Awesome DevOps Freelance

- Documentation: https://adurrr.github.io/awesome-devops-freelance/docs/
- Get Started: https://adurrr.github.io/awesome-devops-freelance/docs/get-started/
- Freelance Devops Roadmap: https://adurrr.github.io/awesome-devops-freelance/docs/get-started/freelance-devops-roadmap/
- How to Use This List: https://adurrr.github.io/awesome-devops-freelance/docs/get-started/how-to-use-this-list/
- Paradigms: https://adurrr.github.io/awesome-devops-freelance/docs/paradigms/
- Landscape 2026: https://adurrr.github.io/awesome-devops-freelance/docs/paradigms/landscape/
- Aiops: https://adurrr.github.io/awesome-devops-freelance/docs/paradigms/landscape/aiops/
- Dataops: https://adurrr.github.io/awesome-devops-freelance/docs/paradigms/landscape/dataops/
- Devops: https://adurrr.github.io/awesome-devops-freelance/docs/paradigms/landscape/devops/
- Devsecops: https://adurrr.github.io/awesome-devops-freelance/docs/paradigms/landscape/devsecops/
- Finops: https://adurrr.github.io/awesome-devops-freelance/docs/paradigms/landscape/finops/
- Llmops: https://adurrr.github.io/awesome-devops-freelance/docs/paradigms/landscape/llmops/
- Mlops: https://adurrr.github.io/awesome-devops-freelance/docs/paradigms/landscape/mlops/
- Platform Engineering: https://adurrr.github.io/awesome-devops-freelance/docs/paradigms/landscape/platform-engineering/
- Sre: https://adurrr.github.io/awesome-devops-freelance/docs/paradigms/landscape/sre/
- Academic References: https://adurrr.github.io/awesome-devops-freelance/docs/paradigms/academic-references/
- Cncf Landscape Analysis: https://adurrr.github.io/awesome-devops-freelance/docs/paradigms/cncf-landscape-analysis/
- Paradigm Familiarization: https://adurrr.github.io/awesome-devops-freelance/docs/paradigms/paradigm-familiarization/
- Tools: https://adurrr.github.io/awesome-devops-freelance/docs/tools/
- Ai for Devops: https://adurrr.github.io/awesome-devops-freelance/docs/tools/ai-for-devops/
- Ci Cd Tools: https://adurrr.github.io/awesome-devops-freelance/docs/tools/ci-cd-tools/
- Container Orchestration: https://adurrr.github.io/awesome-devops-freelance/docs/tools/container-orchestration/
- Cost Management Finops: https://adurrr.github.io/awesome-devops-freelance/docs/tools/cost-management-finops/
- Gitops Tools: https://adurrr.github.io/awesome-devops-freelance/docs/tools/gitops-tools/
- Iaac Tools: https://adurrr.github.io/awesome-devops-freelance/docs/tools/iaac-tools/
- Messaging Streaming: https://adurrr.github.io/awesome-devops-freelance/docs/tools/messaging-streaming/
- Mlops Llmops Tools: https://adurrr.github.io/awesome-devops-freelance/docs/tools/mlops-llmops-tools/
- Observability Monitoring: https://adurrr.github.io/awesome-devops-freelance/docs/tools/observability-monitoring/
- Platform Engineering: https://adurrr.github.io/awesome-devops-freelance/docs/tools/platform-engineering/
- Security Devsecops: https://adurrr.github.io/awesome-devops-freelance/docs/tools/security-devsecops/
- Sre Tools: https://adurrr.github.io/awesome-devops-freelance/docs/tools/sre-tools/
- Careers: https://adurrr.github.io/awesome-devops-freelance/docs/careers/
- Freelancer Profile Analysis: https://adurrr.github.io/awesome-devops-freelance/docs/careers/freelancer-profile-analysis/
- Reference: https://adurrr.github.io/awesome-devops-freelance/docs/reference/
- How to Contribute: https://adurrr.github.io/awesome-devops-freelance/docs/reference/how-to-contribute/
- Methodology: https://adurrr.github.io/awesome-devops-freelance/docs/reference/methodology/
- Research Review Notes: https://adurrr.github.io/awesome-devops-freelance/docs/reference/research-review-notes/
- Architecture: https://adurrr.github.io/awesome-devops-freelance/docs/architecture/

