--- title: "agentops vs agent-kernel" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/agentops-ai-agentops-vs-yaalalabs-agent-kernel" tools: ["agentops-ai-agentops", "yaalalabs-agent-kernel"] --- # agentops vs agent-kernel *GraphCanon updated Sep 20, 2026* ## Verdict Pick agentops if agentOps is an open-source Python toolkit for monitoring AI agents and tracking costs associated with Large Language Model usage; pick agent-kernel if agent-kernel provides an operating system for scalable enterprise AI agents, supporting deployment and orchestration at scale with native integration support for MCP and A2A. [agentops](https://agentops.ai) reports 5.8k GitHub stars, 625 forks, and 184 open issues, last pushed Jun 25, 2026. [agent-kernel](https://kernel.yaala.ai/) has 188 stars, 86 forks, and 137 open issues, last pushed Sep 11, 2026. Figures are from public GitHub metadata via [agentops's repository](https://github.com/AgentOps-AI/agentops) and [agent-kernel's repository](https://github.com/yaalalabs/agent-kernel). | | [agentops](/tools/agentops-ai-agentops.md) | [agent-kernel](/tools/yaalalabs-agent-kernel.md) | | --- | --- | --- | | Tagline | Python SDK for AI agent monitoring and LLM cost tracking | The Operating System for Scalable Enterprise AI Agents | | Stars | 5,830 | 188 | | Forks | 625 | 86 | | Open issues | 184 | 137 | | Language | Python | Python | | Adopt for | AgentOps is an open-source Python toolkit for monitoring AI agents and tracking costs associated with Large Language Model usage. | Agent-kernel provides an operating system for scalable enterprise AI agents, supporting deployment and orchestration at scale with native integration support for MCP and A2A. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | AI Agents, Evaluation & Observability | AI Agents | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [agentops](/tools/agentops-ai-agentops.md) | [agent-kernel](/tools/yaalalabs-agent-kernel.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Very active (96%) | | Days since push | 86d | 1d | | Open issues (now) | 184 | 137 | | Stars delta | +59 (30d) | +75 (30d) | | Open issues delta | +8 (30d) | +9 (30d) | | Full report | [trust report](/tools/agentops-ai-agentops/trust.md) | [trust report](/tools/yaalalabs-agent-kernel/trust.md) | ## Shared compatibility - **Python**: [agentops](/tools/agentops-ai-agentops.md) - Python runtime; [agent-kernel](/tools/yaalalabs-agent-kernel.md) - Python runtime ## Decision facts: agentops - **Adopt for:** AgentOps is an open-source Python toolkit for monitoring AI agents and tracking costs associated with Large Language Model usage. ## Decision facts: agent-kernel - **Requirements:** It requires Python versions between 3.12 and 3.13.x.; Supports deployment to various environments such as AWS Lambda, ECS, Azure Functions, or Container Apps via one Terraform module. - **Adopt for:** Agent-kernel provides an operating system for scalable enterprise AI agents, supporting deployment and orchestration at scale with native integration support for MCP and A2A. ## Choose when ### Choose agentops if… - License: agentops is MIT, agent-kernel is Apache-2.0. - Tags unique to agentops: ai-agents, benchmarking, cost-tracking. - Also covers Evaluation & Observability. - Integrations are needed specifically with Langchain, CrewAI, or OpenAI Agents SDK ### Choose agent-kernel if… - License: agent-kernel is Apache-2.0, agentops is MIT. - Requirements: It requires Python versions between 3.12 and 3.13.x.; Supports deployment to various environments such as AWS Lambda, ECS, Azure Functions, or Container Apps via one Terraform module.. - Tags unique to agent-kernel: a2a, adk, aws, azure. - If you require seamless scalability across different cloud providers like AWS and Azure without lock-in or rewrites. ## When NOT to use agentops - If specific integration support is needed for frameworks not listed including Autogen AG2 CamelAI - In case self-hosting of components is impractical due to resource constraints ## When NOT to use agent-kernel - If your project is confined to a single, specific AI framework which doesn't require the flexibility Agent-kernel offers. - When you do not have Python version 3.12 - 3.13.x, as it's the required runtime environment. ## Common questions ### What is the difference between agentops and agent-kernel? agentops: Python SDK for AI agent monitoring and LLM cost tracking. agent-kernel: The Operating System for Scalable Enterprise AI Agents. See the comparison table for live GitHub stats and shared categories. ### When should I choose agentops over agent-kernel? Choose agentops over agent-kernel when License: agentops is MIT, agent-kernel is Apache-2.0; Tags unique to agentops: ai-agents, benchmarking, cost-tracking; Also covers Evaluation & Observability; Integrations are needed specifically with Langchain, CrewAI, or OpenAI Agents SDK. ### When should I choose agent-kernel over agentops? Choose agent-kernel over agentops when License: agent-kernel is Apache-2.0, agentops is MIT; Requirements: It requires Python versions between 3.12 and 3.13.x.; Supports deployment to various environments such as AWS Lambda, ECS, Azure Functions, or Container Apps via one Terraform module.; Tags unique to agent-kernel: a2a, adk, aws, azure; If you require seamless scalability across different cloud providers like AWS and Azure without lock-in or rewrites. ### When should I avoid agentops? If specific integration support is needed for frameworks not listed including Autogen AG2 CamelAI In case self-hosting of components is impractical due to resource constraints ### When should I avoid agent-kernel? If your project is confined to a single, specific AI framework which doesn't require the flexibility Agent-kernel offers. When you do not have Python version 3.12 - 3.13.x, as it's the required runtime environment. ### Is agentops or agent-kernel more popular on GitHub? agentops has more GitHub stars (5,830 vs 188). Stars measure visibility, not whether either tool fits your constraints. ### Are agentops and agent-kernel open source? Yes - both are open-source projects on GitHub (agentops: MIT, agent-kernel: Apache-2.0). ### Where can I find alternatives to agentops or agent-kernel? GraphCanon lists graph-backed alternatives at [agentops alternatives](/tools/agentops-ai-agentops/alternatives) and [agent-kernel alternatives](/tools/yaalalabs-agent-kernel/alternatives) ([agentops markdown twin](/tools/agentops-ai-agentops/alternatives.md), [agent-kernel markdown twin](/tools/yaalalabs-agent-kernel/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/agentops-ai-agentops-vs-yaalalabs-agent-kernel.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, agentops or agent-kernel? agentops: Steady. agent-kernel: Very 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 agentops and agent-kernel? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [agentops trust report](/tools/agentops-ai-agentops/trust); [agent-kernel trust report](/tools/yaalalabs-agent-kernel/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=agentops-ai-agentops`](/api/graphcanon/graph?tool=agentops-ai-agentops) - 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/_