Premature Microservices Are the New Technical Debt
InfoQ 2025: premature microservices are now a top scaling bottleneck. Common failure at ~1,000 concurrent users. The architecture trap.
Dennis Vorobyov 7 min read backend
Python Development Company
Senior Python developers from EltexSoft. Django, FastAPI, data pipelines, AI/ML backends. Nautical Commerce ($30M), Boeing via Authentise. $50-99/hr.
EltexSoft is a Python development company with senior backend engineers available at $50-99/hr. We build Django web applications, FastAPI microservices, data pipelines, and AI/ML backends. Python clients include Nautical Commerce ($30M Series A, Django + React marketplace platform, acquired by Traide) and Boeing (via Authentise, manufacturing optimization with 80% processing time reduction).
What we ship
The Work
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Django Web Applications
Full-stack Django platforms with REST APIs, admin interfaces, background task processing, and PostgreSQL. Built Nautical Commerce's marketplace PaaS: Django backend, React frontend, 200K+ monthly transactions.
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FastAPI Microservices
High-performance async APIs for real-time workloads, webhook processing, and integration layers. Type-safe with Pydantic validation. When Django is too much framework and Flask is not enough structure.
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Data Pipelines and ETL
Data extraction, transformation, and loading with Python. Pandas, SQLAlchemy, Apache Airflow, Celery. Scheduled jobs, batch processing, and real-time event streams. The infrastructure behind dashboards and analytics.
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AI and ML Backends
Python backends for LLM integration, RAG pipelines, classification models, and prediction services. OpenAI, Anthropic, and open-source models deployed on AWS/GCP with proper API design and monitoring.
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API Development
RESTful and GraphQL APIs with Django REST Framework, FastAPI, or Flask. Versioning, authentication (OAuth 2.0, JWT), rate limiting, documentation (OpenAPI/Swagger). APIs that other teams can actually use.
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Legacy Python Migration
Python 2 to 3 migration. Flask to Django or FastAPI migration. Monolith to microservices decomposition. Untangling spaghetti codebases into maintainable, tested, documented systems.
Python Developers Who Built a $30M Marketplace Platform
Nautical Commerce raised $30M from Drive Capital. The entire backend is Python and Django. EltexSoft had 7 engineers on the project for multiple years: three backend developers writing Django, three full-stack frontend developers on React, and one QA engineer. The platform processes 200K+ monthly transactions. It was later acquired by Traide.
That is what our Python developers build. Not tutorials. Not prototypes. Production systems that process real transactions, handle real money, and pass technical due diligence from acquirers.
EltexSoft is a Python development company. 35-50 senior engineers. Headquartered in Los Angeles, with offices in New York, Lisbon, and Kyiv. Engineering team in Ukraine. Founded in 2015. When you hire Python developers from us, you get engineers who have shipped Django and FastAPI systems at scale.
What We Build With Python
Django Web Applications
Django is our primary Python framework for full-stack web applications. ORM, admin interface, authentication, background tasks with Celery, REST APIs with Django REST Framework, and PostgreSQL. Django’s “batteries included” philosophy means less integration work and faster delivery.
Nautical Commerce’s marketplace PaaS runs on Django. The platform enables ecommerce companies to launch multi-vendor marketplaces with vendor management, product catalog normalization, order routing, commission engines, multi-currency support, and multi-language translations. All Django. All Python.
We also have a dedicated Django page with deeper technical detail on our Django work specifically.
FastAPI Microservices
FastAPI for high-performance async APIs. Type safety with Pydantic. Auto-generated OpenAPI documentation. Async database drivers (asyncpg, motor) for non-blocking I/O. We use FastAPI when the workload is API-first: webhook processing, integration layers between services, ML model serving, and real-time event handling.
Data Pipelines and ETL
Python dominates data engineering because the ecosystem is unmatched. Pandas for data manipulation. SQLAlchemy for database abstraction. Apache Airflow or Prefect for orchestration. Celery for distributed task processing.
We build pipelines that extract data from APIs, databases, and file systems, transform it into analytics-ready formats, and load it into data warehouses or reporting dashboards. Scheduled batch processing and real-time event streams.
AI and ML Backends
Python is the default language for AI/ML. We build LLM integration layers with OpenAI and Anthropic APIs, RAG pipelines with vector databases (Pinecone, Weaviate, pgvector), classification and prediction services, and NLP processing pipelines. All deployed on AWS or GCP with proper API design, monitoring, rate limiting, and cost controls.
Our AI work runs on HIPAA-eligible infrastructure for healthcare clients. We never deploy ML models as Jupyter notebooks in production. They get proper APIs, error handling, logging, and deployment pipelines.
Manufacturing and Industrial
Boeing (via Authentise) used Python for manufacturing process optimization. The results: 80% reduction in processing time, 95% improvement in build preparation, 3x ROI within 8 months. Industrial Python is a different discipline from web Python: data ingestion from hardware, real-time processing, and integration with manufacturing execution systems.
