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feat(new sink): Adding greptimedb metrics sink #17198

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merged 37 commits into from Jul 11, 2023

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sunng87
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@sunng87 sunng87 commented Apr 23, 2023

This patch adds greptimedb sink.

For now, we use greptimedb's git repository for adding its client. We will eventually split it from repo and publish it to crates.io, I hope this is not a road blocker at the moment.

TODOs:

  • website docs
  • spellcheck cleanup
  • integration test verification

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@github-actions github-actions bot added domain: ci Anything related to Vector's CI environment domain: sinks Anything related to the Vector's sinks labels Apr 23, 2023
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Regression Detector Results

Run ID: 7ba4bbce-0a93-445b-9a51-630c0a8ac2c7
Baseline: 5dff0ed
Comparison: 43c9d3b
Total vector CPUs: 7

Explanation

A regression test is an integrated performance test for vector in a repeatable rig, with varying configuration for vector. What follows is a statistical summary of a brief vector run for each configuration across SHAs given above. The goal of these tests are to determine quickly if vector performance is changed and to what degree by a pull request.

The table below, if present, lists those experiments that have experienced a statistically significant change in mean optimization goal performance between baseline and comparison SHAs with 90.00% confidence OR have been detected as newly erratic. Negative values mean that baseline is faster, positive comparison. Results that do not exhibit more than a ±5.00% change in their mean optimization goal are discarded. An experiment is erratic if its coefficient of variation is greater than 0.1. The abbreviated table will be omitted if no interesting change is observed.

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

Fine details of change detection per experiment.
experiment goal Δ mean Δ mean % confidence baseline mean baseline stdev baseline stderr baseline outlier % baseline CoV comparison mean comparison stdev comparison stderr comparison outlier % comparison CoV erratic declared erratic
syslog_log2metric_humio_metrics ingress throughput 265.76KiB/CPU-s 4.21 100.00% 6.16MiB/CPU-s 197.01KiB/CPU-s 2.54KiB/CPU-s 0.0 0.031207 6.42MiB/CPU-s 170.57KiB/CPU-s 2.2KiB/CPU-s 0.0 0.025926 False False
socket_to_socket_blackhole ingress throughput 269.69KiB/CPU-s 2.05 100.00% 12.85MiB/CPU-s 688.61KiB/CPU-s 8.89KiB/CPU-s 0.0 0.052328 13.11MiB/CPU-s 304.37KiB/CPU-s 3.93KiB/CPU-s 0.0 0.022665 False False
syslog_regex_logs2metric_ddmetrics ingress throughput 48.34KiB/CPU-s 1.34 100.00% 3.51MiB/CPU-s 294.41KiB/CPU-s 3.8KiB/CPU-s 0.0 0.081791 3.56MiB/CPU-s 307.74KiB/CPU-s 3.97KiB/CPU-s 0.0 0.084362 False True
http_to_http_acks ingress throughput 45.66KiB/CPU-s 0.86 63.12% 5.21MiB/CPU-s 2.7MiB/CPU-s 35.72KiB/CPU-s 0.0 0.518653 5.25MiB/CPU-s 2.73MiB/CPU-s 36.12KiB/CPU-s 0.0 0.520039 True False
datadog_agent_remap_blackhole_acks ingress throughput 263.01KiB/CPU-s 0.83 100.00% 30.79MiB/CPU-s 1.4MiB/CPU-s 18.5KiB/CPU-s 0.0 0.045452 31.05MiB/CPU-s 689.68KiB/CPU-s 8.9KiB/CPU-s 0.0 0.021692 False False
otlp_http_to_blackhole ingress throughput 8.47KiB/CPU-s 0.54 99.98% 1.52MiB/CPU-s 125.36KiB/CPU-s 1.62KiB/CPU-s 0.0 0.080583 1.53MiB/CPU-s 121.67KiB/CPU-s 1.57KiB/CPU-s 0.0 0.077789 False False
otlp_grpc_to_blackhole ingress throughput 3.47KiB/CPU-s 0.34 99.99% 1020.47KiB/CPU-s 50.98KiB/CPU-s 673.71B/CPU-s 0.0 0.049957 1023.94KiB/CPU-s 46.84KiB/CPU-s 619.08B/CPU-s 0.0 0.045743 False False
http_to_http_noack ingress throughput 3.95KiB/CPU-s 0.03 48.57% 13.61MiB/CPU-s 352.6KiB/CPU-s 4.55KiB/CPU-s 0.0 0.025298 13.61MiB/CPU-s 309.73KiB/CPU-s 4.0KiB/CPU-s 0.0 0.022216 False False
enterprise_http_to_http ingress throughput 4.11KiB/CPU-s 0.03 75.45% 13.62MiB/CPU-s 229.11KiB/CPU-s 2.96KiB/CPU-s 0.0 0.016426 13.62MiB/CPU-s 150.9KiB/CPU-s 1.95KiB/CPU-s 0.0 0.010815 False False
splunk_hec_to_splunk_hec_logs_acks ingress throughput -90.56B/CPU-s -0.00 1.05% 13.61MiB/CPU-s 369.72KiB/CPU-s 4.77KiB/CPU-s 0.0 0.026519 13.61MiB/CPU-s 369.16KiB/CPU-s 4.76KiB/CPU-s 0.0 0.026479 False False
fluent_elasticsearch ingress throughput 1.01KiB/CPU-s 0.00 93.41% 45.41MiB/CPU-s 30.25KiB/CPU-s 395.54B/CPU-s 0.0 0.00065 45.41MiB/CPU-s 30.4KiB/CPU-s 397.45B/CPU-s 0.0 0.000654 False False
splunk_hec_indexer_ack_blackhole ingress throughput -384.71B/CPU-s -0.00 6.43% 13.62MiB/CPU-s 253.72KiB/CPU-s 3.27KiB/CPU-s 0.0 0.018195 13.62MiB/CPU-s 256.7KiB/CPU-s 3.31KiB/CPU-s 0.0 0.01841 False False
splunk_hec_to_splunk_hec_logs_noack ingress throughput -3.59KiB/CPU-s -0.03 55.43% 13.62MiB/CPU-s 244.96KiB/CPU-s 3.16KiB/CPU-s 0.0 0.017564 13.61MiB/CPU-s 269.84KiB/CPU-s 3.48KiB/CPU-s 0.0 0.019354 False False
datadog_agent_remap_blackhole ingress throughput -52.26KiB/CPU-s -0.17 98.62% 30.85MiB/CPU-s 1.12MiB/CPU-s 14.82KiB/CPU-s 0.0 0.036354 30.8MiB/CPU-s 1.15MiB/CPU-s 15.19KiB/CPU-s 0.0 0.037333 False False
syslog_humio_logs ingress throughput -25.35KiB/CPU-s -0.28 100.00% 8.79MiB/CPU-s 243.76KiB/CPU-s 3.15KiB/CPU-s 0.0 0.027094 8.76MiB/CPU-s 284.67KiB/CPU-s 3.67KiB/CPU-s 0.0 0.031729 False False
splunk_hec_route_s3 ingress throughput -45.48KiB/CPU-s -0.38 100.00% 11.61MiB/CPU-s 585.66KiB/CPU-s 7.56KiB/CPU-s 0.0 0.049241 11.57MiB/CPU-s 631.91KiB/CPU-s 8.15KiB/CPU-s 0.0 0.053333 False False
datadog_agent_remap_datadog_logs ingress throughput -125.94KiB/CPU-s -0.38 100.00% 32.39MiB/CPU-s 1.1MiB/CPU-s 14.48KiB/CPU-s 0.0 0.033832 32.27MiB/CPU-s 1.37MiB/CPU-s 18.17KiB/CPU-s 0.0 0.042601 False False
syslog_splunk_hec_logs ingress throughput -49.86KiB/CPU-s -0.56 100.00% 8.71MiB/CPU-s 234.89KiB/CPU-s 3.03KiB/CPU-s 0.0 0.026341 8.66MiB/CPU-s 211.38KiB/CPU-s 2.73KiB/CPU-s 0.0 0.023838 False False
file_to_blackhole egress throughput -58.71KiB/CPU-s -0.79 23.48% 7.26MiB/CPU-s 4.05MiB/CPU-s 142.62KiB/CPU-s 0.0 0.557796 7.2MiB/CPU-s 3.85MiB/CPU-s 135.18KiB/CPU-s 0.0 0.5348 True True
datadog_agent_remap_datadog_logs_acks ingress throughput -283.18KiB/CPU-s -0.86 100.00% 32.15MiB/CPU-s 1.12MiB/CPU-s 14.79KiB/CPU-s 0.0 0.0348 31.87MiB/CPU-s 1.4MiB/CPU-s 18.5KiB/CPU-s 0.0 0.043923 False False
syslog_loki ingress throughput -77.7KiB/CPU-s -0.91 100.00% 8.3MiB/CPU-s 223.24KiB/CPU-s 2.88KiB/CPU-s 0.0 0.026266 8.22MiB/CPU-s 214.28KiB/CPU-s 2.77KiB/CPU-s 0.0 0.025444 False False
http_to_http_json ingress throughput -152.84KiB/CPU-s -1.10 100.00% 13.62MiB/CPU-s 235.68KiB/CPU-s 3.04KiB/CPU-s 0.0 0.016895 13.47MiB/CPU-s 482.19KiB/CPU-s 6.22KiB/CPU-s 0.0 0.03495 False False
syslog_log2metric_splunk_hec_metrics ingress throughput -148.62KiB/CPU-s -1.57 100.00% 9.24MiB/CPU-s 206.34KiB/CPU-s 2.66KiB/CPU-s 0.0 0.021796 9.1MiB/CPU-s 317.52KiB/CPU-s 4.1KiB/CPU-s 0.0 0.034075 False False
http_text_to_http_json ingress throughput -405.82KiB/CPU-s -1.65 100.00% 24.08MiB/CPU-s 676.04KiB/CPU-s 8.72KiB/CPU-s 0.0 0.027418 23.68MiB/CPU-s 597.22KiB/CPU-s 7.71KiB/CPU-s 0.0 0.024627 False False

@bruceg bruceg added type: feature A value-adding code addition that introduce new functionality. sink: new A request for a new sink labels Apr 24, 2023
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github-actions bot commented May 5, 2023

Regression Detector Results

Run ID: 6ca55e59-a0b3-48b1-89a6-228af0a50086
Baseline: bf7904b
Comparison: 9759ce1
Total vector CPUs: 7

Explanation

A regression test is an integrated performance test for vector in a repeatable rig, with varying configuration for vector. What follows is a statistical summary of a brief vector run for each configuration across SHAs given above. The goal of these tests are to determine quickly if vector performance is changed and to what degree by a pull request.

Because a target's optimization goal performance in each experiment will vary somewhat each time it is run, we can only estimate mean differences in optimization goal relative to the baseline target. We express these differences as a percentage change relative to the baseline target, denoted "Δ mean %". These estimates are made to a precision that balances accuracy and cost control. We represent this precision as a 90.00% confidence interval denoted "Δ mean % CI": there is a 90.00% chance that the true value of "Δ mean %" is in that interval.

We decide whether a change in performance is a "regression" -- a change worth investigating further -- if both of the following two criteria are true:

  1. The estimated |Δ mean %| ≥ 5.00%. This criterion intends to answer the question "Does the estimated change in mean optimization goal performance have a meaningful impact on your customers?". We assume that when |Δ mean %| < 5.00%, the impact on your customers is not meaningful. We also assume that a performance change in optimization goal is worth investigating whether it is an increase or decrease, so long as the magnitude of the change is sufficiently large.

  2. Zero is not in the 90.00% confidence interval "Δ mean % CI" about "Δ mean %". This statement is equivalent to saying that there is at least a 90.00% chance that the mean difference in optimization goal is not zero. This criterion intends to answer the question, "Is there a statistically significant difference in mean optimization goal performance?". It also means there is no more than a 10.00% chance this criterion reports a statistically significant difference when the true difference in mean optimization goal is zero -- a "false positive". We assume you are willing to accept a 10.00% chance of inaccurately detecting a change in performance when no true difference exists.

The table below, if present, lists those experiments that have experienced a statistically significant change in mean optimization goal performance between baseline and comparison SHAs with 90.00% confidence OR have been detected as newly erratic. Negative values of "Δ mean %" mean that baseline is faster, whereas positive values of "Δ mean %" mean that comparison is faster. Results that do not exhibit more than a ±5.00% change in their mean optimization goal are discarded. An experiment is erratic if its coefficient of variation is greater than 0.1. The abbreviated table will be omitted if no interesting change is observed.

