AWS for Fluent Bit 2.29.1
2.29.1
This release includes:
- Fluent Bit 1.9.10
- Amazon CloudWatch Logs for Fluent Bit 1.9.1
- Amazon Kinesis Streams for Fluent Bit 1.10.1
- Amazon Kinesis Firehose for Fluent Bit 1.7.1
This release includes the following fixes for AWS customers that we are working on getting accepted upstream:
- Bug - Mitigate Datadog output plugin issue by reverting recent PR aws-for-fluent-bit:491
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 | ✅ | ✅ | ✅ | ||
| kinesis_firehose | tcp | Log Loss | ✅ | ✅ | ✅ |
| Log Duplication | ✅ | 0%(500) | ✅ | ||
| kinesis_streams | stdstream | Log Loss | ✅ | ✅ | 0%(10932) |
| Log Duplication | 0%(500) | 0%(23114) | 0%(117546) | ||
| kinesis_streams | tcp | Log Loss | ✅ | ✅ | ✅ |
| Log Duplication | ✅ | ✅ | 0%(29711) | ||
| 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 | ✅ | ✅ | ✅ |
| Log Duplication | ✅ | ✅ | ✅ | ||
| cloudwatch_logs | tcp | Log Loss | ✅ | ✅ | ✅ |
| 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.