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enhancement(aws_s3 source): Adds an option max_number_of_messages for the aws_s3 source #20261

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fdamstra
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@fdamstra fdamstra commented Apr 8, 2024

Implements #20172

Allows for selection of maximum number of messages to pull from the S3 queue.

Compiled and tested for functionality.

@fdamstra fdamstra requested review from a team as code owners April 8, 2024 17:45
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bits-bot commented Apr 8, 2024

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@github-actions github-actions bot added domain: sources Anything related to the Vector's sources domain: external docs Anything related to Vector's external, public documentation labels Apr 8, 2024
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Thanks for this @fdamstra ! Out of curiosity, what happens if you set this to a count out-of-bounds like 20? I'm just wondering if maybe we should validate it upfront.

src/sources/aws_s3/sqs.rs Outdated Show resolved Hide resolved
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Requesting an additional minor update to the text

src/sources/aws_s3/sqs.rs Outdated Show resolved Hide resolved
website/cue/reference/components/sources/base/aws_s3.cue Outdated Show resolved Hide resolved
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Looks great, thanks for the changes @fdamstra !

@jszwedko jszwedko enabled auto-merge April 9, 2024 20:36
auto-merge was automatically disabled April 11, 2024 12:03

Head branch was pushed to by a user without write access

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pushed a change to fix formatting.

@jszwedko jszwedko enabled auto-merge April 11, 2024 13:56
@jszwedko jszwedko added this pull request to the merge queue Apr 11, 2024
@github-merge-queue github-merge-queue bot removed this pull request from the merge queue due to failed status checks Apr 11, 2024
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Regression Detector Results

Run ID: 2a1d5211-ab8c-407a-ac75-1998851cd8b6
Baseline: f1439bc
Comparison: 12e7808
Total CPUs: 7

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

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

No significant changes in experiment optimization goals

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

There were no significant changes in experiment optimization goals at this confidence level and effect size tolerance.

Fine details of change detection per experiment

perf experiment goal Δ mean % Δ mean % CI
syslog_log2metric_humio_metrics ingress throughput +3.26 [+3.11, +3.42]
http_text_to_http_json ingress throughput +2.51 [+2.38, +2.64]
http_to_http_acks ingress throughput +1.18 [-0.19, +2.56]
otlp_grpc_to_blackhole ingress throughput +0.86 [+0.77, +0.95]
datadog_agent_remap_datadog_logs ingress throughput +0.60 [+0.48, +0.71]
syslog_log2metric_tag_cardinality_limit_blackhole ingress throughput +0.48 [+0.36, +0.59]
splunk_hec_route_s3 ingress throughput +0.39 [-0.07, +0.85]
http_to_s3 ingress throughput +0.25 [-0.03, +0.53]
datadog_agent_remap_blackhole_acks ingress throughput +0.11 [+0.02, +0.20]
syslog_loki ingress throughput +0.11 [+0.04, +0.18]
http_to_http_noack ingress throughput +0.08 [+0.01, +0.15]
fluent_elasticsearch ingress throughput +0.03 [-0.45, +0.51]
splunk_hec_indexer_ack_blackhole ingress throughput +0.00 [-0.14, +0.15]
splunk_hec_to_splunk_hec_logs_acks ingress throughput +0.00 [-0.14, +0.14]
http_to_http_json ingress throughput -0.00 [-0.08, +0.07]
splunk_hec_to_splunk_hec_logs_noack ingress throughput -0.04 [-0.15, +0.08]
enterprise_http_to_http ingress throughput -0.13 [-0.19, -0.06]
syslog_regex_logs2metric_ddmetrics ingress throughput -0.40 [-0.51, -0.28]
file_to_blackhole egress throughput -0.50 [-3.04, +2.04]
datadog_agent_remap_blackhole ingress throughput -0.60 [-0.69, -0.50]
http_elasticsearch ingress throughput -0.84 [-0.91, -0.77]
syslog_splunk_hec_logs ingress throughput -1.30 [-1.38, -1.23]
socket_to_socket_blackhole ingress throughput -1.36 [-1.44, -1.28]
otlp_http_to_blackhole ingress throughput -1.60 [-1.72, -1.48]
datadog_agent_remap_datadog_logs_acks ingress throughput -1.72 [-1.82, -1.63]
syslog_humio_logs ingress throughput -1.73 [-1.85, -1.61]
syslog_log2metric_splunk_hec_metrics ingress throughput -2.06 [-2.20, -1.91]

Explanation

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

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

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

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

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

@jszwedko jszwedko added this pull request to the merge queue Apr 11, 2024
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Regression Detector Results

Run ID: 2f136645-0245-41de-a6d6-b2944bb98999
Baseline: f1439bc
Comparison: 153919d
Total CPUs: 7

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

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

No significant changes in experiment optimization goals

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

There were no significant changes in experiment optimization goals at this confidence level and effect size tolerance.

Fine details of change detection per experiment

perf experiment goal Δ mean % Δ mean % CI
http_text_to_http_json ingress throughput +1.89 [+1.75, +2.03]
syslog_log2metric_humio_metrics ingress throughput +1.82 [+1.62, +2.03]
file_to_blackhole egress throughput +1.77 [-0.67, +4.20]
http_to_http_acks ingress throughput +1.75 [+0.38, +3.12]
datadog_agent_remap_datadog_logs_acks ingress throughput +1.70 [+1.60, +1.80]
otlp_grpc_to_blackhole ingress throughput +1.66 [+1.57, +1.75]
fluent_elasticsearch ingress throughput +1.43 [+0.95, +1.92]
syslog_loki ingress throughput +0.45 [+0.37, +0.52]
splunk_hec_route_s3 ingress throughput +0.44 [-0.04, +0.91]
http_to_s3 ingress throughput +0.23 [-0.05, +0.51]
syslog_splunk_hec_logs ingress throughput +0.22 [+0.16, +0.28]
http_to_http_noack ingress throughput +0.12 [+0.04, +0.20]
http_to_http_json ingress throughput +0.05 [-0.02, +0.13]
splunk_hec_indexer_ack_blackhole ingress throughput +0.01 [-0.14, +0.15]
splunk_hec_to_splunk_hec_logs_acks ingress throughput +0.00 [-0.14, +0.14]
splunk_hec_to_splunk_hec_logs_noack ingress throughput -0.04 [-0.15, +0.08]
http_elasticsearch ingress throughput -0.04 [-0.13, +0.04]
syslog_regex_logs2metric_ddmetrics ingress throughput -0.09 [-0.20, +0.01]
enterprise_http_to_http ingress throughput -0.14 [-0.22, -0.07]
datadog_agent_remap_datadog_logs ingress throughput -0.44 [-0.54, -0.33]
datadog_agent_remap_blackhole ingress throughput -0.62 [-0.72, -0.52]
datadog_agent_remap_blackhole_acks ingress throughput -0.68 [-0.80, -0.56]
socket_to_socket_blackhole ingress throughput -1.02 [-1.09, -0.95]
otlp_http_to_blackhole ingress throughput -1.24 [-1.35, -1.12]
syslog_log2metric_tag_cardinality_limit_blackhole ingress throughput -1.46 [-1.57, -1.35]
syslog_log2metric_splunk_hec_metrics ingress throughput -3.16 [-3.32, -2.99]
syslog_humio_logs ingress throughput -3.33 [-3.48, -3.18]

Explanation

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

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

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

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

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

Merged via the queue into vectordotdev:master with commit 153919d Apr 11, 2024
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