chore: remove ability to make tags on a context

[tobz]

Context

We don't currently do anything with mutating the tags on a context, at least not anymore... so removing this for now to clean things up.

[tobz]

• chore: add resolver test for origin uniqueness + small cleanup #442 : 2 dependent PRs (#443 , #444 )
• chore: introduce first-class origin tags abstraction #441
• chore: slightly revamp External Data support to expose both pod and container entity ID #440
• chore: switch metric-specific destinations to use new Tagged trait for metric tags #439
• chore: make Tagged relevant to materialized tags, not raw tags #438
• chore: remove ability to make tags on a context #437 👈 (View in Graphite)
• chore: update to latest Datadog Agent RC for image builds/benchmarks #436
• main

This stack of pull requests is managed by Graphite. Learn more about stacking.

[pr-commenter]

Regression Detector (DogStatsD)

Regression Detector Results

Run ID: 091388f7-e2c9-44a7-a96a-864708896a5c

Baseline: 7.62.0-rc.8
Comparison: 7.62.0-rc.8

Optimization Goals: ✅ No significant changes detected

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
➖	dsd_uds_10mb_3k_contexts	ingress throughput	+0.00	[-0.00, +0.01]	1
➖	dsd_uds_100mb_3k_contexts	ingress throughput	+0.00	[-0.05, +0.05]	1
➖	dsd_uds_512kb_3k_contexts	ingress throughput	+0.00	[-0.01, +0.01]	1
➖	dsd_uds_1mb_3k_contexts	ingress throughput	+0.00	[-0.00, +0.00]	1
➖	dsd_uds_100mb_250k_contexts	ingress throughput	+0.00	[-0.00, +0.00]	1
➖	dsd_uds_1mb_50k_contexts_memlimit	ingress throughput	-0.00	[-0.00, +0.00]	1
➖	dsd_uds_1mb_50k_contexts	ingress throughput	-0.00	[-0.00, +0.00]	1
➖	dsd_uds_1mb_3k_contexts_dualship	ingress throughput	-0.00	[-0.00, +0.00]	1
➖	dsd_uds_40mb_12k_contexts_40_senders	ingress throughput	-0.00	[-0.00, +0.00]	1
➖	dsd_uds_500mb_3k_contexts	ingress throughput	-0.00	[-0.01, +0.01]	1
➖	dsd_uds_100mb_3k_contexts_distributions_only	memory utilization	-1.26	[-1.47, -1.06]	1
➖	quality_gates_idle_rss	memory utilization	-1.52	[-1.60, -1.44]	1

Bounds Checks: ❌ Failed

perf	experiment	bounds_check_name	replicates_passed	links
❌	quality_gates_idle_rss	memory_usage	0/10

Explanation

Confidence level: 90.00%
Effect size tolerance: |Δ mean %| ≥ 5.00%

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

• ✅ = significantly better comparison variant performance
• ❌ = significantly worse comparison variant performance
• ➖ = no significant change in performance

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".

[pr-commenter]

Regression Detector (Saluki)

Regression Detector Results

Run ID: 5f7835f3-77f8-472f-ad2d-e27cdeb0f49a

Baseline: 507fe24
Comparison: df12b22
Diff

❌ Experiments with missing or malformed data

This is a critical error. No usable optimization goal data was produced by the listed experiments. This may be a result of misconfiguration. Ping #single-machine-performance and we can help out.

• dsd_uds_100mb_250k_contexts

Optimization Goals: ✅ No significant changes detected

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI	trials	links
➖	dsd_uds_500mb_3k_contexts	ingress throughput	+0.83	[+0.71, +0.95]	1
➖	dsd_uds_1mb_50k_contexts_memlimit	ingress throughput	+0.20	[-0.28, +0.67]	1
➖	dsd_uds_10mb_3k_contexts	ingress throughput	+0.02	[-0.00, +0.05]	1
➖	dsd_uds_50mb_10k_contexts_no_inlining	ingress throughput	+0.01	[-0.06, +0.08]	1
➖	dsd_uds_50mb_10k_contexts_no_inlining_no_allocs	ingress throughput	+0.00	[-0.06, +0.06]	1
➖	dsd_uds_1mb_50k_contexts	ingress throughput	+0.00	[-0.00, +0.01]	1
➖	dsd_uds_512kb_3k_contexts	ingress throughput	-0.00	[-0.01, +0.01]	1
➖	dsd_uds_1mb_3k_contexts	ingress throughput	-0.00	[-0.00, +0.00]	1
➖	dsd_uds_100mb_3k_contexts	ingress throughput	-0.00	[-0.05, +0.04]	1
➖	quality_gates_idle_rss	memory utilization	-0.01	[-0.04, +0.02]	1
➖	dsd_uds_40mb_12k_contexts_40_senders	ingress throughput	-0.01	[-0.04, +0.02]	1
➖	dsd_uds_1mb_3k_contexts_dualship	ingress throughput	-0.02	[-0.03, +0.00]	1
➖	dsd_uds_100mb_3k_contexts_distributions_only	memory utilization	-0.97	[-1.10, -0.84]	1

Bounds Checks: ✅ Passed

perf	experiment	bounds_check_name	replicates_passed	links
✅	quality_gates_idle_rss	memory_usage	10/10

Explanation

Confidence level: 90.00%
Effect size tolerance: |Δ mean %| ≥ 5.00%

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

• ✅ = significantly better comparison variant performance
• ❌ = significantly worse comparison variant performance
• ➖ = no significant change in performance

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".

[pr-commenter]

Regression Detector Links

Experiment Result Links

experiment	link(s)
dsd_uds_100mb_250k_contexts	[Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_100mb_3k_contexts	[Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_100mb_3k_contexts_distributions_only	[Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_10mb_3k_contexts	[Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_1mb_3k_contexts	[Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_1mb_3k_contexts_dualship	[Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_1mb_50k_contexts	[Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_1mb_50k_contexts_memlimit	[Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_40mb_12k_contexts_40_senders	[Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_500mb_3k_contexts	[Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_512kb_3k_contexts	[Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
quality_gates_idle_rss	[Profiling (ADP)] [Profiling (DSD)] [SMP Dashboard]
dsd_uds_50mb_10k_contexts_no_inlining (ADP only)	[Profiling (ADP)] [SMP Dashboard]
dsd_uds_50mb_10k_contexts_no_inlining_no_allocs (ADP only)	[Profiling (ADP)] [SMP Dashboard]