742b-493d-46be-a9c3-7a510401fe41
Baseline: cfb86ca
Comparison: a479267
Total CPUs: 7

Performance changes are noted in the perf column of each table:

• ✅ denotes better comparison variant performance
• ❌ denotes worse comparison variant performance

Experiments with missing or malformed data

• idle

Usually, this warning means that there is no usable optimization goal data for that experiment, which could be a result of misconfiguration.

No interesting changes in experiment optimization goals with confidence ≥ 90.00% and |Δ mean %| ≥ 5.00%.

Declared stable experiments that are now erratic

An experiment is erratic (i.e., not stable) if its coefficient of variation is at least 0.10.

perf	experiment	goal	Δ mean %	Δ mean % CI	confidence
❌	otel_to_otel_logs	ingress throughput	-1.38	[-2.09, -0.67]	99.86%

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI	confidence
✅	file_tree	egress throughput	+0.24	[-1.55, +2.03]	17.60%
✅	file_to_blackhole	egress throughput	+0.05	[-6.12, +6.21]	0.97%
❌	dogstatsd_string_interner_8MiB_10k	ingress throughput	+0.00	[-0.00, +0.00]	0.00%
❌	dogstatsd_string_interner_8MiB_1k	ingress throughput	+0.00	[-0.00, +0.00]	0.00%
❌	dogstatsd_string_interner_8MiB_50k	ingress throughput	+0.00	[-0.00, +0.00]	0.00%
❌	dogstatsd_string_interner_64MiB_100	ingress throughput	+0.00	[-0.00, +0.00]	0.00%
❌	dogstatsd_string_interner_64MiB_1k	ingress throughput	+0.00	[-0.00, +0.00]	0.00%
❌	trace_agent_json	ingress throughput	+0.00	[-0.01, +0.01]	0.00%
❌	dogstatsd_string_interner_8MiB_100	ingress throughput	+0.00	[-0.00, +0.00]	0.00%
❌	dogstatsd_string_interner_128MiB_1k	ingress throughput	+0.00	[-0.00, +0.00]	0.00%
❌	tcp_dd_logs_filter_exclude	ingress throughput	+0.00	[-0.00, +0.00]	0.00%
❌	uds_dogstatsd_to_api	ingress throughput	+0.00	[-0.00, +0.00]	0.00%
❌	trace_agent_msgpack	ingress throughput	+0.00	[-0.00, +0.00]	0.00%
❌	dogstatsd_string_interner_128MiB_100	ingress throughput	+0.00	[-0.00, +0.00]	0.00%
❌	dogstatsd_string_interner_8MiB_100k	ingress throughput	-0.00	[-0.04, +0.04]	6.14%
❌	tcp_syslog_to_blackhole	ingress throughput	-0.33	[-0.39, -0.26]	100.00%
❌	otel_to_otel_logs	ingress throughput	-1.38	[-2.09, -0.67]	99.86%

Explanation

A regression test is an A/B test of target performance in a repeatable rig, where "performance" is measured as "comparison variant minus baseline variant" for an optimization goal (e.g., ingress throughput). Due to intrinsic variability in measuring that goal, we can only estimate its mean value for each experiment; we report uncertainty in that value as a 90.00% confidence interval denoted "Δ mean % CI".

For each experiment, we decide whether a change in performance is a "regression" -- a change worth investigating further -- if all of the following criteria are true:

1. Its estimated |Δ mean %| ≥ 5.00%, indicating the change is big enough to merit a closer look.

2. Its 90.00% confidence interval "Δ mean % CI" does not contain zero, indicating that if our statistical model is accurate, there is at least a 90.00% chance there is a difference in performance between baseline and comparison variants.

3. Its configuration does not mark it "erratic".

[cswatt]

one (minor) suggestion, approving so as to not block