chore(deps): Bump Rust to 1.75.0

[neuronull]

Apologies for not separating the clippy fixes by rust version- will keep that in mind in the future.

There weren't really many changes that required decisions. Closest being a couple of field / struct name changes.

[StephenWakely]

We should be able to get rid of at least most of our uses of async_trait with this update. Do we want to do that in a follow up PR?

[neuronull]

We should be able to get rid of at least most of our uses of async_trait with this update. Do we want to do that in a follow up PR?

I can create a follow-up PR for that, thanks for flagging.

[neuronull]

We should be able to get rid of at least most of our uses of async_trait with this update. Do we want to do that in a follow up PR?

I can create a follow-up PR for that, thanks for flagging.

Actually, I started looking into this more and it appears this limitation:

https://blog.rust-lang.org/2023/12/21/async-fn-rpit-in-traits.html#async-fn-in-public-traits

Highly affects us.

Basically all of our traits that are using async_trait, are publicly defined. I tried changing one and got the warning that is described in that blog post.
So, I think we might be better off waiting for this to get fully ironed out.

cc @StephenWakely

[bruceg]

We should be able to get rid of at least most of our uses of async_trait with this update. Do we want to do that in a follow up PR?

Only if we also increase the MSRV as well, which we haven't been doing.

[github-actions]

Regression Detector Results

Run ID: c9cea1b3-8caf-407f-8c47-395575e9f351
Baseline: aa6fd40
Comparison: 64d9f39
Total CPUs: 7

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

Significant changes in experiment optimization goals

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

perf	experiment	goal	Δ mean %	Δ mean % CI
✅	syslog_log2metric_humio_metrics	ingress throughput	+18.18	[+18.05, +18.31]
✅	syslog_loki	ingress throughput	+8.54	[+8.47, +8.60]
✅	datadog_agent_remap_blackhole_acks	ingress throughput	+8.19	[+8.09, +8.30]
✅	syslog_log2metric_splunk_hec_metrics	ingress throughput	+8.12	[+7.97, +8.27]
✅	syslog_splunk_hec_logs	ingress throughput	+8.06	[+8.00, +8.12]
✅	syslog_log2metric_tag_cardinality_limit_blackhole	ingress throughput	+7.36	[+7.24, +7.49]
✅	otlp_grpc_to_blackhole	ingress throughput	+6.78	[+6.68, +6.88]
✅	datadog_agent_remap_blackhole	ingress throughput	+6.73	[+6.62, +6.84]
✅	syslog_humio_logs	ingress throughput	+6.64	[+6.52, +6.76]
✅	datadog_agent_remap_datadog_logs_acks	ingress throughput	+6.62	[+6.53, +6.71]
✅	datadog_agent_remap_datadog_logs	ingress throughput	+5.26	[+5.16, +5.36]

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI
✅	syslog_log2metric_humio_metrics	ingress throughput	+18.18	[+18.05, +18.31]
✅	syslog_loki	ingress throughput	+8.54	[+8.47, +8.60]
✅	datadog_agent_remap_blackhole_acks	ingress throughput	+8.19	[+8.09, +8.30]
✅	syslog_log2metric_splunk_hec_metrics	ingress throughput	+8.12	[+7.97, +8.27]
✅	syslog_splunk_hec_logs	ingress throughput	+8.06	[+8.00, +8.12]
✅	syslog_log2metric_tag_cardinality_limit_blackhole	ingress throughput	+7.36	[+7.24, +7.49]
✅	otlp_grpc_to_blackhole	ingress throughput	+6.78	[+6.68, +6.88]
✅	datadog_agent_remap_blackhole	ingress throughput	+6.73	[+6.62, +6.84]
✅	syslog_humio_logs	ingress throughput	+6.64	[+6.52, +6.76]
✅	datadog_agent_remap_datadog_logs_acks	ingress throughput	+6.62	[+6.53, +6.71]
✅	datadog_agent_remap_datadog_logs	ingress throughput	+5.26	[+5.16, +5.36]
➖	splunk_hec_route_s3	ingress throughput	+4.88	[+4.37, +5.40]
➖	otlp_http_to_blackhole	ingress throughput	+3.62	[+3.46, +3.79]
➖	http_text_to_http_json	ingress throughput	+3.48	[+3.34, +3.62]
➖	fluent_elasticsearch	ingress throughput	+2.99	[+2.50, +3.48]
➖	syslog_regex_logs2metric_ddmetrics	ingress throughput	+2.40	[+2.29, +2.52]
➖	socket_to_socket_blackhole	ingress throughput	+1.90	[+1.80, +2.00]
➖	http_to_http_acks	ingress throughput	+0.73	[-0.60, +2.05]
➖	http_to_http_json	ingress throughput	+0.04	[-0.04, +0.11]
➖	http_to_http_noack	ingress throughput	+0.03	[-0.07, +0.14]
➖	splunk_hec_to_splunk_hec_logs_acks	ingress throughput	-0.01	[-0.16, +0.15]
➖	http_elasticsearch	ingress throughput	-0.01	[-0.07, +0.05]
➖	splunk_hec_indexer_ack_blackhole	ingress throughput	-0.01	[-0.16, +0.13]
➖	splunk_hec_to_splunk_hec_logs_noack	ingress throughput	-0.08	[-0.19, +0.04]
➖	enterprise_http_to_http	ingress throughput	-0.11	[-0.19, -0.03]
➖	http_to_s3	ingress throughput	-0.74	[-1.02, -0.46]
➖	file_to_blackhole	egress throughput	-1.86	[-4.38, +0.65]

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".