The Python Stack We Use
Frameworks: Django 5.x, FastAPI, Flask (for lightweight services). ORM/DB: Django ORM, SQLAlchemy, asyncpg. PostgreSQL (default), MySQL, MongoDB, Redis. Task queues: Celery, Redis Queue, Dramatiq. Data: Pandas, NumPy, Apache Airflow, Prefect. AI/ML: LangChain, OpenAI API, Anthropic API, Hugging Face, scikit-learn, PyTorch. API: Django REST Framework, FastAPI with Pydantic, GraphQL (Strawberry). Testing: pytest (default), coverage, factory_boy, hypothesis. DevOps: Docker, GitHub Actions, Terraform, AWS/GCP.
What It Costs
Senior Python developer (dedicated): $50-99/hr. A full-time dedicated developer costs $8,000-$16,000/month.
By project type:
Django web application MVP: $30K-$80K, 3-5 months.
FastAPI microservice: $10K-$30K, 1-3 months.
Data pipeline/ETL system: $20K-$60K, 2-4 months.
AI/ML backend integration: $20K-$60K, 2-4 months.
Full marketplace backend (Django): $80K-$200K, 6-12 months.
Compare to US Python agencies at $100-$250/hr. Our $50-99/hr rate with senior-only engineers delivers 40-60% lower total cost.
Who We Are
EltexSoft is a boutique Python development company. 35-50 senior engineers. Headquartered in Los Angeles, with offices in New York, Lisbon, and Kyiv. Engineering team in Ukraine. Founded in 2015.
Python clients include Nautical Commerce ($30M Series A, acquired by Traide) and Boeing (via Authentise). We also build with Django, Laravel, React, Vue, iOS, and Android.
5.0 Clutch rating across 30+ verified reviews. 200+ five-star Upwork reviews. Top Rated Plus and Expert-Vetted agency status (top 1%). Average client engagement: 3+ years.
30-minute technical call. Bring your Django migration, your API architecture question, or your ML backend requirements. We’ll tell you what we’d build and what we wouldn’t.
Field notes
What we've written about this
Dennis Vorobyov 7 min read FAQ
Common questions
How do I hire Python developers from EltexSoft?
Contact us with your project requirements. We assign senior Python developers from our team. Introductions in 1 week, start in 2-3 weeks. $50-99/hr on monthly retainer. Our Python engineers have 5+ years of production experience and work in European timezones with 5+ hours of US overlap.
Django or FastAPI?
Django when you need a full-stack framework with ORM, admin, authentication, and template rendering built in. Nautical Commerce runs on Django. FastAPI when you need high-performance async APIs, microservices, or ML model serving. We use both and recommend based on the project, not on preference.
How much do Python developers cost?
EltexSoft charges $50-99/hr for senior Python developers on monthly retainer. A full-time dedicated Python developer costs $8,000-$16,000/month. Compare to US Python developers at $150-$250/hr. Our engineers are senior, English-fluent, and experienced with production systems processing hundreds of thousands of transactions.
Do you build AI and machine learning backends?
Yes. Python is our default language for AI/ML workloads. We build LLM integration layers (OpenAI, Anthropic, open-source), RAG pipelines with vector databases (Pinecone, Weaviate, pgvector), classification and prediction services, and data processing pipelines. All deployed on proper infrastructure with monitoring, not Jupyter notebooks in production.
Can you work with our existing Python codebase?
Yes. We regularly inherit Python codebases from prior teams. We audit the architecture, identify technical debt, improve test coverage, and either refactor incrementally or recommend a structured migration. Python 2 to 3 migration is a specialty.
What databases do you use with Python?
PostgreSQL is our default. MySQL when the project requires it. MongoDB for document-oriented workloads. Redis for caching and queuing. Elasticsearch for search. We use Django ORM, SQLAlchemy, or async drivers (asyncpg) depending on the framework.
Do you handle DevOps for Python applications?
Yes. Docker containerization, CI/CD pipelines (GitHub Actions), cloud deployment (AWS, GCP), monitoring (Datadog, Sentry), and infrastructure as code (Terraform). Our Python developers deploy their own code and monitor their own systems.
How long does a Python project take?
A Django web application MVP takes 3-5 months. A FastAPI microservice takes 1-3 months. A data pipeline or ETL system takes 2-4 months. An AI/ML backend integration takes 2-4 months. A full marketplace backend (like Nautical Commerce) takes 6-12 months.
What industries do your Python developers work in?
eCommerce and marketplaces (Nautical Commerce), manufacturing (Boeing via Authentise), FinTech, HealthTech, and AI engineering. Python is our go-to for any backend that involves data processing, API services, or machine learning.
Who owns the code?
You do. Full work-for-hire assignment. Source code, infrastructure configurations, test suites, and documentation belong to you from day one.
Tell us what you're building.
One business day reply. From an engineer, not a sales rep.