--- title: "moby vs heron" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/moby-moby-vs-netis-heron" tools: ["moby-moby", "netis-heron"] --- # moby vs heron *GraphCanon updated Jul 15, 2026* ## Verdict Pick moby when moby is primarily Go; heron is Rust; pick heron when heron is primarily Rust; moby is Go. [moby](https://mobyproject.org/) reports 72k GitHub stars, 19k forks, and 3.8k open issues, last pushed Jul 10, 2026. [heron](https://heron-ai.pages.dev) has 67 stars, 8 forks, and 2 open issues, last pushed Jun 23, 2026. Figures are from public GitHub metadata via [moby's repository](https://github.com/moby/moby) and [heron's repository](https://github.com/Netis/heron). | | [moby](/tools/moby-moby.md) | [heron](/tools/netis-heron.md) | | --- | --- | --- | | Tagline | The Moby Project - a collaborative project for the container ecosystem to assemble container-based systems | Agent and LLM API performance monitoring via network packet probe. Measures performance of OpenClaw, Claude, Codex, DeepAgents and more, deployed on the provider side, no SDK changes required. | | Stars | 71,899 | 67 | | Forks | 19,126 | 8 | | Open issues | 3,821 | 2 | | Language | Go | Rust | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Developer Tools, Inference & Serving, LLM Frameworks | AI Agents, Inference & Serving, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [moby](/tools/moby-moby.md) | [heron](/tools/netis-heron.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 1d | 22d | | Open issues (now) | 3.8k | 2 | | Full report | [trust report](/tools/moby-moby/trust.md) | [trust report](/tools/netis-heron/trust.md) | ## Choose when ### Choose moby if… - moby is primarily Go; heron is Rust. - Tags unique to moby: containers, docker, go, golang. - Also covers Developer Tools. - moby ships Docker support for self-hosted deployment. ### Choose heron if… - heron is primarily Rust; moby is Go. - Tags unique to heron: agentic-ai, ai-agent-development, ai-observability, libpcap. - Also covers AI Agents. ## When NOT to use moby - Developer Tools: A gateway is overkill when you're pinned to a single provider and model. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## When NOT to use heron - AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ## Common questions ### What is the difference between moby and heron? moby: The Moby Project - a collaborative project for the container ecosystem to assemble container-based systems. heron: Agent and LLM API performance monitoring via network packet probe. Measures performance of OpenClaw, Claude, Codex, DeepAgents and more, deployed on the provider side, no SDK changes required.. See the comparison table for live GitHub stats and shared categories. ### When should I choose moby over heron? Choose moby over heron when moby is primarily Go; heron is Rust; Tags unique to moby: containers, docker, go, golang; Also covers Developer Tools; moby ships Docker support for self-hosted deployment. ### When should I choose heron over moby? Choose heron over moby when heron is primarily Rust; moby is Go; Tags unique to heron: agentic-ai, ai-agent-development, ai-observability, libpcap; Also covers AI Agents. ### When should I avoid moby? Developer Tools: A gateway is overkill when you're pinned to a single provider and model. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### When should I avoid heron? AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. ### Is moby or heron more popular on GitHub? moby has more GitHub stars (71,899 vs 67). Stars measure visibility, not whether either tool fits your constraints. ### Are moby and heron open source? Yes - both are open-source projects on GitHub (moby: Apache-2.0, heron: Apache-2.0). ### Where can I find alternatives to moby or heron? GraphCanon lists graph-backed alternatives at [moby alternatives](/tools/moby-moby/alternatives) and [heron alternatives](/tools/netis-heron/alternatives) ([moby markdown twin](/tools/moby-moby/alternatives.md), [heron markdown twin](/tools/netis-heron/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/moby-moby-vs-netis-heron.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, moby or heron? moby: Very active. heron: Active. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for moby and heron? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [moby trust report](/tools/moby-moby/trust); [heron trust report](/tools/netis-heron/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=moby-moby`](/api/graphcanon/graph?tool=moby-moby) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_