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AWS for Fluent Bit 2.31.11

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@PettitWesley PettitWesley released this 16 May 17:38
· 146 commits to mainline since this release

2.31.11

This release includes:

  • Fluent Bit 1.9.10
  • Amazon CloudWatch Logs for Fluent Bit 1.9.3
  • Amazon Kinesis Streams for Fluent Bit 1.10.2
  • Amazon Kinesis Firehose for Fluent Bit 1.7.2

Compared to 2.31.10 this release adds:

  • Bug - Improve parsing of STS AssumeRole response fluent-bit:7313
  • Bug - Fix potential null dereference in configuration parsing fluent-bit:6874
  • Bug - ElasticSearch output: fix potential bulk buffer over-run fluent-bit:5770
  • Bug - Fix parsing of time zone offsets on Windows fluent-bit:6368
  • Bug - Fix memory cleanup of failed retries fluent-bit:6862
  • Bug - Fix printf format string in flb_time_pop_from_mpack warning fluent-bit:7262
  • Enhancement - TCP Input: user friendly warning message when records are skipped fluent-bit:6061

We’ve run the new released image in our ECS load testing framework and here is the result. This testing result provides benchmarks of aws-for-fluent-bit under different input load. Learn more about the load test.

plugin source 20 MB/s 25 MB/s 30 MB/s
kinesis_firehose stdstream Log Loss
Log Duplication 0%(4500) 0%(1000)
kinesis_firehose tcp Log Loss
Log Duplication 0%(7500) 0%(5500)
kinesis_streams stdstream Log Loss 0%(5462)
Log Duplication 0%(1000) 0%(19597) 0%(123943)
kinesis_streams tcp Log Loss 0%(4237)
Log Duplication 0%(20278) 0%(43773) 0%(111891)
s3 stdstream Log Loss
Log Duplication
s3 tcp Log Loss
Log Duplication
plugin source 1 MB/s 2 MB/s 3 MB/s
cloudwatch_logs stdstream Log Loss 1%(21569) 16%(297769)
Log Duplication
cloudwatch_logs tcp Log Loss 16%(200244)
Log Duplication

Note:

  • The green check ✅ in the table means no log loss or no log duplication.
  • Number in parentheses means the number of records out of total records. For example, 0%(1064/1.8M) under 30Mb/s throughput means 1064 duplicate records out of 18M input records by which log duplication percentage is 0%.
  • Log loss is the percentage of data lost and log duplication is the percentage of duplicate logs received at the destination. Your results may differ because they can be influenced by many factors like different configs and environment settings. Log duplication is exclusively caused by partially succeeded batches that were retried, which means it is random.