Operations Driven Python:
Basic Training

Operations Driven Python:
Basic Training

Streamline your Python projects with advanced operations techniques and optimize your development lifecycle.

With our expert-led DBT training program,
designed to equip you with cutting-edge skills in modern application deployment and management.
Benefit from our wealth of experience from countless customer projects:

Experience a balanced mix of theory, live demonstrations and practical exercises.

Master the integration of operations-driven development into the software lifecycle, from CI/CD pipelines to containerization.

Learn how to build robust Python interfaces like CLIs and APIs, while managing observability and log management efficiently.

Implement automated testing, deployment, and monitoring strategies to ensure operational excellence in your Python applications.

Operations Driven Python Training – upcoming dates

18.11. – 20.11.2024

Operations Driven Python in 3 Days

03.03. – 04.03.2024

Operations Driven Python in 2 Days

This course is designed for Python developers and DevOps engineers looking to enhance their operational skills. If you want to learn how to integrate operations-driven techniques like CI/CD pipelines, containerization, and log management into your Python projects, this course is perfect for you. Ideal for professionals who are building production-level applications and want to ensure operational efficiency and smooth deployments.

Practical Applications That We Will Cover in the Training:

  • 1
    Hands-on experience with interface creation, software packaging, application containerization, and CI/CD pipeline management.
  • 2
    Knowledge of implementing observability, log management, task scheduling, and operations automation using various tools.
  • 3
    Understanding of how to design operationally excellent Python applications that enhance efficiency and quality.

After The Course, You Will Be Able To:

  • 1
    Design, implement, and manage interfaces, CI/CD pipelines, and containerization strategies for Python applications.
  • 2
    Implement observability, log management, and task scheduling effectively using various tools.
  • 3
    Use cutting-edge tools for monitoring and optimizing Python applications in real-time.
  • 4
    Bridge the gap between development and operations by mastering operations-driven development techniques.

The Operations Driven Python training is perfect for you if…

  • You want to gain a comprehensive understanding of operations-driven development and its integration into the software lifecycle.
  • You want to learn best practices for creating interfaces like CLIs and APIs in Python, as well as techniques for packaging, containerizing, and orchestrating Python applications.
  • You want to understand how to implement robust CI/CD pipelines for automated testing and deployment, and tools and strategies for log management, task scheduling, and operations automation.

The Operations Driven Python training is not suitable for you if…

  • You are a beginner in programming and do not have basic Python knowledge.
  • You are looking for an introductory course on Python development or DevOps.
  • You prefer a focus on don’t plan to write production code that needs to operatable

Agenda

Training

For small companies and teams that are new to the topic.

  • The role of operability in software development lifecycle. Overview of the course objectives, structure, and expected outcomes
  • Understanding Development Lifecycles beyond Teams
  • The software development lifecycle (SDLC) from an operations perspective
  • Integrating development and operations for continuous improvement
  • The importance of SLAs and SOPs in team collaboration and service delivery
  • Creating, negotiating, and maintaining effective SLAs and SOPs

  • CLI & REPLs:
    • Building Command-Line Interfaces (CLI) for Python applications
    • Introduction to Python REPLs for interactive debugging and development
  • gRPC and RESTful APIs:
    • Designing efficient and scalable APIs
    • Implementing gRPC and RESTful APIs in Python

  • Best practices in structuring Python projects
  • Creating packages with setuptools, pip or poetry
  • Versioning and dependency management

  • Introduction to Docker and containerization fundamentals.
  • Containerizing a Python application.
  • Hosting applications via Docker Swarm

  • Setting up CI/CD pipelines using tools like Jenkins or GitHub Actions
  • Automating testing and deployment of Python applications
  • Best practices for managing environments and configurations
  • Deployment strategies: blue-green, canary, rolling updates
  • Protocols and practices to ensure smooth deployments

  • Using Airflow:
    • Basics of workflow orchestration with Airflow
    • Designing and deploying data pipelines
  • Exploring Rundeck:
    • Introduction to Rundeck for job scheduling and operations
    • Use cases and integration with Python applications

  • Best practices for logging in Python applications
  • Overview of log management systems: ELK, EFK, and Graylog
  • Setting up and configuring a log management solution

  • Introduction to observability and OpenTelemetry
  • Instrumenting Python code with OpenTelemetry for tracing, metrics, and logs

  • Introduction to Grafana and EFK for data visualization
  • Creating dashboards for real-time monitoring and analytics

Customized

For large companies and teams that want to master special challenges.