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

Fine details of change detection per experiment.
experiment goal Δ mean % Δ mean % CI confidence
http_text_to_http_json ingress throughput +2.82 [+2.77, +2.88] 100.00%
datadog_agent_remap_datadog_logs ingress throughput +0.69 [+0.57, +0.81] 100.00%
datadog_agent_remap_blackhole ingress throughput +0.44 [+0.36, +0.52] 100.00%
syslog_splunk_hec_logs ingress throughput +0.36 [+0.29, +0.43] 100.00%
datadog_agent_remap_blackhole_acks ingress throughput +0.32 [+0.24, +0.39] 100.00%
syslog_regex_logs2metric_ddmetrics ingress throughput +0.28 [+0.02, +0.53] 84.06%
http_to_http_acks ingress throughput +0.17 [-1.05, +1.40] 14.45%
enterprise_http_to_http ingress throughput +0.05 [+0.01, +0.08] 90.29%
file_to_blackhole ingress throughput +0.03 [-0.02, +0.07] 54.73%
splunk_hec_indexer_ack_blackhole ingress throughput +0.01 [-0.03, +0.06] 34.21%
splunk_hec_to_splunk_hec_logs_noack ingress throughput +0.01 [-0.04, +0.05] 15.77%
fluent_elasticsearch ingress throughput -0.00 [-0.00, -0.00] 82.98%
splunk_hec_to_splunk_hec_logs_acks ingress throughput -0.00 [-0.07, +0.06] 6.78%
http_to_http_noack ingress throughput -0.03 [-0.09, +0.03] 47.24%
syslog_humio_logs ingress throughput -0.09 [-0.16, -0.02] 89.52%
http_to_http_json ingress throughput -0.31 [-0.37, -0.25] 100.00%
datadog_agent_remap_datadog_logs_acks ingress throughput -0.35 [-0.44, -0.25] 100.00%
syslog_log2metric_humio_metrics ingress throughput -0.69 [-0.79, -0.58] 100.00%
syslog_loki ingress throughput -0.86 [-0.92, -0.79] 100.00%
syslog_log2metric_splunk_hec_metrics ingress throughput -1.09 [-1.22, -0.96] 100.00%
socket_to_socket_blackhole ingress throughput -1.16 [-1.22, -1.11] 100.00%
otlp_grpc_to_blackhole ingress throughput -1.63 [-1.73, -1.52] 100.00%
splunk_hec_route_s3 ingress throughput -2.65 [-2.78, -2.52] 100.00%
otlp_http_to_blackhole ingress throughput -2.69 [-2.86, -2.53] 100.00%

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jszwedko commented May 8, 2023

Thanks for this submission @sunng87 !

We have a few questions:

  • We hadn't yet had a Vector user ask for this (in Github issues at least). Are you aware of Vector users needing this sink? Or is the hope that you'll grow GreptimeDB's community by way of adding integrations like these to other projects?
  • We noticed that GreptimeDB has a MySQL-compatible interface. What are the pros/cons of using that interface vs. the native client you introduced here?
  • Our team lacks familiarity with GreptimeDB. If we were to add this, would you be able to continue to support this sink in the future?

Thank you!

@sunng87
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sunng87 commented May 9, 2023

@jszwedko Thank you for your questions.

  1. GreptimeDB is relatively new and while seeking for ingestion solutions we found vector a great match. We are going to promote vector as one of our recommended agents. So it would be nice if we can upstream our sink.
  2. MySQL interface works great for data analysis scenarios. But in ingestion of devops/monitoring data, it lacks support for auto table creation, which is a road blocker for us. Although prometheus remote write and influx line protocol over http are also supported by greptimedb, we hope to use a binary and column-oriented format in our recommended agent.
  3. Yes I will. Our community and I will continuously support and improve this sink because it plays critical role in greptimedb's stack. Also I hope to contribute more to vector not only about the sink but also whole project.

@sunng87 sunng87 force-pushed the feature/greptimedb branch 5 times, most recently from 73f6b7d to 58ba5ff Compare May 9, 2023 07:20
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github-actions bot commented May 9, 2023

Regression Detector Results

Run ID: 2d2ad781-efc2-4bf1-9b10-44a877b4d151
Baseline: 9a723e3
Comparison: a934858
Total vector CPUs: 7

Explanation

A regression test is an integrated performance test for vector in a repeatable rig, with varying configuration for vector. What follows is a statistical summary of a brief vector run for each configuration across SHAs given above. The goal of these tests are to determine quickly if vector performance is changed and to what degree by a pull request.

Because a target's optimization goal performance in each experiment will vary somewhat each time it is run, we can only estimate mean differences in optimization goal relative to the baseline target. We express these differences as a percentage change relative to the baseline target, denoted "Δ mean %". These estimates are made to a precision that balances accuracy and cost control. We represent this precision as a 90.00% confidence interval denoted "Δ mean % CI": there is a 90.00% chance that the true value of "Δ mean %" is in that interval.

We decide whether a change in performance is a "regression" -- a change worth investigating further -- if both of the following two criteria are true:

  1. The estimated |Δ mean %| ≥ 5.00%. This criterion intends to answer the question "Does the estimated change in mean optimization goal performance have a meaningful impact on your customers?". We assume that when |Δ mean %| < 5.00%, the impact on your customers is not meaningful. We also assume that a performance change in optimization goal is worth investigating whether it is an increase or decrease, so long as the magnitude of the change is sufficiently large.

  2. Zero is not in the 90.00% confidence interval "Δ mean % CI" about "Δ mean %". This statement is equivalent to saying that there is at least a 90.00% chance that the mean difference in optimization goal is not zero. This criterion intends to answer the question, "Is there a statistically significant difference in mean optimization goal performance?". It also means there is no more than a 10.00% chance this criterion reports a statistically significant difference when the true difference in mean optimization goal is zero -- a "false positive". We assume you are willing to accept a 10.00% chance of inaccurately detecting a change in performance when no true difference exists.

The table below, if present, lists those experiments that have experienced a statistically significant change in mean optimization goal performance between baseline and comparison SHAs with 90.00% confidence OR have been detected as newly erratic. Negative values of "Δ mean %" mean that baseline is faster, whereas positive values of "Δ mean %" mean that comparison is faster. Results that do not exhibit more than a ±5.00% change in their mean optimization goal are discarded. An experiment is erratic if its coefficient of variation is greater than 0.1. The abbreviated table will be omitted if no interesting change is observed.

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

Fine details of change detection per experiment.
experiment goal Δ mean % Δ mean % CI confidence
syslog_log2metric_splunk_hec_metrics ingress throughput +2.32 [+2.21, +2.42] 100.00%
datadog_agent_remap_datadog_logs_acks ingress throughput +1.22 [+1.12, +1.33] 100.00%
syslog_loki ingress throughput +0.69 [+0.63, +0.76] 100.00%
datadog_agent_remap_datadog_logs ingress throughput +0.38 [+0.28, +0.47] 100.00%
syslog_splunk_hec_logs ingress throughput +0.09 [+0.03, +0.15] 93.72%
file_to_blackhole ingress throughput +0.05 [+0.00, +0.10] 80.89%
enterprise_http_to_http ingress throughput +0.04 [+0.01, +0.08] 88.60%
splunk_hec_indexer_ack_blackhole ingress throughput +0.00 [-0.04, +0.05] 4.01%
splunk_hec_to_splunk_hec_logs_acks ingress throughput +0.00 [-0.06, +0.06] 0.52%
fluent_elasticsearch ingress throughput -0.00 [-0.00, +0.00] 9.06%
syslog_humio_logs ingress throughput -0.02 [-0.09, +0.04] 35.16%
splunk_hec_to_splunk_hec_logs_noack ingress throughput -0.03 [-0.08, +0.01] 65.76%
http_to_http_noack ingress throughput -0.05 [-0.10, +0.01] 70.01%
splunk_hec_route_s3 ingress throughput -0.11 [-0.24, +0.02] 72.93%
datadog_agent_remap_blackhole_acks ingress throughput -0.51 [-0.60, -0.42] 100.00%
http_to_http_json ingress throughput -0.72 [-0.77, -0.67] 100.00%
otlp_grpc_to_blackhole ingress throughput -0.76 [-0.87, -0.66] 100.00%
syslog_regex_logs2metric_ddmetrics ingress throughput -0.84 [-1.09, -0.58] 100.00%
syslog_log2metric_humio_metrics ingress throughput -0.91 [-1.03, -0.79] 100.00%
datadog_agent_remap_blackhole ingress throughput -0.99 [-1.08, -0.90] 100.00%
http_to_http_acks ingress throughput -1.55 [-2.76, -0.34] 89.87%
otlp_http_to_blackhole ingress throughput -2.59 [-2.75, -2.44] 100.00%
http_text_to_http_json ingress throughput -3.13 [-3.22, -3.05] 100.00%
socket_to_socket_blackhole ingress throughput -3.18 [-3.23, -3.12] 100.00%

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github-actions bot commented May 9, 2023

Regression Detector Results

Run ID: 74a183fd-f850-4b07-818f-a10d8f0f56a6
Baseline: 9a723e3
Comparison: d258fac
Total vector CPUs: 7

Explanation

A regression test is an integrated performance test for vector in a repeatable rig, with varying configuration for vector. What follows is a statistical summary of a brief vector run for each configuration across SHAs given above. The goal of these tests are to determine quickly if vector performance is changed and to what degree by a pull request.

Because a target's optimization goal performance in each experiment will vary somewhat each time it is run, we can only estimate mean differences in optimization goal relative to the baseline target. We express these differences as a percentage change relative to the baseline target, denoted "Δ mean %". These estimates are made to a precision that balances accuracy and cost control. We represent this precision as a 90.00% confidence interval denoted "Δ mean % CI": there is a 90.00% chance that the true value of "Δ mean %" is in that interval.

We decide whether a change in performance is a "regression" -- a change worth investigating further -- if both of the following two criteria are true:

  1. The estimated |Δ mean %| ≥ 5.00%. This criterion intends to answer the question "Does the estimated change in mean optimization goal performance have a meaningful impact on your customers?". We assume that when |Δ mean %| < 5.00%, the impact on your customers is not meaningful. We also assume that a performance change in optimization goal is worth investigating whether it is an increase or decrease, so long as the magnitude of the change is sufficiently large.

  2. Zero is not in the 90.00% confidence interval "Δ mean % CI" about "Δ mean %". This statement is equivalent to saying that there is at least a 90.00% chance that the mean difference in optimization goal is not zero. This criterion intends to answer the question, "Is there a statistically significant difference in mean optimization goal performance?". It also means there is no more than a 10.00% chance this criterion reports a statistically significant difference when the true difference in mean optimization goal is zero -- a "false positive". We assume you are willing to accept a 10.00% chance of inaccurately detecting a change in performance when no true difference exists.

The table below, if present, lists those experiments that have experienced a statistically significant change in mean optimization goal performance between baseline and comparison SHAs with 90.00% confidence OR have been detected as newly erratic. Negative values of "Δ mean %" mean that baseline is faster, whereas positive values of "Δ mean %" mean that comparison is faster. Results that do not exhibit more than a ±5.00% change in their mean optimization goal are discarded. An experiment is erratic if its coefficient of variation is greater than 0.1. The abbreviated table will be omitted if no interesting change is observed.

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

Fine details of change detection per experiment.
experiment goal Δ mean % Δ mean % CI confidence
syslog_splunk_hec_logs ingress throughput +2.71 [+2.52, +2.90] 100.00%
syslog_regex_logs2metric_ddmetrics ingress throughput +1.95 [+1.72, +2.18] 100.00%
syslog_loki ingress throughput +0.74 [+0.67, +0.80] 100.00%
http_to_http_acks ingress throughput +0.58 [-0.64, +1.81] 45.66%
datadog_agent_remap_blackhole ingress throughput +0.38 [+0.29, +0.47] 100.00%
datadog_agent_remap_blackhole_acks ingress throughput +0.27 [+0.21, +0.34] 100.00%
enterprise_http_to_http ingress throughput +0.06 [+0.02, +0.10] 95.50%
file_to_blackhole ingress throughput +0.02 [-0.03, +0.07] 40.70%
fluent_elasticsearch ingress throughput +0.00 [-0.00, +0.00] 38.54%
http_to_http_noack ingress throughput -0.00 [-0.06, +0.06] 0.37%
splunk_hec_to_splunk_hec_logs_acks ingress throughput -0.00 [-0.06, +0.06] 1.19%
splunk_hec_indexer_ack_blackhole ingress throughput -0.00 [-0.05, +0.04] 9.07%
splunk_hec_to_splunk_hec_logs_noack ingress throughput -0.03 [-0.07, +0.02] 53.18%
syslog_log2metric_splunk_hec_metrics ingress throughput -0.08 [-0.14, -0.02] 92.20%
syslog_humio_logs ingress throughput -0.43 [-0.49, -0.37] 100.00%
http_to_http_json ingress throughput -0.43 [-0.48, -0.38] 100.00%
syslog_log2metric_humio_metrics ingress throughput -1.01 [-1.10, -0.93] 100.00%
splunk_hec_route_s3 ingress throughput -1.25 [-1.37, -1.14] 100.00%
datadog_agent_remap_datadog_logs_acks ingress throughput -1.32 [-1.40, -1.25] 100.00%
otlp_grpc_to_blackhole ingress throughput -1.46 [-1.57, -1.36] 100.00%
socket_to_socket_blackhole ingress throughput -1.70 [-1.76, -1.65] 100.00%
otlp_http_to_blackhole ingress throughput -2.02 [-2.16, -1.87] 100.00%
datadog_agent_remap_datadog_logs ingress throughput -2.76 [-2.87, -2.66] 100.00%
http_text_to_http_json ingress throughput -4.32 [-4.38, -4.26] 100.00%

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Regression Detector Results

Run ID: b965da19-08b3-483d-8577-fb89db2e9610
Baseline: 9a723e3
Comparison: 73f6b7d
Total vector CPUs: 7

Explanation

A regression test is an integrated performance test for vector in a repeatable rig, with varying configuration for vector. What follows is a statistical summary of a brief vector run for each configuration across SHAs given above. The goal of these tests are to determine quickly if vector performance is changed and to what degree by a pull request.