# MLOps & LLMOps Tools → Extended List

> **Full comparison of MLOps and LLMOps tools for DevOps freelancers → covering the full AI lifecycle.**

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**Last updated**: 2026-05-26


| Tool | Stars | License | Best For |
|---|---|---|---|
| **MLflow** | 20k+ | Apache 2.0 | Experiment tracking + model registry + deployment |
| **Weights & Biases** | - | SaaS | ML experiment tracking & visualization |
| **DVC** | 15k+ | Apache 2.0 | Data + ML experiment version control |
| **Neptune.ai** | - | SaaS | Metadata store for MLOps |

## Pipeline Orchestration

| Tool | Stars | License/Status | Best For |
|---|---|---|---|
| **Kubeflow** | 14k+ | Apache 2.0 CNCF Incubating | ML pipelines on K8s |
| **Prefect** | 17k+ | Apache 2.0 | Python-native workflow orchestration |
| **ZenML** | 4k+ | Apache 2.0 | Portable MLOps pipelines |
| **Flyte** | 5k+ | Apache 2.0 CNCF Incubating | Data & ML orchestration |
| **Airflow** | 38k+ | Apache 2.0 | Data pipeline orchestration |

## Model Serving

| Tool | Stars | License/Status | Best For |
|---|---|---|---|
| **KServe** | 4k+ | Apache 2.0 CNCF Incubating | K8s-native model serving |
| **Seldon Core** | 4k+ | Apache 2.0 | ML deployment & monitoring |
| **BentoML** | 7k+ | Apache 2.0 | Unified model serving framework |
| **TensorFlow Serving** | 5k+ | Apache 2.0 | TF model serving |
| **TorchServe** | 4k+ | Apache 2.0 | PyTorch model serving |
| **vLLM** | 45k+ | Apache 2.0 | LLM inference optimization |

## LLMOps Tools

| Tool | License | Best For |
|---|---|---|
| **LangChain** | MIT | LLM application framework, RAG, agents |
| **LangSmith** | Commercial | LLM observability & tracing |
| **Guardrails AI** | Commercial | LLM input/output guardrails |
| **Weights & Biases Prompts** | Commercial | LLM prompt engineering |
| **LlamaIndex** | MIT | RAG framework |
| **Flowise** | Apache 2.0 | Visual LLM workflow builder |
| **MLflow AI Gateway** | Apache 2.0 | Unified LLM API gateway |

## Monitoring & Observability for ML

| Tool | Stars | License | Best For |
|---|---|---|---|
| **Evidently AI** | 5k+ | Apache 2.0 | ML model drift monitoring |
| **WhyLabs** | - | SaaS | ML observability |
| **Arize AI** | - | SaaS | ML monitoring & troubleshooting |
| **Grafana + ML plugins** | - | Open source | Custom ML dashboards |

## Feature Store

| Tool | Stars | License | Best For |
|---|---|---|---|
| **Feast** | 5k+ | Apache 2.0 | Open source feature store |
| **Tecton** | - | SaaS | Enterprise feature platform |

## Freelance MLOps/LLMOps Opportunities

| Service | Rate Range | Key Tools |
|---|---|---|
| MLOps pipeline setup | $120-200/hr | MLflow + Kubeflow + KServe |
| LLM RAG deployment | $150-250/hr | LangChain + vLLM + Guardrails |
| ML monitoring setup | $120-180/hr | Evidently AI + Grafana |
| LLMOps guardrails | $150-250/hr | Guardrails AI + LangSmith |
| ML infrastructure | $130-220/hr | K8s + KServe + Kubeflow |
| Feature store deployment | $120-200/hr | Feast + Tecton |

## Learning Resources

- [MLflow Docs](https://mlflow.org/docs/)
- [LangChain Academy](https://academy.langchain.com/)
- [KServe Docs](https://kserve.github.io/)
- [Kubeflow Docs](https://www.kubeflow.org/docs/)
- [Designing ML Systems (O'Reilly)](https://www.oreilly.com/library/view/designing-machine-learning/9781098107956/)

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*Last updated: 2026-05-26*