  • Ihr Ökosystem
  • Ihre Best Practices
  • Ihre Probleme und Themen

  • The role of operability in software development lifecycle. Overview of the course objectives, structure, and expected outcomes
  • Understanding Development Lifecycles beyond Teams
  • The software development lifecycle (SDLC) from an operations perspective
  • Integrating development and operations for continuous improvement
  • The importance of SLAs and SOPs in team collaboration and service delivery
  • Creating, negotiating, and maintaining effective SLAs and SOPs

  • CLI & REPLs:
    • Building Command-Line Interfaces (CLI) for Python applications
    • Introduction to Python REPLs for interactive debugging and development
  • gRPC and RESTful APIs:
    • Designing efficient and scalable APIs
    • Implementing gRPC and RESTful APIs in Python

  • Best practices in structuring Python projects
  • Creating packages with setuptools, pip or poetry
  • Versioning and dependency management

  • Introduction to Docker and containerization fundamentals.
  • Containerizing a Python application.
  • Hosting applications via Docker Swarm

  • Setting up CI/CD pipelines using tools like Jenkins or GitHub Actions
  • Automating testing and deployment of Python applications
  • Best practices for managing environments and configurations
  • Deployment strategies: blue-green, canary, rolling updates
  • Protocols and practices to ensure smooth deployments

  • Using Airflow:
    • Basics of workflow orchestration with Airflow
    • Designing and deploying data pipelines
  • Exploring Rundeck:
    • Introduction to Rundeck for job scheduling and operations
    • Use cases and integration with Python applications

  • Best practices for logging in Python applications
  • Overview of log management systems: ELK, EFK, and Graylog
  • Setting up and configuring a log management solution

  • Introduction to observability and OpenTelemetry
  • Instrumenting Python code with OpenTelemetry for tracing, metrics, and logs

  • Introduction to Grafana and EFK for data visualization
  • Creating dashboards for real-time monitoring and analytics

Hear from our satisfied training attendees

A1 Telekom Austria AG

Reinhard Burgmann
Head of Data Ecosystem

„UTA coached my team along the development process of the migration plan of our on premises data lake to the public cloud.

The outstanding level of expertise, both on a technical and organizational level, ensured a well-structured and realistic migration plan including timeline, milestones, and efforts.

The enablement of my team was at the center of a very smooth collaboration. Through UTA, we achieved our goal faster and reduced risks of the migration project significantly.

I highly recommend UTA’s services!“

Vattenfall

Bernard Benning
BA Heat

„I recently attended Vattenfall IT’s online Kafka training day hosted by Ultra Tendency, and it was an enriching experience.

The trainer, Ahmed, did a fantastic job explaining the theory behind Kafka, and the emphasis on practical application was great. The hands-on programming exercises were particularly helpful, and I’ve never experienced training with so many interactive examples!

Overall, I highly recommend this training to anyone who wants to improve their Kafka knowledge interactively and gain valuable skills.“

VP Bank

Eisele Peer
Lead Architect & Head of IT Integration & Development

“The MLOps training exceeded our expectations!

It offered a perfect blend of an overview, hands-on coding examples, and real-world use cases. The trainer answered all questions competently and adapted the content to fit our company’s infrastructure.

This training not only provided us with knowledge but also practical skills that we can apply immediately.“

Your investment

1949 €plus VAT.
  • Learn to create efficient command-line interfaces (CLIs), RESTful APIs, and scalable gRPC services for Python applications.
  • Gain hands-on experience with Docker containerization and orchestration, packaging Python software, and managing versions and dependencies.
  • Master the implementation of CI/CD pipelines using Jenkins or GitHub Actions, automating deployment and testing workflows for your Python projects.
  • Discover how to manage logs, observability, and task scheduling using tools like OpenTelemetry, Grafana, Airflow, and Rundeck to monitor and optimize your applications in real-time.
Book now
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Get to know your trainers

Marvin Taschenberger

Professional Software Architect, Ultra Tendency

Hudhaifa Ahmed

Senior Lead Big Data Developer Berlin Territory Manager, Ultra Tendency

Matthias Baumann

Chief Technology Officer & Principal Big Data Solutions Architect Lead, Ultra Tendency

Required hardware & infrastructure for your Docker Training

  • You will need a PC or Mac with a web browser and MS Teams.
  • During the training, we will provide you with a virtual machine with the required local dependencies, services and root access.
  • This VM has a running Kubernetes cluster on which you can test and execute the training instructions.
  • You can access the machine via a browser or SSH if you wish and the network restrictions allow it.