Because a target's optimization goal performance in each experiment will vary somewhat each time it is run, we can only estimate mean differences in optimization goal relative to the baseline target. We express these differences as a percentage change relative to the baseline target, denoted "Δ mean %". These estimates are made to a precision that balances accuracy and cost control. We represent this precision as a 90.00% confidence interval denoted "Δ mean % CI": there is a 90.00% chance that the true value of "Δ mean %" is in that interval.

We decide whether a change in performance is a "regression" -- a change worth investigating further -- if both of the following two criteria are true:

  1. The estimated |Δ mean %| ≥ 5.00%. This criterion intends to answer the question "Does the estimated change in mean optimization goal performance have a meaningful impact on your customers?". We assume that when |Δ mean %| < 5.00%, the impact on your customers is not meaningful. We also assume that a performance change in optimization goal is worth investigating whether it is an increase or decrease, so long as the magnitude of the change is sufficiently large.

  2. Zero is not in the 90.00% confidence interval "Δ mean % CI" about "Δ mean %". This statement is equivalent to saying that there is at least a 90.00% chance that the mean difference in optimization goal is not zero. This criterion intends to answer the question, "Is there a statistically significant difference in mean optimization goal performance?". It also means there is no more than a 10.00% chance this criterion reports a statistically significant difference when the true difference in mean optimization goal is zero -- a "false positive". We assume you are willing to accept a 10.00% chance of inaccurately detecting a change in performance when no true difference exists.

The table below, if present, lists those experiments that have experienced a statistically significant change in mean optimization goal performance between baseline and comparison SHAs with 90.00% confidence OR have been detected as newly erratic. Negative values of "Δ mean %" mean that baseline is faster, whereas positive values of "Δ mean %" mean that comparison is faster. Results that do not exhibit more than a ±5.00% change in their mean optimization goal are discarded. An experiment is erratic if its coefficient of variation is greater than 0.1. The abbreviated table will be omitted if no interesting change is observed.

Changes in experiment optimization goals with confidence ≥ 90.00% and |Δ mean %| ≥ 5.00%:

experiment goal Δ mean % confidence
http_to_http_acks ingress throughput +5.75 100.00%
http_text_to_http_json ingress throughput -5.92 100.00%
Fine details of change detection per experiment.
experiment goal Δ mean % Δ mean % CI confidence
http_to_http_acks ingress throughput +5.75 [+4.44, +7.05] 100.00%
syslog_regex_logs2metric_ddmetrics ingress throughput +1.44 [+1.17, +1.70] 100.00%
syslog_log2metric_splunk_hec_metrics ingress throughput +1.35 [+1.27, +1.43] 100.00%
datadog_agent_remap_blackhole_acks ingress throughput +0.67 [+0.58, +0.76] 100.00%
syslog_loki ingress throughput +0.20 [+0.13, +0.27] 99.99%
file_to_blackhole ingress throughput +0.05 [+0.00, +0.10] 80.48%
enterprise_http_to_http ingress throughput +0.04 [+0.00, +0.08] 84.13%
http_to_http_noack ingress throughput +0.01 [-0.05, +0.08] 21.92%
splunk_hec_indexer_ack_blackhole ingress throughput +0.00 [-0.04, +0.04] 2.19%
fluent_elasticsearch ingress throughput -0.00 [-0.00, +0.00] 12.60%
splunk_hec_to_splunk_hec_logs_acks ingress throughput -0.00 [-0.06, +0.06] 0.59%
splunk_hec_to_splunk_hec_logs_noack ingress throughput -0.00 [-0.05, +0.05] 2.37%
syslog_humio_logs ingress throughput -0.03 [-0.10, +0.04] 39.37%
datadog_agent_remap_blackhole ingress throughput -0.26 [-0.34, -0.18] 100.00%
otlp_grpc_to_blackhole ingress throughput -0.37 [-0.48, -0.25] 99.99%
http_to_http_json ingress throughput -0.58 [-0.63, -0.53] 100.00%
datadog_agent_remap_datadog_logs ingress throughput -0.67 [-0.76, -0.57] 100.00%
splunk_hec_route_s3 ingress throughput -0.92 [-1.04, -0.81] 100.00%
syslog_splunk_hec_logs ingress throughput -1.70 [-1.77, -1.64] 100.00%
otlp_http_to_blackhole ingress throughput -2.08 [-2.23, -1.94] 100.00%
datadog_agent_remap_datadog_logs_acks ingress throughput -2.50 [-2.61, -2.40] 100.00%
syslog_log2metric_humio_metrics ingress throughput -2.61 [-2.72, -2.51] 100.00%
socket_to_socket_blackhole ingress throughput -2.70 [-2.75, -2.64] 100.00%
http_text_to_http_json ingress throughput -5.92 [-5.97, -5.86] 100.00%

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Regression Detector Results

Run ID: 332c772f-ba44-4a79-aa50-d31934688049
Baseline: 9a723e3
Comparison: 332190b
Total vector CPUs: 7

Explanation

A regression test is an integrated performance test for vector in a repeatable rig, with varying configuration for vector. What follows is a statistical summary of a brief vector run for each configuration across SHAs given above. The goal of these tests are to determine quickly if vector performance is changed and to what degree by a pull request.

Because a target's optimization goal performance in each experiment will vary somewhat each time it is run, we can only estimate mean differences in optimization goal relative to the baseline target. We express these differences as a percentage change relative to the baseline target, denoted "Δ mean %". These estimates are made to a precision that balances accuracy and cost control. We represent this precision as a 90.00% confidence interval denoted "Δ mean % CI": there is a 90.00% chance that the true value of "Δ mean %" is in that interval.

We decide whether a change in performance is a "regression" -- a change worth investigating further -- if both of the following two criteria are true:

  1. The estimated |Δ mean %| ≥ 5.00%. This criterion intends to answer the question "Does the estimated change in mean optimization goal performance have a meaningful impact on your customers?". We assume that when |Δ mean %| < 5.00%, the impact on your customers is not meaningful. We also assume that a performance change in optimization goal is worth investigating whether it is an increase or decrease, so long as the magnitude of the change is sufficiently large.

  2. Zero is not in the 90.00% confidence interval "Δ mean % CI" about "Δ mean %". This statement is equivalent to saying that there is at least a 90.00% chance that the mean difference in optimization goal is not zero. This criterion intends to answer the question, "Is there a statistically significant difference in mean optimization goal performance?". It also means there is no more than a 10.00% chance this criterion reports a statistically significant difference when the true difference in mean optimization goal is zero -- a "false positive". We assume you are willing to accept a 10.00% chance of inaccurately detecting a change in performance when no true difference exists.

The table below, if present, lists those experiments that have experienced a statistically significant change in mean optimization goal performance between baseline and comparison SHAs with 90.00% confidence OR have been detected as newly erratic. Negative values of "Δ mean %" mean that baseline is faster, whereas positive values of "Δ mean %" mean that comparison is faster. Results that do not exhibit more than a ±5.00% change in their mean optimization goal are discarded. An experiment is erratic if its coefficient of variation is greater than 0.1. The abbreviated table will be omitted if no interesting change is observed.

Changes in experiment optimization goals with confidence ≥ 90.00% and |Δ mean %| ≥ 5.00%:

experiment goal Δ mean % confidence
syslog_regex_logs2metric_ddmetrics ingress throughput +5.67 100.00%
http_text_to_http_json ingress throughput -5.24 100.00%
socket_to_socket_blackhole ingress throughput -5.35 100.00%
splunk_hec_indexer_ack_blackhole ingress throughput -8.52 100.00%
Fine details of change detection per experiment.
experiment goal Δ mean % Δ mean % CI confidence
syslog_regex_logs2metric_ddmetrics ingress throughput +5.67 [+5.41, +5.93] 100.00%
syslog_log2metric_splunk_hec_metrics ingress throughput +1.30 [+1.19, +1.41] 100.00%
splunk_hec_route_s3 ingress throughput +1.20 [+1.08, +1.32] 100.00%
datadog_agent_remap_blackhole ingress throughput +0.38 [+0.27, +0.49] 100.00%
syslog_humio_logs ingress throughput +0.26 [+0.20, +0.32] 100.00%
file_to_blackhole ingress throughput +0.04 [-0.01, +0.09] 72.26%
enterprise_http_to_http ingress throughput +0.04 [+0.01, +0.08] 88.01%
fluent_elasticsearch ingress throughput +0.00 [-0.00, +0.00] 8.07%
http_to_http_noack ingress throughput -0.00 [-0.06, +0.06] 1.10%
splunk_hec_to_splunk_hec_logs_acks ingress throughput -0.00 [-0.06, +0.06] 2.70%
splunk_hec_to_splunk_hec_logs_noack ingress throughput -0.02 [-0.07, +0.02] 51.80%
http_to_http_acks ingress throughput -0.12 [-1.34, +1.09] 10.36%
http_to_http_json ingress throughput -0.27 [-0.31, -0.23] 100.00%
otlp_http_to_blackhole ingress throughput -0.29 [-0.48, -0.10] 95.00%
syslog_splunk_hec_logs ingress throughput -0.39 [-0.46, -0.33] 100.00%
syslog_loki ingress throughput -0.63 [-0.71, -0.55] 100.00%
syslog_log2metric_humio_metrics ingress throughput -1.07 [-1.16, -0.97] 100.00%
datadog_agent_remap_datadog_logs ingress throughput -1.52 [-1.63, -1.40] 100.00%
datadog_agent_remap_blackhole_acks ingress throughput -1.82 [-1.89, -1.75] 100.00%
datadog_agent_remap_datadog_logs_acks ingress throughput -1.85 [-1.93, -1.77] 100.00%
otlp_grpc_to_blackhole ingress throughput -1.96 [-2.07, -1.85] 100.00%
http_text_to_http_json ingress throughput -5.24 [-5.29, -5.19] 100.00%
socket_to_socket_blackhole ingress throughput -5.35 [-5.44, -5.26] 100.00%
splunk_hec_indexer_ack_blackhole ingress throughput -8.52 [-8.94, -8.09] 100.00%

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Regression Detector Results

Run ID: 8e1e7013-1c7f-4c10-8eb6-480571d5422c
Baseline: 9a723e3
Comparison: 58ba5ff
Total vector CPUs: 7

Explanation

A regression test is an integrated performance test for vector in a repeatable rig, with varying configuration for vector. What follows is a statistical summary of a brief vector run for each configuration across SHAs given above. The goal of these tests are to determine quickly if vector performance is changed and to what degree by a pull request.

Because a target's optimization goal performance in each experiment will vary somewhat each time it is run, we can only estimate mean differences in optimization goal relative to the baseline target. We express these differences as a percentage change relative to the baseline target, denoted "Δ mean %". These estimates are made to a precision that balances accuracy and cost control. We represent this precision as a 90.00% confidence interval denoted "Δ mean % CI": there is a 90.00% chance that the true value of "Δ mean %" is in that interval.

We decide whether a change in performance is a "regression" -- a change worth investigating further -- if both of the following two criteria are true:

  1. The estimated |Δ mean %| ≥ 5.00%. This criterion intends to answer the question "Does the estimated change in mean optimization goal performance have a meaningful impact on your customers?". We assume that when |Δ mean %| < 5.00%, the impact on your customers is not meaningful. We also assume that a performance change in optimization goal is worth investigating whether it is an increase or decrease, so long as the magnitude of the change is sufficiently large.

  2. Zero is not in the 90.00% confidence interval "Δ mean % CI" about "Δ mean %". This statement is equivalent to saying that there is at least a 90.00% chance that the mean difference in optimization goal is not zero. This criterion intends to answer the question, "Is there a statistically significant difference in mean optimization goal performance?". It also means there is no more than a 10.00% chance this criterion reports a statistically significant difference when the true difference in mean optimization goal is zero -- a "false positive". We assume you are willing to accept a 10.00% chance of inaccurately detecting a change in performance when no true difference exists.

