Technologies
Azure + Python Development
Data apps, ML services, and APIs powered by Python on Azure.
We deliver Python solutions on Azure — FastAPI and Django APIs, batch and streaming data jobs, Azure ML training pipelines, and Functions for lightweight inference — with reproducible environments and MLOps where models matter.
Plan Python on AzureWhy Python on Azure
Azure ML, Databricks, and Functions give Python teams managed compute for training and serving without building GPU farms from scratch.
ML-Native Platform
Azure ML, Foundry, and Cognitive Services integrate with Python SDKs your data scientists already use.
Data Ecosystem
Synapse, Data Factory, and Event Hubs connect Python ETL and analytics to enterprise data lakes.
Rapid API Delivery
FastAPI on Container Apps ships typed APIs with OpenAPI and async I/O for data-heavy endpoints.
Reproducible Environments
Conda, pip, and container images pinned in ACR for consistent train and infer cycles.
Python Reference Architecture on Azure
How we structure Python APIs, batch jobs, and ML workloads across Azure services.
Serving
FastAPI / Django
HTTP APIs with auth, validation, and async database access on Container Apps or App Service.
Azure Functions
Lightweight scoring endpoints and scheduled jobs triggered by queues or timers.
ML & Analytics
Azure ML
Training pipelines, model registry, and managed online endpoints for inference.
Batch / Spark Jobs
Scheduled feature engineering on Synapse, Databricks, or Container Apps jobs.
Data
Data Lake / Blob
Raw and curated datasets with lifecycle tiers and access policies.
Azure SQL / Cosmos
Operational stores for application state and feature serving.
What We Build with Python on Azure
Python deliverables spanning APIs, automation, and machine learning on Azure.
FastAPI Microservices
High-performance APIs with Pydantic models, OAuth, and background task queues.
ML Inference Services
Managed endpoints and batch scoring with monitoring for drift and latency.
Data Pipelines
ETL and feature pipelines orchestrated with Data Factory or Azure ML jobs.
AI-Assisted Workflows
RAG and agent patterns using Azure OpenAI with Python orchestration layers.
Automation & Scripting
Operational scripts packaged as Functions or Container Apps jobs with audit logging.
Azure Services in the Python Stack
Azure services we connect to Python applications, pipelines, and models.
Azure Service
Role in stack
- Azure Machine Learning
Training, registry, deployment, and MLOps for Python model lifecycles.
- Azure Functions (Python)
Event-driven handlers and lightweight inference without always-on VMs.
- Azure Container Apps
Hosts FastAPI/Django containers with KEDA scale rules on queue depth.
- Azure Data Factory
Orchestrates Python notebooks and scripts across data movement stages.
- Azure OpenAI
LLM and embedding APIs consumed by Python RAG and agent services.
- Application Insights
Traces Python requests, dependencies, and custom ML metrics in production.
How We Deliver Python on Azure
Practices for reliable data apps and ML systems your team can extend.
- 1
Environment Lockfiles
requirements.txt or poetry.lock with container builds in CI for identical prod images.
- 2
MLOps When Models Ship
Versioned datasets, experiment tracking, and approval gates before endpoint promotion.
- 3
Secure Data Access
Managed identity to storage and SQL; no shared keys in notebooks or repos.
- 4
Performance Profiling
Async I/O, connection pooling, and caching for APIs serving analytics workloads.
- 5
Knowledge Transfer
Jupyter-to-production playbooks and runbooks for retraining and rollback.
Python on Azure Questions
- FastAPI suits APIs and microservices with async and OpenAPI-first design. Django fits admin-heavy apps, ORM-centric domains, and teams already standardized on it.
Accelerate Python on Azure
Whether you need APIs, pipelines, or ML in production — share your goals and we map the architecture.
Explore More Technologies