Microservice Architecture in Python
This course introduces participants to the world of microservices, showing how to effectively transform monolithic applications into scalable, flexible solutions.
Ideal for teams that…
Solid backend and architecture — patterns proven in production.
How to migrate from monolith to microservices—from domain analysis through defining responsibilities and implementing microservices in Python
Containerization of applications—creating Docker images, working with containers, and tackling common issues in microservice applications
Orchestration with Kubernetes—environment setup, managing microservices, and practical implementation of GitOps
Managing monitoring, logging, and CI/CD—configuring tools like Prometheus and Grafana, and automating build, test, and deployment processes in a microservice context
What we actually do
- · Day 1: Introduction and Microservices Fundamentals Monolithic architecture and introduction to microservices Characteristics Benefits Limitations Review of common microservice architectures API Gateway CQRS Event Sourcing Domain-Driven Design Sidecar pattern Discussion of trade-offs and challenges Defining boundaries of responsibility Domain analysis Identifying components Workshop Splitting a monolith into microservices using a complex example Defining communication between services Microservice applications in Python Design patterns for Python microservices Overview of frameworks Ready-made application templates APIs Workers (multithreading) Event and log handling Environment configuration Virtual environments Database migrations
- · Day 2: Migration Process and Basics of Orchestration Migration process Automating tests Identifying deployment environments Splitting monolith Organizing repositories for CI/CD Deployment strategies GitOps Workshop Verifying migration by implementing core services in Python Validating boundary splits Running services locally Containerization Docker fundamentals Building secure, lightweight images Typical pitfalls Workshop on Dockerizing Python services Orchestration using Kubernetes Introduction to Kubernetes components (Pod, Deployment, Service) Managed Kubernetes services Workshop Deploying and managing microservices in Kubernetes Working with YAML configs Discussion of GitOps approach
- · Day 3: Monitoring, Logs, CI/CD and “12-Factor App” Principles Monitoring, tracing, logging, and alerting Tools: Prometheus, Grafana, Jaeger Workshop Setting up monitoring and alerts for microservices in Kubernetes Integrating logs and distributed tracing CI/CD process for microservices Fundamentals Simple CI/CD pipeline (build / test / deploy) Versioning services Handling multiple versions The 12-Factor App principles applied to microservices Overview of the twelve factors Workshop Evaluating existing services against the principles Adapting selected services to comply
From brief to retro in 30 days.
Brief & diagnosis
A call with the team lead + a short survey for participants. We define goals, gap and context.
Program customization
We adapt modules, case studies and code examples to your stack. Approval in 5 days.
Workshop
Trainer-led sessions, hands-on, code review. Mentor available between sessions too.
Retro + report
Outcome report for the team and lead. 30 days of consulting included.
Send a brief. We'll reply within 1 day.
After a short brief we'll prepare a program and a quote. No obligations — it's just a starting point.
Thank you!
We'll get back to you within 1 business day.
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