The table below, if present, lists those experiments that have experienced a statistically significant change in mean optimization goal performance between baseline and comparison SHAs with 90.00% confidence OR have been detected as newly erratic. Negative values of "Δ mean %" mean that baseline is faster, whereas positive values of "Δ mean %" mean that comparison is faster. Results that do not exhibit more than a ±5.00% change in their mean optimization goal are discarded. An experiment is erratic if its coefficient of variation is greater than 0.1. The abbreviated table will be omitted if no interesting change is observed.

Changes in experiment optimization goals with confidence ≥ 90.00% and |Δ mean %| ≥ 5.00%:

experiment goal Δ mean % confidence
http_text_to_http_json ingress throughput -5.93 100.00%
Fine details of change detection per experiment.
experiment goal Δ mean % Δ mean % CI confidence
http_to_http_acks ingress throughput +0.92 [-0.32, +2.16] 66.05%
syslog_regex_logs2metric_ddmetrics ingress throughput +0.68 [+0.45, +0.92] 99.98%
file_to_blackhole ingress throughput +0.05 [-0.00, +0.10] 78.75%
enterprise_http_to_http ingress throughput +0.03 [-0.01, +0.06] 64.21%
splunk_hec_indexer_ack_blackhole ingress throughput +0.01 [-0.04, +0.05] 17.95%
fluent_elasticsearch ingress throughput +0.00 [-0.00, +0.00] 9.76%
splunk_hec_to_splunk_hec_logs_acks ingress throughput -0.00 [-0.06, +0.06] 4.24%
splunk_hec_to_splunk_hec_logs_noack ingress throughput -0.01 [-0.05, +0.04] 19.67%
syslog_log2metric_splunk_hec_metrics ingress throughput -0.03 [-0.09, +0.04] 38.96%
http_to_http_noack ingress throughput -0.05 [-0.11, +0.01] 73.10%
datadog_agent_remap_datadog_logs_acks ingress throughput -0.24 [-0.34, -0.14] 99.84%
http_to_http_json ingress throughput -0.34 [-0.38, -0.30] 100.00%
syslog_humio_logs ingress throughput -0.40 [-0.46, -0.33] 100.00%
splunk_hec_route_s3 ingress throughput -0.61 [-0.74, -0.49] 100.00%
syslog_loki ingress throughput -0.70 [-0.77, -0.64] 100.00%
syslog_splunk_hec_logs ingress throughput -0.78 [-0.85, -0.72] 100.00%
datadog_agent_remap_blackhole_acks ingress throughput -0.96 [-1.04, -0.88] 100.00%
otlp_http_to_blackhole ingress throughput -1.65 [-1.81, -1.49] 100.00%
otlp_grpc_to_blackhole ingress throughput -1.82 [-1.93, -1.71] 100.00%
datadog_agent_remap_blackhole ingress throughput -2.37 [-2.47, -2.28] 100.00%
datadog_agent_remap_datadog_logs ingress throughput -2.47 [-2.55, -2.38] 100.00%
socket_to_socket_blackhole ingress throughput -3.82 [-3.87, -3.78] 100.00%
syslog_log2metric_humio_metrics ingress throughput -4.00 [-4.12, -3.89] 100.00%
http_text_to_http_json ingress throughput -5.93 [-5.99, -5.87] 100.00%

@StephenWakely
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StephenWakely commented May 10, 2023

2. Although prometheus remote write and influx line protocol over http are also supported by greptimedb

I'm curious what the issues are with using Vector with these protocols? Is it less efficient or not as functional?

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sunng87 commented May 12, 2023

@StephenWakely I haven't fully tested those protocols via vector but I think it should work if our implementation is correct. The reason we use our own protocol is because we want a compact, controllable default ingestion protocol in our recommended agent. We can keep adding new features as our database iterates.

@github-actions github-actions bot added the domain: external docs Anything related to Vector's external, public documentation label May 22, 2023
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Regression Detector Results

Run ID: 3960fabf-fe4f-451b-913c-6d87159177b0
Baseline: 618379a
Comparison: 8f255e1
Total vector CPUs: 7

Explanation

A regression test is an integrated performance test for vector in a repeatable rig, with varying configuration for vector. What follows is a statistical summary of a brief vector run for each configuration across SHAs given above. The goal of these tests are to determine quickly if vector performance is changed and to what degree by a pull request.

Because a target's optimization goal performance in each experiment will vary somewhat each time it is run, we can only estimate mean differences in optimization goal relative to the baseline target. We express these differences as a percentage change relative to the baseline target, denoted "Δ mean %". These estimates are made to a precision that balances accuracy and cost control. We represent this precision as a 90.00% confidence interval denoted "Δ mean % CI": there is a 90.00% chance that the true value of "Δ mean %" is in that interval.

We decide whether a change in performance is a "regression" -- a change worth investigating further -- if both of the following two criteria are true:

  1. The estimated |Δ mean %| ≥ 5.00%. This criterion intends to answer the question "Does the estimated change in mean optimization goal performance have a meaningful impact on your customers?". We assume that when |Δ mean %| < 5.00%, the impact on your customers is not meaningful. We also assume that a performance change in optimization goal is worth investigating whether it is an increase or decrease, so long as the magnitude of the change is sufficiently large.

  2. Zero is not in the 90.00% confidence interval "Δ mean % CI" about "Δ mean %". This statement is equivalent to saying that there is at least a 90.00% chance that the mean difference in optimization goal is not zero. This criterion intends to answer the question, "Is there a statistically significant difference in mean optimization goal performance?". It also means there is no more than a 10.00% chance this criterion reports a statistically significant difference when the true difference in mean optimization goal is zero -- a "false positive". We assume you are willing to accept a 10.00% chance of inaccurately detecting a change in performance when no true difference exists.

The table below, if present, lists those experiments that have experienced a statistically significant change in mean optimization goal performance between baseline and comparison SHAs with 90.00% confidence OR have been detected as newly erratic. Negative values of "Δ mean %" mean that baseline is faster, whereas positive values of "Δ mean %" mean that comparison is faster. Results that do not exhibit more than a ±5.00% change in their mean optimization goal are discarded. An experiment is erratic if its coefficient of variation is greater than 0.1. The abbreviated table will be omitted if no interesting change is observed.

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

Fine details of change detection per experiment.
experiment goal Δ mean % Δ mean % CI confidence
splunk_hec_route_s3 ingress throughput +1.30 [+1.18, +1.42] 100.00%
syslog_log2metric_humio_metrics ingress throughput +0.92 [+0.83, +1.02] 100.00%
http_text_to_http_json ingress throughput +0.87 [+0.81, +0.92] 100.00%
syslog_loki ingress throughput +0.86 [+0.79, +0.93] 100.00%
datadog_agent_remap_datadog_logs ingress throughput +0.78 [+0.68, +0.87] 100.00%
datadog_agent_remap_blackhole_acks ingress throughput +0.32 [+0.25, +0.40] 100.00%
syslog_log2metric_splunk_hec_metrics ingress throughput +0.31 [+0.22, +0.41] 100.00%
enterprise_http_to_http ingress throughput +0.04 [+0.01, +0.08] 89.65%
file_to_blackhole ingress throughput +0.03 [-0.01, +0.08] 63.23%
http_to_http_noack ingress throughput +0.03 [-0.03, +0.08] 49.92%
splunk_hec_to_splunk_hec_logs_acks ingress throughput -0.00 [-0.06, +0.06] 0.31%
fluent_elasticsearch ingress throughput -0.00 [-0.00, +0.00] 21.13%
splunk_hec_indexer_ack_blackhole ingress throughput -0.01 [-0.05, +0.04] 12.79%
splunk_hec_to_splunk_hec_logs_noack ingress throughput -0.02 [-0.06, +0.03] 39.87%
syslog_humio_logs ingress throughput -0.42 [-0.47, -0.36] 100.00%
datadog_agent_remap_blackhole ingress throughput -0.58 [-0.67, -0.49] 100.00%
http_to_http_json ingress throughput -0.73 [-0.78, -0.68] 100.00%
otlp_grpc_to_blackhole ingress throughput -0.88 [-0.98, -0.78] 100.00%
otlp_http_to_blackhole ingress throughput -1.15 [-1.30, -1.00] 100.00%
syslog_splunk_hec_logs ingress throughput -1.23 [-1.29, -1.17] 100.00%
syslog_regex_logs2metric_ddmetrics ingress throughput -1.33 [-1.57, -1.08] 100.00%
datadog_agent_remap_datadog_logs_acks ingress throughput -1.72 [-1.81, -1.63] 100.00%
http_to_http_acks ingress throughput -1.88 [-3.08, -0.67] 95.42%
socket_to_socket_blackhole ingress throughput -2.16 [-2.20, -2.12] 100.00%

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Regression Detector Results

Run ID: f176870d-c7ae-4063-8728-40c582e1f837
Baseline: 618379a
Comparison: afbf89f
Total vector CPUs: 7

Explanation

A regression test is an integrated performance test for vector in a repeatable rig, with varying configuration for vector. What follows is a statistical summary of a brief vector run for each configuration across SHAs given above. The goal of these tests are to determine quickly if vector performance is changed and to what degree by a pull request.

Because a target's optimization goal performance in each experiment will vary somewhat each time it is run, we can only estimate mean differences in optimization goal relative to the baseline target. We express these differences as a percentage change relative to the baseline target, denoted "Δ mean %". These estimates are made to a precision that balances accuracy and cost control. We represent this precision as a 90.00% confidence interval denoted "Δ mean % CI": there is a 90.00% chance that the true value of "Δ mean %" is in that interval.

We decide whether a change in performance is a "regression" -- a change worth investigating further -- if both of the following two criteria are true:

  1. The estimated |Δ mean %| ≥ 5.00%. This criterion intends to answer the question "Does the estimated change in mean optimization goal performance have a meaningful impact on your customers?". We assume that when |Δ mean %| < 5.00%, the impact on your customers is not meaningful. We also assume that a performance change in optimization goal is worth investigating whether it is an increase or decrease, so long as the magnitude of the change is sufficiently large.

  2. Zero is not in the 90.00% confidence interval "Δ mean % CI" about "Δ mean %". This statement is equivalent to saying that there is at least a 90.00% chance that the mean difference in optimization goal is not zero. This criterion intends to answer the question, "Is there a statistically significant difference in mean optimization goal performance?". It also means there is no more than a 10.00% chance this criterion reports a statistically significant difference when the true difference in mean optimization goal is zero -- a "false positive". We assume you are willing to accept a 10.00% chance of inaccurately detecting a change in performance when no true difference exists.

The table below, if present, lists those experiments that have experienced a statistically significant change in mean optimization goal performance between baseline and comparison SHAs with 90.00% confidence OR have been detected as newly erratic. Negative values of "Δ mean %" mean that baseline is faster, whereas positive values of "Δ mean %" mean that comparison is faster. Results that do not exhibit more than a ±5.00% change in their mean optimization goal are discarded. An experiment is erratic if its coefficient of variation is greater than 0.1. The abbreviated table will be omitted if no interesting change is observed.

Changes in experiment optimization goals with confidence ≥ 90.00% and |Δ mean %| ≥ 5.00%:

experiment goal Δ mean % confidence
http_text_to_http_json ingress throughput +5.70 100.00%
Fine details of change detection per experiment.
experiment goal Δ mean % Δ mean % CI confidence
http_text_to_http_json ingress throughput +5.70 [+5.63, +5.76] 100.00%
datadog_agent_remap_datadog_logs ingress throughput +1.71 [+1.60, +1.83] 100.00%
syslog_loki ingress throughput +1.59 [+1.52, +1.66] 100.00%
socket_to_socket_blackhole ingress throughput +0.98 [+0.93, +1.04] 100.00%
syslog_regex_logs2metric_ddmetrics ingress throughput +0.46 [+0.21, +0.71] 98.09%
http_to_http_json ingress throughput +0.12 [+0.06, +0.18] 99.04%
enterprise_http_to_http ingress throughput +0.07 [+0.03, +0.11] 98.05%
file_to_blackhole ingress throughput +0.06 [+0.02, +0.11] 92.71%
http_to_http_noack ingress throughput +0.03 [-0.03, +0.09] 44.57%
splunk_hec_to_splunk_hec_logs_acks ingress throughput +0.00 [-0.06, +0.06] 5.26%
fluent_elasticsearch ingress throughput +0.00 [-0.00, +0.00] 8.97%
splunk_hec_indexer_ack_blackhole ingress throughput -0.00 [-0.04, +0.04] 0.54%
splunk_hec_to_splunk_hec_logs_noack ingress throughput -0.03 [-0.08, +0.01] 64.23%
syslog_log2metric_splunk_hec_metrics ingress throughput -0.29 [-0.37, -0.21] 100.00%
otlp_grpc_to_blackhole ingress throughput -0.56 [-0.67, -0.46] 100.00%
syslog_splunk_hec_logs ingress throughput -0.67 [-0.72, -0.61] 100.00%
otlp_http_to_blackhole ingress throughput -0.84 [-1.00, -0.68] 100.00%
splunk_hec_route_s3 ingress throughput -1.23 [-1.37, -1.10] 100.00%
datadog_agent_remap_blackhole ingress throughput -1.64 [-1.73, -1.55] 100.00%
datadog_agent_remap_datadog_logs_acks ingress throughput -1.73 [-1.82, -1.64] 100.00%
http_to_http_acks ingress throughput -2.22 [-3.42, -1.02] 98.22%
syslog_humio_logs ingress throughput -2.66 [-2.74, -2.58] 100.00%
datadog_agent_remap_blackhole_acks ingress throughput -4.21 [-4.30, -4.12] 100.00%
syslog_log2metric_humio_metrics ingress throughput -4.52 [-4.60, -4.44] 100.00%

@sunng87 sunng87 marked this pull request as ready for review May 23, 2023 06:48
@sunng87 sunng87 requested a review from a team as a code owner May 23, 2023 06:48
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sunng87 commented Jul 1, 2023

@StephenWakely Just added custom ca and client certificate support. And it's also possible to preview the docs now.