[datadog-vectordotdev]

Datadog Report

Branch report: neuronull/bump-rust-1.75.0
Commit report: 5033e64
Test service: vector

✅ 0 Failed, 2353 Passed, 0 Skipped, 40m 18.32s Wall Time

[StephenWakely]

Basically all of our traits that are using async_trait, are publicly defined.

Darn it. I was hoping that we would be able to get away with that given we aren't really a publicly consumed library..

[github-actions]

Regression Detector Results

Run ID: 3db62cf5-8420-428c-9bdb-82e6956d0770
Baseline: a3f0337
Comparison: b2cc788
Total CPUs: 7

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

Significant changes in experiment optimization goals

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

perf	experiment	goal	Δ mean %	Δ mean % CI
✅	syslog_log2metric_splunk_hec_metrics	ingress throughput	+12.81	[+12.65, +12.97]
✅	syslog_humio_logs	ingress throughput	+11.83	[+11.72, +11.94]
✅	otlp_http_to_blackhole	ingress throughput	+11.23	[+10.77, +11.69]
✅	syslog_splunk_hec_logs	ingress throughput	+10.76	[+10.71, +10.82]
✅	syslog_log2metric_humio_metrics	ingress throughput	+10.28	[+10.14, +10.42]
✅	syslog_log2metric_tag_cardinality_limit_blackhole	ingress throughput	+9.71	[+9.61, +9.82]
✅	syslog_loki	ingress throughput	+9.36	[+9.30, +9.42]
✅	datadog_agent_remap_datadog_logs	ingress throughput	+7.85	[+7.74, +7.96]
✅	datadog_agent_remap_datadog_logs_acks	ingress throughput	+7.69	[+7.60, +7.77]
✅	syslog_regex_logs2metric_ddmetrics	ingress throughput	+7.63	[+7.53, +7.74]
✅	socket_to_socket_blackhole	ingress throughput	+7.45	[+7.37, +7.54]
✅	otlp_grpc_to_blackhole	ingress throughput	+6.52	[+6.42, +6.62]
✅	datadog_agent_remap_blackhole_acks	ingress throughput	+5.97	[+5.85, +6.09]
✅	datadog_agent_remap_blackhole	ingress throughput	+5.62	[+5.52, +5.72]
✅	http_text_to_http_json	ingress throughput	+5.33	[+5.22, +5.45]

Fine details of change detection per experiment

perf	experiment	goal	Δ mean %	Δ mean % CI
✅	syslog_log2metric_splunk_hec_metrics	ingress throughput	+12.81	[+12.65, +12.97]
✅	syslog_humio_logs	ingress throughput	+11.83	[+11.72, +11.94]
✅	otlp_http_to_blackhole	ingress throughput	+11.23	[+10.77, +11.69]
✅	syslog_splunk_hec_logs	ingress throughput	+10.76	[+10.71, +10.82]
✅	syslog_log2metric_humio_metrics	ingress throughput	+10.28	[+10.14, +10.42]
✅	syslog_log2metric_tag_cardinality_limit_blackhole	ingress throughput	+9.71	[+9.61, +9.82]
✅	syslog_loki	ingress throughput	+9.36	[+9.30, +9.42]
✅	datadog_agent_remap_datadog_logs	ingress throughput	+7.85	[+7.74, +7.96]
✅	datadog_agent_remap_datadog_logs_acks	ingress throughput	+7.69	[+7.60, +7.77]
✅	syslog_regex_logs2metric_ddmetrics	ingress throughput	+7.63	[+7.53, +7.74]
✅	socket_to_socket_blackhole	ingress throughput	+7.45	[+7.37, +7.54]
✅	otlp_grpc_to_blackhole	ingress throughput	+6.52	[+6.42, +6.62]
✅	datadog_agent_remap_blackhole_acks	ingress throughput	+5.97	[+5.85, +6.09]
✅	datadog_agent_remap_blackhole	ingress throughput	+5.62	[+5.52, +5.72]
✅	http_text_to_http_json	ingress throughput	+5.33	[+5.22, +5.45]
➖	splunk_hec_route_s3	ingress throughput	+2.75	[+2.24, +3.25]
➖	http_elasticsearch	ingress throughput	+2.06	[+1.99, +2.12]
➖	fluent_elasticsearch	ingress throughput	+1.43	[+0.96, +1.91]
➖	file_to_blackhole	egress throughput	+0.48	[-2.08, +3.04]
➖	http_to_http_noack	ingress throughput	+0.22	[+0.13, +0.31]
➖	http_to_http_json	ingress throughput	+0.03	[-0.05, +0.10]
➖	splunk_hec_to_splunk_hec_logs_acks	ingress throughput	-0.00	[-0.16, +0.15]
➖	splunk_hec_indexer_ack_blackhole	ingress throughput	-0.01	[-0.15, +0.13]
➖	splunk_hec_to_splunk_hec_logs_noack	ingress throughput	-0.06	[-0.17, +0.05]
➖	enterprise_http_to_http	ingress throughput	-0.09	[-0.15, -0.04]
➖	http_to_s3	ingress throughput	-0.71	[-0.98, -0.44]
➖	http_to_http_acks	ingress throughput	-0.80	[-2.12, +0.52]

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".