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Flowgger is a lightweight, single-executable data collector written in Rust that reads logs from multiple input sources (UDP, TCP, TLS, Redis, stdin), parses them in various formats (JSON/GELF, LTSV, Cap'n Proto, RFC5424), and forwards them to downstream systems like Kafka or Graylog. It emphasizes speed, memory efficiency, and safety through Rust's memory guarantees without unsafe code.
Key facts
Objective fields from the source. Values we can't verify are shown as “Unknown” rather than guessed.
| Field | Value |
|---|---|
| Repository | awslabs/flowgger |
| Owner | awslabs |
| Primary language | Rust |
| License | BSD-2-Clause — OSI-approved |
| Stars | 882 |
| Forks | 60 |
| Open issues | 15 |
| Latest release | 0.3.2 (2024-05-17) |
| Last updated | 2025-06-23 |
| Source | https://github.com/awslabs/flowgger |
What flowgger is
A standalone log ingestion pipeline written in Rust that decodes structured and semi-structured logs, validates input rigorously, and re-encodes into target formats for asynchronous delivery to Kafka, Graylog, or other collectors. Avoids JVM overhead and uses async I/O to handle high-volume message streams.
Get the flowgger source
Clone the repository and explore it locally.
git clone https://github.com/awslabs/flowgger.gitcd flowgger# follow the project's README for install & configurationNeed it deployed, integrated, or customized instead? DEV.co ships production installs.
Best use cases
Implementation considerations
- Configuration is TOML-based; review flowgger.toml schema and the v0.3.0 breaking change from strftime to the `time` crate's format_description syntax.
- Validate input protocol and format support matches your sources (stdin, UDP/TCP/TLS for intake; Kafka/Graylog/Redis for egress).
- Deploy as a single binary; ensure your infrastructure can execute Rust binaries or use pre-built releases (verify availability for your OS/arch).
- No unsafe code is used, but test the version you plan to deploy against your log volume and latency requirements.
- Monitor the 15 open issues; assess if any block your use case or warrant a fork/patch.
When to avoid it — and what to weigh
- Require extensive built-in transformations or field enrichment — Flowgger focuses on parsing and forwarding; complex conditional logic, lookups, or data enrichment require external orchestration or custom extensions.
- Depend on a large ecosystem of plugins and integrations — The project has a narrower integration surface than Logstash or Fluentd; unsupported input/output formats may require code contributions.
- Need commercial support or SLA guarantees — AWS Labs project with community-driven maintenance; no official commercial support tier documented.
- Expect frequent feature releases and rapid evolution — Release cadence is infrequent (v0.3.2 in May 2024 after ~2 years); breaking changes (e.g., chrono→time) may require configuration updates.
License & commercial use
BSD 2-Clause license. Permissive OSI-approved license allowing commercial use, modification, and distribution with attribution and liability disclaimer.
BSD 2-Clause is permissive and does not restrict commercial use or proprietary deployment. However, AWS Labs maintains the project without formal commercial support. Ensure your legal and compliance teams review the license for your specific use case, and consider the implications of depending on a community-maintained AWS project for production log infrastructure.
DEV.co evaluation signals
Editorial assessment — not user reviews. Directional, with an explicit confidence level.
| Signal | Assessment |
|---|---|
| Maintenance | Moderate |
| Documentation | Adequate |
| License clarity | Clear |
| Deployment complexity | Low |
| DEV.co fit | Good |
| Assessment confidence | High |
Written in Rust without unsafe code, leveraging memory safety guarantees. Input validation is emphasized as a design goal. No known CVEs are evident from the data provided, but review dependency chain (especially after v0.3.0's migration from chrono to time due to RUSTSEC-2020-0071). TLS is supported for encrypted transport. Requires standard operational security practices: least-privilege service accounts, network segmentation, credential rotation, and regular dependency audits.
Alternatives to consider
Logstash (Elastic)
Full-featured log processing pipeline with extensive plugins; heavier resource footprint (requires JVM). Mature commercial support. Consider if you need advanced transformations or have existing Elastic Stack investment.
Fluentd / Fluent Bit
Lightweight, multi-format log forwarder; Fluent Bit is especially suited for edge/container workloads. More established plugin ecosystem. Consider if you prioritize ecosystem size over binary compactness.
Vector (Timber.io)
Modern Rust-based log/metric/trace collector with broad integrations and built-in transformations. Active commercial backing and rapid release cadence. Consider if you need richer data pipeline orchestration.
Build on flowgger with DEV.co software developers
Test Flowgger with your log volume and format to confirm performance and feature fit. Review the GitHub wiki and open issues for integration details. Contact Devco for guidance on architecture and production deployment.
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flowgger FAQ
Can Flowgger replace Logstash or Fluentd?
What are the performance characteristics compared to Logstash?
Is this suitable for production?
How do I handle custom log formats?
From evaluation to production software
DEV.co pairs senior engineers with teams adopting tools like flowgger. Our software development services span open-source observability architecture, implementation, and the AI development services that increasingly sit alongside them.
Ready to evaluate Flowgger for your logging pipeline?
Test Flowgger with your log volume and format to confirm performance and feature fit. Review the GitHub wiki and open issues for integration details. Contact Devco for guidance on architecture and production deployment.