The CI is failing because this "Validate comment" CI check doesn't seem to be able to run on forked pull request, which has no access to secrets of this project.

By the way, we just launched preview of greptime.cloud, a hosted greptimedb-as-a-service platform. Really looking forward to have vector in our ecosystem.

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Nice, this is getting really close now. I just think we need to make sure it doesn't panic with incorrect TLS settings.

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sunng87 commented Jul 4, 2023

Updated. @StephenWakely PTAL

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Taking over from @StephenWakely. I took a look through code and everything looks good. Thank you for all the effort you put into polishing this. I've left some minor comments and suggestions that should all be straightforward.

I haven't had a chance yet to look at the documentation changes. I will hopefully have time to look through those tomorrow.

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Reference docs look good to me!

We'll be ready to approve and merge once the remaining comments are addressed.

sunng87 and others added 3 commits July 8, 2023 16:33
Co-authored-by: Doug Smith <dsmith3197@users.noreply.github.com>
Co-authored-by: Doug Smith <dsmith3197@users.noreply.github.com>
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sunng87 commented Jul 8, 2023

@dsmith3197 Thank you for your in-depth review. I've addressed all the issues. Magic numbers have been removed by test guarded constants.

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Looks amazing, thank you for addressing all the feedback!

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/ci-run-integration-greptimedb

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Awesome. This is looking really good now. Thanks!

@StephenWakely StephenWakely added this pull request to the merge queue Jul 11, 2023
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Regression Detector Results

Run ID: f6fb8ff0-17dc-4202-abf6-20087924a656
Baseline: 5b1219f
Comparison: da36a5e
Total vector CPUs: 7

Explanation

A regression test is an integrated performance test for vector in a repeatable rig, with varying configuration for vector. What follows is a statistical summary of a brief vector run for each configuration across SHAs given above. The goal of these tests are to determine quickly if vector performance is changed and to what degree by a pull request.

Because a target's optimization goal performance in each experiment will vary somewhat each time it is run, we can only estimate mean differences in optimization goal relative to the baseline target. We express these differences as a percentage change relative to the baseline target, denoted "Δ mean %". These estimates are made to a precision that balances accuracy and cost control. We represent this precision as a 90.00% confidence interval denoted "Δ mean % CI": there is a 90.00% chance that the true value of "Δ mean %" is in that interval.

We decide whether a change in performance is a "regression" -- a change worth investigating further -- if both of the following two criteria are true:

  1. The estimated |Δ mean %| ≥ 5.00%. This criterion intends to answer the question "Does the estimated change in mean optimization goal performance have a meaningful impact on your customers?". We assume that when |Δ mean %| < 5.00%, the impact on your customers is not meaningful. We also assume that a performance change in optimization goal is worth investigating whether it is an increase or decrease, so long as the magnitude of the change is sufficiently large.

  2. Zero is not in the 90.00% confidence interval "Δ mean % CI" about "Δ mean %". This statement is equivalent to saying that there is at least a 90.00% chance that the mean difference in optimization goal is not zero. This criterion intends to answer the question, "Is there a statistically significant difference in mean optimization goal performance?". It also means there is no more than a 10.00% chance this criterion reports a statistically significant difference when the true difference in mean optimization goal is zero -- a "false positive". We assume you are willing to accept a 10.00% chance of inaccurately detecting a change in performance when no true difference exists.

The table below, if present, lists those experiments that have experienced a statistically significant change in mean optimization goal performance between baseline and comparison SHAs with 90.00% confidence OR have been detected as newly erratic. Negative values of "Δ mean %" mean that baseline is faster, whereas positive values of "Δ mean %" mean that comparison is faster. Results that do not exhibit more than a ±5.00% change in their mean optimization goal are discarded. An experiment is erratic if its coefficient of variation is greater than 0.1. The abbreviated table will be omitted if no interesting change is observed.

Changes in experiment optimization goals with confidence ≥ 90.00% and |Δ mean %| ≥ 5.00%:

experiment goal Δ mean % confidence
http_text_to_http_json ingress throughput +5.22 100.00%
Fine details of change detection per experiment.
experiment goal Δ mean % Δ mean % CI confidence
http_text_to_http_json ingress throughput +5.22 [+5.14, +5.29] 100.00%
syslog_humio_logs ingress throughput +3.74 [+3.66, +3.82] 100.00%
socket_to_socket_blackhole ingress throughput +2.86 [+2.80, +2.91] 100.00%
syslog_splunk_hec_logs ingress throughput +2.62 [+2.54, +2.69] 100.00%
syslog_regex_logs2metric_ddmetrics ingress throughput +2.15 [+1.97, +2.34] 100.00%
file_to_blackhole egress throughput +2.00 [-1.95, +5.95] 48.32%
syslog_loki ingress throughput +1.80 [+1.74, +1.85] 100.00%
syslog_log2metric_humio_metrics ingress throughput +1.12 [+1.05, +1.19] 100.00%
syslog_log2metric_splunk_hec_metrics ingress throughput +0.76 [+0.67, +0.85] 100.00%
otlp_http_to_blackhole ingress throughput +0.38 [+0.25, +0.51] 99.98%
http_to_http_acks ingress throughput +0.37 [-0.89, +1.63] 29.37%
http_to_http_noack ingress throughput +0.06 [-0.00, +0.12] 78.02%
enterprise_http_to_http ingress throughput +0.03 [-0.00, +0.06] 73.57%
splunk_hec_indexer_ack_blackhole ingress throughput +0.01 [-0.03, +0.05] 22.43%
splunk_hec_to_splunk_hec_logs_noack ingress throughput +0.01 [-0.04, +0.05] 15.32%
fluent_elasticsearch ingress throughput +0.00 [+0.00, +0.00] 96.77%
splunk_hec_to_splunk_hec_logs_acks ingress throughput -0.00 [-0.06, +0.06] 1.76%
http_to_http_json ingress throughput -0.00 [-0.04, +0.03] 8.28%
otlp_grpc_to_blackhole ingress throughput -0.02 [-0.12, +0.09] 15.60%
datadog_agent_remap_blackhole ingress throughput -0.21 [-0.30, -0.13] 99.89%
datadog_agent_remap_blackhole_acks ingress throughput -0.81 [-0.88, -0.74] 100.00%
datadog_agent_remap_datadog_logs_acks ingress throughput -1.31 [-1.40, -1.22] 100.00%
splunk_hec_route_s3 ingress throughput -1.52 [-1.64, -1.39] 100.00%
datadog_agent_remap_datadog_logs ingress throughput -1.60 [-1.70, -1.49] 100.00%

@github-merge-queue github-merge-queue bot removed this pull request from the merge queue due to no response for status checks Jul 11, 2023
@StephenWakely StephenWakely added this pull request to the merge queue Jul 11, 2023
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sunng87 commented Jul 11, 2023

@StephenWakely @dsmith3197 Thank you for your help!

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Regression Detector Results

Run ID: 74d509d9-dc3d-4dde-be73-9dbc8cede15a
Baseline: 3989791
Comparison: 98f44ae
Total vector CPUs: 7

Explanation

A regression test is an integrated performance test for vector in a repeatable rig, with varying configuration for vector. What follows is a statistical summary of a brief vector run for each configuration across SHAs given above. The goal of these tests are to determine quickly if vector performance is changed and to what degree by a pull request.

Because a target's optimization goal performance in each experiment will vary somewhat each time it is run, we can only estimate mean differences in optimization goal relative to the baseline target. We express these differences as a percentage change relative to the baseline target, denoted "Δ mean %". These estimates are made to a precision that balances accuracy and cost control. We represent this precision as a 90.00% confidence interval denoted "Δ mean % CI": there is a 90.00% chance that the true value of "Δ mean %" is in that interval.

We decide whether a change in performance is a "regression" -- a change worth investigating further -- if both of the following two criteria are true:

  1. The estimated |Δ mean %| ≥ 5.00%. This criterion intends to answer the question "Does the estimated change in mean optimization goal performance have a meaningful impact on your customers?". We assume that when |Δ mean %| < 5.00%, the impact on your customers is not meaningful. We also assume that a performance change in optimization goal is worth investigating whether it is an increase or decrease, so long as the magnitude of the change is sufficiently large.

  2. Zero is not in the 90.00% confidence interval "Δ mean % CI" about "Δ mean %". This statement is equivalent to saying that there is at least a 90.00% chance that the mean difference in optimization goal is not zero. This criterion intends to answer the question, "Is there a statistically significant difference in mean optimization goal performance?". It also means there is no more than a 10.00% chance this criterion reports a statistically significant difference when the true difference in mean optimization goal is zero -- a "false positive". We assume you are willing to accept a 10.00% chance of inaccurately detecting a change in performance when no true difference exists.

The table below, if present, lists those experiments that have experienced a statistically significant change in mean optimization goal performance between baseline and comparison SHAs with 90.00% confidence OR have been detected as newly erratic. Negative values of "Δ mean %" mean that baseline is faster, whereas positive values of "Δ mean %" mean that comparison is faster. Results that do not exhibit more than a ±5.00% change in their mean optimization goal are discarded. An experiment is erratic if its coefficient of variation is greater than 0.1. The abbreviated table will be omitted if no interesting change is observed.

Changes in experiment optimization goals with confidence ≥ 90.00% and |Δ mean %| ≥ 5.00%:

experiment goal Δ mean % confidence
http_text_to_http_json ingress throughput +5.91 100.00%
Fine details of change detection per experiment.
experiment goal Δ mean % Δ mean % CI confidence
http_text_to_http_json ingress throughput +5.91 [+5.84, +5.99] 100.00%
datadog_agent_remap_blackhole ingress throughput +4.90 [+4.80, +5.00] 100.00%
socket_to_socket_blackhole ingress throughput +4.68 [+4.60, +4.75] 100.00%
file_to_blackhole egress throughput +4.48 [+0.64, +8.33] 86.47%
syslog_splunk_hec_logs ingress throughput +2.88 [+2.80, +2.96] 100.00%
otlp_http_to_blackhole ingress throughput +1.68 [+1.52, +1.84] 100.00%
syslog_humio_logs ingress throughput +1.59 [+1.49, +1.68] 100.00%
syslog_loki ingress throughput +1.41 [+1.31, +1.51] 100.00%
syslog_regex_logs2metric_ddmetrics ingress throughput +1.40 [+1.12, +1.68] 100.00%
http_to_http_acks ingress throughput +0.90 [-0.35, +2.15] 64.55%
syslog_log2metric_splunk_hec_metrics ingress throughput +0.63 [+0.54, +0.72] 100.00%
otlp_grpc_to_blackhole ingress throughput +0.25 [+0.15, +0.36] 99.73%
http_to_http_noack ingress throughput +0.03 [-0.03, +0.08] 43.89%
splunk_hec_indexer_ack_blackhole ingress throughput +0.01 [-0.04, +0.05] 16.13%
enterprise_http_to_http ingress throughput +0.00 [-0.02, +0.03] 7.42%
fluent_elasticsearch ingress throughput -0.00 [-0.00, +0.00] 2.79%
splunk_hec_to_splunk_hec_logs_noack ingress throughput -0.00 [-0.04, +0.04] 1.38%
http_to_http_json ingress throughput -0.00 [-0.04, +0.04] 6.52%
splunk_hec_to_splunk_hec_logs_acks ingress throughput -0.01 [-0.07, +0.06] 10.29%
datadog_agent_remap_blackhole_acks ingress throughput -0.05 [-0.15, +0.05] 51.01%
splunk_hec_route_s3 ingress throughput -0.65 [-0.79, -0.51] 100.00%
datadog_agent_remap_datadog_logs ingress throughput -2.32 [-2.43, -2.20] 100.00%
datadog_agent_remap_datadog_logs_acks ingress throughput -2.79 [-2.89, -2.68] 100.00%
syslog_log2metric_humio_metrics ingress throughput -4.90 [-4.99, -4.81] 100.00%

Merged via the queue into vectordotdev:master with commit 98f44ae Jul 11, 2023
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Thank you for your help!

