ebhy/budgetml

Health v2 · maintenance only

Adoption not part of the score

1343 stars · 65 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

BudgetML is a Python library that deploys machine learning models as secured HTTPS API endpoints on cheap GCP preemptible instances in under 10 lines of code. It auto-generates a FastAPI server with Swagger docs, OAuth2 security, and LetsEncrypt SSL certificates while keeping costs minimal and uptime high.

Use cases

• deploy a machine learning model as a REST API cheaply
• serve model predictions on a low-budget cloud endpoint
• quickly put a trained model into production without DevOps knowledge
• host an inference API on a preemptible GCP instance
• get an HTTPS prediction endpoint with SSL in minutes
• avoid setting up Kubernetes for a single model deployment

When to choose

• you are a data scientist who wants a model endpoint fast without learning Docker, SSL, or backend servers
• cost is a primary concern and you can tolerate brief periodic downtime
• you need a simple single-model API rather than a full production MLOps setup
• you want automatic FastAPI server generation with interactive Swagger docs

When to avoid

• you need a fully production-grade, highly available serving infrastructure
• you are not deploying on Google Cloud Platform
• you need multi-model orchestration, autoscaling, or Kubernetes features
• you require active maintenance and long-term support, since the project is unmaintained

Facets

library · maturity maintenance

deployment api-framework http-server machine-learning llm-inference machine-learning cloud-computing apis data-science python cloud mlops fastapi model-serving inference-endpoint gcp preemptible-instances ssl low-cost-deployment docker linux

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