Thank you for the contribution!

aholmberg pushed a commit to aholmberg/vector that referenced this pull request Feb 14, 2024
# [1.33.0](answerbook/vector@v1.32.1...v1.33.0) (2024-01-03)

### Bug Fixes

* allow empty message_key value in config (vectordotdev#18091) [8a2f8f6](answerbook/vector@8a2f8f6) - GitHub
* **aws provider**: Don't unwap external_id (vectordotdev#18452) [77d12ee](answerbook/vector@77d12ee) - Jesse Szwedko
* **azure_blob sink**: Base Content-Type on encoder and not compression (vectordotdev#18184) [4a049d4](answerbook/vector@4a049d4) - GitHub
* **ci**: add missing env var (vectordotdev#17872) [7e6495c](answerbook/vector@7e6495c) - GitHub
* **ci**: address issues in integration test suite workflow (vectordotdev#17928) [8b2447a](answerbook/vector@8b2447a) - GitHub
* **ci**: Drop docker-compose from bootstrap install (vectordotdev#18407) [d9db2e0](answerbook/vector@d9db2e0) - Jesse Szwedko
* **ci**: fix gardener move blocked to triage on comment (vectordotdev#18126) [93b1945](answerbook/vector@93b1945) - GitHub
* **codecs**: Move protobuf codec options under a `protobuf` key (vectordotdev#18111) [36788d1](answerbook/vector@36788d1) - GitHub
* **component validation**: make tests deterministic through absolute comparisons instead of bounds checks (vectordotdev#17956) [52a8036](answerbook/vector@52a8036) - GitHub
* **config**: Fix TOML parsing of compression levels (vectordotdev#18173) [8fc574f](answerbook/vector@8fc574f) - GitHub
* **demo gcp_pubsub internal_metrics source throttle transform**: Fix `interval` fractional second parsing (vectordotdev#17917) [b44a431](answerbook/vector@b44a431) - GitHub
* **deps**: load default and legacy openssl providers (vectordotdev#18276) [8868b07](answerbook/vector@8868b07) - Jesse Szwedko
* **dev**: fix issues when using container tools and `cargo` is not installed locally (vectordotdev#18112) [36111b5](answerbook/vector@36111b5) - GitHub
* **dev**: fix Rust toolchain check in Makefile (vectordotdev#18218) [f77fd3d](answerbook/vector@f77fd3d) - GitHub
* **docs, syslog source**: Correct docs for `syslog_ip` (vectordotdev#18003) [a1d3c3a](answerbook/vector@a1d3c3a) - GitHub
* **docs**: add the 'http_client_requests_sent_total' (vectordotdev#18299) [2dcaf30](answerbook/vector@2dcaf30) - Jesse Szwedko
* make LogEvent index operator test only (vectordotdev#18185) [0c1cf23](answerbook/vector@0c1cf23) - GitHub
* **observability**: add all events that are being encoded (vectordotdev#18289) [c9ccee0](answerbook/vector@c9ccee0) - Jesse Szwedko
* **opentelemetry source**: Remove the 4MB default for gRPC request decoding (vectordotdev#18306) [56177eb](answerbook/vector@56177eb) - Jesse Szwedko
* propagate and display invalid JSON errors in VRL web playground (vectordotdev#17826) [8519cb1](answerbook/vector@8519cb1) - GitHub
* propagate config build error instead of panicking (vectordotdev#18124) [8022464](answerbook/vector@8022464) - GitHub
* **reload**: restart api server based on topology (vectordotdev#17958) [b00727e](answerbook/vector@b00727e) - GitHub
* **spelling**: add spell check exception (vectordotdev#17906) [c4827e4](answerbook/vector@c4827e4) - GitHub
* **splunk_hec source**: insert fields as event_path so names aren't parsed as a path (vectordotdev#17943) [1acf5b4](answerbook/vector@1acf5b4) - GitHub
* **syslog source, docs**: Fix docs for `host` field for syslog source (vectordotdev#18453) [dd460a0](answerbook/vector@dd460a0) - Jesse Szwedko
* **vdev**: Add `--features` with default features for vdev test (vectordotdev#17977) [eb4383f](answerbook/vector@eb4383f) - GitHub
* **vector sink**: Add DataLoss error code as non-retryable (vectordotdev#17904) [4ef0b17](answerbook/vector@4ef0b17) - GitHub
* **vector sink**: cert verification with proxy enabled (vectordotdev#17651) [45e24c7](answerbook/vector@45e24c7) - GitHub
* **vector source**: Remove the 4MB default for requests (vectordotdev#18186) [4cc9cdf](answerbook/vector@4cc9cdf) - GitHub
* **website**: Fix installer list for MacOS (vectordotdev#18364) [3b9144c](answerbook/vector@3b9144c) - Jesse Szwedko
* **websocket sink**: send encoded message as binary frame (vectordotdev#18060) [b85f4f9](answerbook/vector@b85f4f9) - GitHub

### Chores

* Add licenses to packages (vectordotdev#18006) [db9e47f](answerbook/vector@db9e47f) - GitHub
* add more direct regression case for s3 sink (vectordotdev#18082) [c592cb1](answerbook/vector@c592cb1) - GitHub
* added sink review checklist (vectordotdev#17799) [7f45949](answerbook/vector@7f45949) - GitHub
* **api**: Refactor top and tap for library use (vectordotdev#18129) [600f819](answerbook/vector@600f819) - GitHub
* **aws provider, external_docs**: Update the AWS authentication documentation (vectordotdev#18492) [9356c56](answerbook/vector@9356c56) - Jesse Szwedko
* **azure_monitor_logs sink**: refactor to new sink style (vectordotdev#18172) [0aeb143](answerbook/vector@0aeb143) - GitHub
* **CI**: Add missing `--use-consignor` flag on `smp` call (vectordotdev#17966) [7cae000](answerbook/vector@7cae000) - GitHub
* **ci**: Bump docker/setup-buildx-action from 2.8.0 to 2.9.0 (vectordotdev#17907) [251c4c4](answerbook/vector@251c4c4) - GitHub
* **ci**: Bump docker/setup-buildx-action from 2.9.0 to 2.9.1 (vectordotdev#17955) [77ffce8](answerbook/vector@77ffce8) - GitHub
* **ci**: check for team membership on secret-requiring int tests (vectordotdev#17909) [9765809](answerbook/vector@9765809) - GitHub
* **ci**: exclude protobuf files from spell checking (vectordotdev#18152) [34eaf43](answerbook/vector@34eaf43) - GitHub
* **ci**: Feature branch should be checked against `CURRENT_BRANCH` [4742c2f](answerbook/vector@4742c2f) - Darin Spivey [LOG-18882](https://logdna.atlassian.net/browse/LOG-18882)
* **ci**: fix gardener issues comment workflow (vectordotdev#17868) [e9f21a9](answerbook/vector@e9f21a9) - GitHub
* **ci**: fix gardener issues comment workflow pt 2 (vectordotdev#17886) [57ea2b3](answerbook/vector@57ea2b3) - GitHub
* **ci**: fix gardener issues comment workflow pt 3 (vectordotdev#17903) [98ca627](answerbook/vector@98ca627) - GitHub
* **ci**: Fix integration test filter generation (vectordotdev#17914) [528fac3](answerbook/vector@528fac3) - GitHub
* **ci**: fix k8s validate comment job logic (vectordotdev#17841) [99502bb](answerbook/vector@99502bb) - GitHub
* **ci**: remove kinetic as it's no longer supported (vectordotdev#18540) [beb74c1](answerbook/vector@beb74c1) - Jesse Szwedko
* **ci**: Remove path filter that runs all integration tests (vectordotdev#17908) [70632b7](answerbook/vector@70632b7) - GitHub
* **ci**: save time int test workflow merge queue (vectordotdev#17869) [9581b35](answerbook/vector@9581b35) - GitHub
* **ci**: Set HOMEBREW_NO_INSTALL_FROM_API in CI (vectordotdev#17867) [36174e2](answerbook/vector@36174e2) - GitHub
* **CI**: Single Machine Performance: turn off consignor (vectordotdev#17967) [1dfc3e1](answerbook/vector@1dfc3e1) - GitHub
* **CI**: Switch regression detector to new API and analysis service (vectordotdev#17912) [f808ea2](answerbook/vector@f808ea2) - GitHub
* **CI**: Update `smp` to version 0.9.1 (vectordotdev#17964) [98e47c1](answerbook/vector@98e47c1) - GitHub
* **ci**: Use GitHub App token for team membership rather than user PAT (vectordotdev#17936) [7774c49](answerbook/vector@7774c49) - GitHub
* **codecs**: Update syslog_loose to properly handle escapes (vectordotdev#18114) [b009e4d](answerbook/vector@b009e4d) - GitHub
* **core**: Expose shutdown errors (vectordotdev#18153) [cd8c8b1](answerbook/vector@cd8c8b1) - GitHub
* **deps**: Bump `nkeys` to 0.3.2 (vectordotdev#18264) [a1dfd54](answerbook/vector@a1dfd54) - Jesse Szwedko
* **deps**: Bump anyhow from 1.0.71 to 1.0.72 (vectordotdev#17986) [9a6ffad](answerbook/vector@9a6ffad) - GitHub
* **deps**: Bump apache-avro from 0.14.0 to 0.15.0 (vectordotdev#17931) [d5b7fe6](answerbook/vector@d5b7fe6) - GitHub
* **deps**: Bump assert_cmd from 2.0.11 to 2.0.12 (vectordotdev#17982) [fde77bd](answerbook/vector@fde77bd) - GitHub
* **deps**: Bump async_graphql, async_graphql_warp from 5.0.10 to 6.0.0 (vectordotdev#18122) [7df6af7](answerbook/vector@7df6af7) - GitHub
* **deps**: Bump async-compression from 0.4.0 to 0.4.1 (vectordotdev#17932) [5b1219f](answerbook/vector@5b1219f) - GitHub
* **deps**: Bump async-trait from 0.1.68 to 0.1.71 (vectordotdev#17881) [53b2854](answerbook/vector@53b2854) - GitHub
* **deps**: Bump async-trait from 0.1.71 to 0.1.72 (vectordotdev#18053) [bbe2c74](answerbook/vector@bbe2c74) - GitHub
* **deps**: Bump async-trait from 0.1.72 to 0.1.73 (vectordotdev#18235) [20fa1bf](answerbook/vector@20fa1bf) - GitHub
* **deps**: Bump axum from 0.6.18 to 0.6.19 (vectordotdev#18002) [52ac10a](answerbook/vector@52ac10a) - GitHub
* **deps**: Bump axum from 0.6.19 to 0.6.20 (vectordotdev#18154) [0ddd221](answerbook/vector@0ddd221) - GitHub
* **deps**: Bump bitmask-enum from 2.1.0 to 2.2.0 (vectordotdev#17833) [fc62e9c](answerbook/vector@fc62e9c) - GitHub
* **deps**: Bump bitmask-enum from 2.2.0 to 2.2.1 (vectordotdev#17921) [6326f37](answerbook/vector@6326f37) - GitHub
* **deps**: Bump bitmask-enum from 2.2.1 to 2.2.2 (vectordotdev#18236) [851e99c](answerbook/vector@851e99c) - GitHub
* **deps**: Bump bstr from 1.5.0 to 1.6.0 (vectordotdev#17877) [17ccc56](answerbook/vector@17ccc56) - GitHub
* **deps**: Bump clap from 4.3.19 to 4.3.21 (vectordotdev#18178) [0ae3d51](answerbook/vector@0ae3d51) - GitHub
* **deps**: Bump clap_complete from 4.3.1 to 4.3.2 (vectordotdev#17878) [2126707](answerbook/vector@2126707) - GitHub
* **deps**: Bump colored from 2.0.0 to 2.0.4 (vectordotdev#17876) [93f8144](answerbook/vector@93f8144) - GitHub
* **deps**: Bump console-subscriber from 0.1.9 to 0.1.10 (vectordotdev#17844) [f74d5dd](answerbook/vector@f74d5dd) - GitHub
* **deps**: Bump darling from 0.20.1 to 0.20.3 (vectordotdev#17969) [656b1fe](answerbook/vector@656b1fe) - GitHub
* **deps**: Bump dashmap from 5.4.0 to 5.5.0 (vectordotdev#17938) [b535d18](answerbook/vector@b535d18) - GitHub
* **deps**: Bump dyn-clone from 1.0.11 to 1.0.12 (vectordotdev#17987) [81de3e5](answerbook/vector@81de3e5) - GitHub
* **deps**: Bump enum_dispatch from 0.3.11 to 0.3.12 (vectordotdev#17879) [bf1407c](answerbook/vector@bf1407c) - GitHub
* **deps**: Bump gloo-utils from 0.1.7 to 0.2.0 (vectordotdev#18227) [e61c14f](answerbook/vector@e61c14f) - GitHub
* **deps**: Bump governor from 0.5.1 to 0.6.0 (vectordotdev#17960) [467baab](answerbook/vector@467baab) - GitHub
* **deps**: Bump indicatif from 0.17.5 to 0.17.6 (vectordotdev#18146) [a7c95dd](answerbook/vector@a7c95dd) - GitHub
* **deps**: Bump indoc from 2.0.1 to 2.0.2 (vectordotdev#17843) [ed5bc3a](answerbook/vector@ed5bc3a) - GitHub
* **deps**: Bump indoc from 2.0.2 to 2.0.3 (vectordotdev#17996) [3c25758](answerbook/vector@3c25758) - GitHub
* **deps**: Bump infer from 0.14.0 to 0.15.0 (vectordotdev#17860) [97f4433](answerbook/vector@97f4433) - GitHub
* **deps**: Bump inventory from 0.3.10 to 0.3.11 (vectordotdev#18070) [d8f211e](answerbook/vector@d8f211e) - GitHub
* **deps**: Bump inventory from 0.3.6 to 0.3.8 (vectordotdev#17842) [bf2f975](answerbook/vector@bf2f975) - GitHub
* **deps**: Bump inventory from 0.3.8 to 0.3.9 (vectordotdev#17995) [9c59fea](answerbook/vector@9c59fea) - GitHub
* **deps**: Bump inventory from 0.3.9 to 0.3.10 (vectordotdev#18064) [684e43f](answerbook/vector@684e43f) - GitHub
* **deps**: Bump lapin from 2.2.1 to 2.3.1 (vectordotdev#17974) [38719a3](answerbook/vector@38719a3) - GitHub
* **deps**: Bump log from 0.4.19 to 0.4.20 (vectordotdev#18237) [cb007fe](answerbook/vector@cb007fe) - GitHub
* **deps**: Bump lru from 0.10.1 to 0.11.0 (vectordotdev#17945) [4d4b393](answerbook/vector@4d4b393) - GitHub
* **deps**: Bump metrics from 0.21.0 to 0.21.1 (vectordotdev#17836) [c8e1267](answerbook/vector@c8e1267) - GitHub
* **deps**: Bump metrics-util from 0.15.0 to 0.15.1 (vectordotdev#17835) [f91d1b2](answerbook/vector@f91d1b2) - GitHub
* **deps**: Bump nkeys from 0.3.0 to 0.3.1 (vectordotdev#18056) [087a0ac](answerbook/vector@087a0ac) - GitHub
* **deps**: Bump no-proxy from 0.3.2 to 0.3.3 (vectordotdev#18094) [9458b6c](answerbook/vector@9458b6c) - GitHub
* **deps**: Bump num-traits from 0.2.15 to 0.2.16 (vectordotdev#18039) [4de89f2](answerbook/vector@4de89f2) - GitHub
* **deps**: Bump opendal from 0.38.0 to 0.38.1 (vectordotdev#17999) [90f494c](answerbook/vector@90f494c) - GitHub
* **deps**: Bump OpenSSL base version to 3.1.* (vectordotdev#17669) [8454a6f](answerbook/vector@8454a6f) - GitHub
* **deps**: Bump openssl from 0.10.55 to 0.10.56 (vectordotdev#18170) [09610b3](answerbook/vector@09610b3) - GitHub
* **deps**: Bump paste from 1.0.12 to 1.0.13 (vectordotdev#17846) [51d8497](answerbook/vector@51d8497) - GitHub
* **deps**: Bump paste from 1.0.13 to 1.0.14 (vectordotdev#17991) [a36d36e](answerbook/vector@a36d36e) - GitHub
* **deps**: Bump pin-project from 1.1.1 to 1.1.2 (vectordotdev#17837) [17e6632](answerbook/vector@17e6632) - GitHub
* **deps**: Bump pin-project from 1.1.2 to 1.1.3 (vectordotdev#18169) [e125eee](answerbook/vector@e125eee) - GitHub
* **deps**: Bump proc-macro2 from 1.0.63 to 1.0.64 (vectordotdev#17922) [22b6c2b](answerbook/vector@22b6c2b) - GitHub
* **deps**: Bump proc-macro2 from 1.0.64 to 1.0.66 (vectordotdev#17989) [fbc0308](answerbook/vector@fbc0308) - GitHub
* **deps**: Bump quote from 1.0.29 to 1.0.31 (vectordotdev#17990) [6e552f0](answerbook/vector@6e552f0) - GitHub
* **deps**: Bump quote from 1.0.31 to 1.0.32 (vectordotdev#18069) [dc2348a](answerbook/vector@dc2348a) - GitHub
* **deps**: Bump rdkafka from 0.32.2 to 0.33.2 (vectordotdev#17891) [c8deeda](answerbook/vector@c8deeda) - GitHub
* **deps**: Bump redis from 0.23.0 to 0.23.1 (vectordotdev#18107) [48abad4](answerbook/vector@48abad4) - GitHub
* **deps**: Bump redis from 0.23.1 to 0.23.2 (vectordotdev#18234) [ec3b440](answerbook/vector@ec3b440) - GitHub
* **deps**: Bump regex from 1.8.4 to 1.9.0 (vectordotdev#17874) [cb950b0](answerbook/vector@cb950b0) - GitHub
* **deps**: Bump regex from 1.9.0 to 1.9.1 (vectordotdev#17915) [bc5822c](answerbook/vector@bc5822c) - GitHub
* **deps**: Bump regex from 1.9.1 to 1.9.3 (vectordotdev#18167) [00037b0](answerbook/vector@00037b0) - GitHub
* **deps**: Bump rmp-serde from 1.1.1 to 1.1.2 (vectordotdev#18054) [497fdce](answerbook/vector@497fdce) - GitHub
* **deps**: Bump roaring from 0.10.1 to 0.10.2 (vectordotdev#18079) [f6c53d0](answerbook/vector@f6c53d0) - GitHub
* **deps**: Bump ryu from 1.0.13 to 1.0.14 (vectordotdev#17848) [4613b36](answerbook/vector@4613b36) - GitHub
* **deps**: Bump ryu from 1.0.14 to 1.0.15 (vectordotdev#17993) [f53c687](answerbook/vector@f53c687) - GitHub
* **deps**: Bump schannel from 0.1.21 to 0.1.22 (vectordotdev#17850) [ae59be6](answerbook/vector@ae59be6) - GitHub
* **deps**: Bump security-framework from 2.9.1 to 2.9.2 (vectordotdev#18051) [b305334](answerbook/vector@b305334) - GitHub
* **deps**: Bump semver from 1.0.17 to 1.0.18 (vectordotdev#17998) [ca368d8](answerbook/vector@ca368d8) - GitHub
* **deps**: Bump semver from 5.7.1 to 5.7.2 in /website (vectordotdev#17937) [784f3fe](answerbook/vector@784f3fe) - GitHub
* **deps**: Bump serde from 1.0.167 to 1.0.168 (vectordotdev#17920) [3989791](answerbook/vector@3989791) - GitHub
* **deps**: Bump serde from 1.0.168 to 1.0.171 (vectordotdev#17976) [66f4838](answerbook/vector@66f4838) - GitHub
* **deps**: Bump serde from 1.0.171 to 1.0.173 (vectordotdev#18032) [b36c531](answerbook/vector@b36c531) - GitHub
* **deps**: Bump serde from 1.0.173 to 1.0.174 (vectordotdev#18050) [437cad6](answerbook/vector@437cad6) - GitHub
* **deps**: Bump serde from 1.0.174 to 1.0.175 (vectordotdev#18071) [16a42ed](answerbook/vector@16a42ed) - GitHub
* **deps**: Bump serde from 1.0.175 to 1.0.180 (vectordotdev#18127) [e6f2ccc](answerbook/vector@e6f2ccc) - GitHub
* **deps**: Bump serde from 1.0.180 to 1.0.181 (vectordotdev#18155) [2c51c5c](answerbook/vector@2c51c5c) - GitHub
* **deps**: Bump serde from 1.0.181 to 1.0.183 (vectordotdev#18171) [6036d5c](answerbook/vector@6036d5c) - GitHub
* **deps**: Bump serde_bytes from 0.11.11 to 0.11.12 (vectordotdev#17988) [04f9ddc](answerbook/vector@04f9ddc) - GitHub
* **deps**: Bump serde_bytes from 0.11.9 to 0.11.11 (vectordotdev#17898) [b262316](answerbook/vector@b262316) - GitHub
* **deps**: Bump serde_json from 1.0.100 to 1.0.102 (vectordotdev#17948) [4a377a7](answerbook/vector@4a377a7) - GitHub
* **deps**: Bump serde_json from 1.0.102 to 1.0.103 (vectordotdev#17992) [0ebe7a7](answerbook/vector@0ebe7a7) - GitHub
* **deps**: Bump serde_json from 1.0.103 to 1.0.104 (vectordotdev#18095) [00ed120](answerbook/vector@00ed120) - GitHub
* **deps**: Bump serde_json from 1.0.99 to 1.0.100 (vectordotdev#17859) [1a427ed](answerbook/vector@1a427ed) - GitHub
* **deps**: Bump serde_with from 3.0.0 to 3.1.0 (vectordotdev#18004) [39a2bf5](answerbook/vector@39a2bf5) - GitHub
* **deps**: Bump serde_with from 3.1.0 to 3.2.0 (vectordotdev#18162) [be551c8](answerbook/vector@be551c8) - GitHub
* **deps**: Bump serde_yaml from 0.9.22 to 0.9.24 (vectordotdev#18007) [3b91662](answerbook/vector@3b91662) - GitHub
* **deps**: Bump serde_yaml from 0.9.24 to 0.9.25 (vectordotdev#18040) [7050b7e](answerbook/vector@7050b7e) - GitHub
* **deps**: Bump smallvec from 1.10.0 to 1.11.0 (vectordotdev#17880) [46dc18a](answerbook/vector@46dc18a) - GitHub
* **deps**: Bump snafu from 0.7.4 to 0.7.5 (vectordotdev#17919) [49714cf](answerbook/vector@49714cf) - GitHub
* **deps**: Bump strip-ansi-escapes from 0.1.1 to 0.2.0 (vectordotdev#18203) [8bbe6a6](answerbook/vector@8bbe6a6) - GitHub
* **deps**: Bump syn from 2.0.23 to 2.0.25 (vectordotdev#17970) [5dfede4](answerbook/vector@5dfede4) - GitHub
* **deps**: Bump syn from 2.0.25 to 2.0.26 (vectordotdev#17994) [caf6103](answerbook/vector@caf6103) - GitHub
* **deps**: Bump syn from 2.0.26 to 2.0.27 (vectordotdev#18042) [983a92a](answerbook/vector@983a92a) - GitHub
* **deps**: Bump syn from 2.0.27 to 2.0.28 (vectordotdev#18117) [d3e5128](answerbook/vector@d3e5128) - GitHub
* **deps**: Bump thiserror from 1.0.40 to 1.0.43 (vectordotdev#17900) [ea0f5b1](answerbook/vector@ea0f5b1) - GitHub
* **deps**: Bump thiserror from 1.0.43 to 1.0.44 (vectordotdev#18052) [ee2396f](answerbook/vector@ee2396f) - GitHub
* **deps**: Bump tikv-jemallocator from 0.5.0 to 0.5.4 (vectordotdev#18102) [564104e](answerbook/vector@564104e) - GitHub
* **deps**: Bump to syn 2, serde_with 3, darling 0.20, and serde_derive_internals 0.28 (vectordotdev#17930) [3921a24](answerbook/vector@3921a24) - GitHub
* **deps**: Bump tokio from 1.29.0 to 1.29.1 (vectordotdev#17811) [0454d9d](answerbook/vector@0454d9d) - GitHub
* **deps**: Bump tokio from 1.29.1 to 1.30.0 (vectordotdev#18202) [92c2b9c](answerbook/vector@92c2b9c) - GitHub
* **deps**: Bump tokio-tungstenite from 0.19.0 to 0.20.0 (vectordotdev#18065) [3968325](answerbook/vector@3968325) - GitHub
* **deps**: Bump toml from 0.7.5 to 0.7.6 (vectordotdev#17875) [44d3a8c](answerbook/vector@44d3a8c) - GitHub
* **deps**: Bump tower-http from 0.4.1 to 0.4.2 (vectordotdev#18030) [9b4cd44](answerbook/vector@9b4cd44) - GitHub
* **deps**: Bump tower-http from 0.4.2 to 0.4.3 (vectordotdev#18055) [f1d4196](answerbook/vector@f1d4196) - GitHub
* **deps**: Bump typetag from 0.2.10 to 0.2.11 (vectordotdev#18048) [5bccafe](answerbook/vector@5bccafe) - GitHub
* **deps**: Bump typetag from 0.2.11 to 0.2.12 (vectordotdev#18066) [b70074c](answerbook/vector@b70074c) - GitHub
* **deps**: Bump typetag from 0.2.8 to 0.2.9 (vectordotdev#17882) [b10d070](answerbook/vector@b10d070) - GitHub
* **deps**: Bump typetag from 0.2.9 to 0.2.10 (vectordotdev#17968) [f4b1111](answerbook/vector@f4b1111) - GitHub
* **deps**: Bump uuid from 1.4.0 to 1.4.1 (vectordotdev#18001) [60e765d](answerbook/vector@60e765d) - GitHub
* **deps**: Bump zstd from 0.12.3+zstd.1.5.2 to 0.12.4 (vectordotdev#18031) [752056c](answerbook/vector@752056c) - GitHub
* **deps**: Remove an unneeded advisory ignore (vectordotdev#18226) [01295b0](answerbook/vector@01295b0) - GitHub
* **deps**: Swap out bloom crate for bloomy (vectordotdev#17911) [d592b0c](answerbook/vector@d592b0c) - GitHub
* **deps**: Swap tui crate for ratatui (vectordotdev#18225) [8838faf](answerbook/vector@8838faf) - GitHub
* **deps**: Update to Rust 1.71.0 (vectordotdev#18075) [1dd505f](answerbook/vector@1dd505f) - GitHub
* **deps**: Update tokio-util fork to 0.7.8 (vectordotdev#18078) [421b421](answerbook/vector@421b421) - GitHub
* **deps**: Upgrade debian usages to use bookworm (vectordotdev#18057) [fecca5e](answerbook/vector@fecca5e) - GitHub
* **deps**: Upgrade to Rust 1.71.1 (vectordotdev#18221) [eaed0a8](answerbook/vector@eaed0a8) - GitHub
* **deps**: Upgrading version of lading used (vectordotdev#18210) [91e48f6](answerbook/vector@91e48f6) - GitHub
* **dev**: Fix package install in Tiltfile (vectordotdev#18198) [f39a0e9](answerbook/vector@f39a0e9) - GitHub
* **dev**: Install dd-rust-license-tool from crates.io (vectordotdev#18025) [7d0db6b](answerbook/vector@7d0db6b) - GitHub
* **dev**: Mark loki-logproto crate as unpublished (vectordotdev#17979) [5dd2084](answerbook/vector@5dd2084) - GitHub
* **docs**: Add macOS troubleshooting section to VRL web playground (vectordotdev#17824) [0fbdb33](answerbook/vector@0fbdb33) - GitHub
* **docs**: Fix links in CONTRIBUTING.md (vectordotdev#18061) [250cc95](answerbook/vector@250cc95) - GitHub
* **docs**: Remove mentions of deprecated transforms from guides (vectordotdev#17933) [37fb02b](answerbook/vector@37fb02b) - GitHub
* **external docs**: update sink tutorials with Data Volume tag changes (vectordotdev#18148) [b2d23a8](answerbook/vector@b2d23a8) - GitHub
* Install script supports Apple ARM with Rosetta (vectordotdev#18016) [fd10e69](answerbook/vector@fd10e69) - GitHub
* **observability**: add tests to sinks for Data Volume tags (vectordotdev#17853) [4915b42](answerbook/vector@4915b42) - GitHub
* **observability**: consolidate `EventCountTags` with `TaggedEventsSent` (vectordotdev#17865) [81f5c50](answerbook/vector@81f5c50) - GitHub
* **observability**: count byte_size after transforming event (vectordotdev#17941) [0bf6abd](answerbook/vector@0bf6abd) - GitHub
* **observability**: Fix a couple typos with the registered event cache (vectordotdev#17809) [205300b](answerbook/vector@205300b) - GitHub
* **releasing**: Add 0.32.0 highlight for legacy OpenSSL provider deprecation (vectordotdev#18263) [1a32e96](answerbook/vector@1a32e96) - Jesse Szwedko
* **releasing**: Add known issues for v0.32.0 (vectordotdev#18298) [38e95b5](answerbook/vector@38e95b5) - Jesse Szwedko
* **releasing**: Add note about protobuf codec addition for 0.32.0 release (vectordotdev#18275) [91f7612](answerbook/vector@91f7612) - Jesse Szwedko
* **releasing**: Add upgrade note for 0.31.0 about S3 path changes (vectordotdev#17934) [f8461cb](answerbook/vector@f8461cb) - GitHub
* **releasing**: Bump Vector to 0.32.0 (vectordotdev#17887) [9c0d2f2](answerbook/vector@9c0d2f2) - GitHub
* **releasing**: Fix link in v0.31.0 release docs (vectordotdev#17888) [1260c83](answerbook/vector@1260c83) - GitHub
* **releasing**: Fix markdown syntax in minor release template (vectordotdev#17890) [0735ffe](answerbook/vector@0735ffe) - GitHub
* **releasing**: Prepare v0.31.0 release [aeccd26](answerbook/vector@aeccd26) - Jesse Szwedko
* **releasing**: Prepare v0.32.0 release [1b403e1](answerbook/vector@1b403e1) - Jesse Szwedko
* **releasing**: Prepare v0.32.1 release [9965884](answerbook/vector@9965884) - Jesse Szwedko
* **releasing**: Prepare v0.32.2 release [0982551](answerbook/vector@0982551) - Jesse Szwedko
* **releasing**: Regenerate k8s manifests with v0.23.0 of the chart (vectordotdev#17892) [604fea0](answerbook/vector@604fea0) - GitHub
* **releasing**: Run hadolint on distributed Dockerfiles (vectordotdev#18224) [ad08d01](answerbook/vector@ad08d01) - GitHub
* replace path tuples with actual target paths (vectordotdev#18139) [8068f1d](answerbook/vector@8068f1d) - GitHub
* replace various string paths with actual paths (vectordotdev#18109) [d8eefe3](answerbook/vector@d8eefe3) - GitHub
* **security**: Make the warning for the deprecated OpenSSL provider more verbose (vectordotdev#18278) [042fb51](answerbook/vector@042fb51) - Jesse Szwedko
* separate hanwritten and generated files in web-playground (vectordotdev#17871) [9ec0443](answerbook/vector@9ec0443) - GitHub
* stop ignoring topology test (vectordotdev#17953) [a05542a](answerbook/vector@a05542a) - GitHub
* update `rustls-webpki` due to security advisory (vectordotdev#18344) [1cb51a4](answerbook/vector@1cb51a4) - Jesse Szwedko
* Update `smp` to its latest released version (vectordotdev#18204) [7603d28](answerbook/vector@7603d28) - GitHub

### Features

* **adaptive_concurrency**: support configuring the initial ARC limit (vectordotdev#18175) [3b53bcd](answerbook/vector@3b53bcd) - GitHub
* add support for `external_id` in AWS assume role (vectordotdev#17743) [689a79e](answerbook/vector@689a79e) - GitHub
* **clickhouse sink**: make `database` and `table` templateable (vectordotdev#18005) [536a7f1](answerbook/vector@536a7f1) - GitHub
* **codecs**: add support for protobuf decoding (vectordotdev#18019) [a06c711](answerbook/vector@a06c711) - GitHub
* **component validation**: validate `component_errors_total` for sources (vectordotdev#17965) [aa60520](answerbook/vector@aa60520) - GitHub
* **deps, vrl**: Update VRL to 0.6.0 (vectordotdev#18150) [adfef2e](answerbook/vector@adfef2e) - GitHub
* emit an error if the condition return type is not a boolean (vectordotdev#18196) [caf6103](answerbook/vector@caf6103) - GitHub
* LogSchema metadata key refacoring (vectordotdev#18099) [a8bb9f4](answerbook/vector@a8bb9f4) - GitHub
* Migrate `LogSchema` `source_type_key` to new lookup code (vectordotdev#17947) [d29424d](answerbook/vector@d29424d) - GitHub
* Migrate LogSchema::host_key to new lookup code (vectordotdev#17972) [32950d8](answerbook/vector@32950d8) - GitHub
* Migrate LogSchema::message_key to new lookup code (vectordotdev#18024) [0f14c0d](answerbook/vector@0f14c0d) - GitHub
* Migrate LogSchema::metadata key to new lookup code (vectordotdev#18058) [8663602](answerbook/vector@8663602) - GitHub
* migrate to `async_nats` client (vectordotdev#18165) [483e46f](answerbook/vector@483e46f) - GitHub
* **new sink**: Adding greptimedb metrics sink (vectordotdev#17198) [98f44ae](answerbook/vector@98f44ae) - GitHub
* **new sink**: Initial `datadog_events` sink (vectordotdev#7678) [53fc86a](answerbook/vector@53fc86a) - Jesse Szwedko
* Refactor 'event.get()' to use path types (vectordotdev#18160) [e476e12](answerbook/vector@e476e12) - GitHub
* Refactor dnstap to use 'OwnedValuePath's (vectordotdev#18212) [ca7fa05](answerbook/vector@ca7fa05) - GitHub
* Refactor TraceEvent insert to use TargetPath compatible types (vectordotdev#18090) [f015b29](answerbook/vector@f015b29) - GitHub
* replace LogEvent 'String's with '&OwnedTargetPath's (vectordotdev#18084) [065eecb](answerbook/vector@065eecb) - GitHub
* replace tuples with &OwnedTargetPath wherever possible (vectordotdev#18097) [28f5c23](answerbook/vector@28f5c23) - GitHub
* switch to crates.io release of Azure SDK (vectordotdev#18166) [3c535ec](answerbook/vector@3c535ec) - GitHub

### Miscellaneous

* Merge pull request vectordotdev#379 from answerbook/feature/LOG-18882 [8bd9860](answerbook/vector@8bd9860) - GitHub [LOG-18882](https://logdna.atlassian.net/browse/LOG-18882)
* Merge branch 'master' into feature/LOG-18882 [d217387](answerbook/vector@d217387) - Darin Spivey [LOG-18882](https://logdna.atlassian.net/browse/LOG-18882)
* Merge tag 'v0.32.2' into feature/LOG-18882 [c05f969](answerbook/vector@c05f969) - Darin Spivey [LOG-18882](https://logdna.atlassian.net/browse/LOG-18882)
* Managed by Terraform provider [92e320a](answerbook/vector@92e320a) - Terraform
* 0.32.0.cue typo (vectordotdev#18270) [0f7d6e6](answerbook/vector@0f7d6e6) - Jesse Szwedko
* add PGO information (vectordotdev#18369) [3040ae2](answerbook/vector@3040ae2) - Jesse Szwedko
* check VRL conditions return type at compile time (vectordotdev#17894) [fa489f8](answerbook/vector@fa489f8) - GitHub
* **ci**: combine build steps for integration test workflows (vectordotdev#17724) [911477a](answerbook/vector@911477a) - GitHub
* describe the difference between configuration fields and runtime flags (vectordotdev#17784) [01e2dfa](answerbook/vector@01e2dfa) - GitHub
* **elasticsearch sink**: Allow empty data_stream fields (vectordotdev#18193) [1dd7bb1](answerbook/vector@1dd7bb1) - GitHub
* **file source**: fix some typos (vectordotdev#18401) [1164f55](answerbook/vector@1164f55) - Jesse Szwedko
* Fix "Bring your own toolbox" in `DEVELOPING.md` (vectordotdev#18014) [115bd7b](answerbook/vector@115bd7b) - GitHub
* Fix schema.log_namespace and telemetry.tags documentation (vectordotdev#17961) [50736e2](answerbook/vector@50736e2) - GitHub
* **internal docs**: Fix basic sink tutorial issues (vectordotdev#18136) [5a6ce73](answerbook/vector@5a6ce73) - GitHub
* **lua transform**: Emit events with the `source_id` set (vectordotdev#17870) [bc1b83a](answerbook/vector@bc1b83a) - GitHub
* **observability**: add fixed tag option to `RegisteredEventCache` (vectordotdev#17814) [bc86222](answerbook/vector@bc86222) - GitHub
* **prometheus_scrape source**: run requests in parallel with timeouts (vectordotdev#18021) [a9df958](answerbook/vector@a9df958) - GitHub
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domain: ci Anything related to Vector's CI environment domain: external docs Anything related to Vector's external, public documentation domain: sinks Anything related to the Vector's sinks sink: new A request for a new sink type: feature A value-adding code addition that introduce new functionality.
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