Become a DevOps Engineer for Microsoft Azure
At 5-10 hours/week
Get access to the classroom immediately on enrollment
In Collaboration With
Intermediate Python, familiarity with Linux shell scripting and cloud concepts.
In modern deployments, automated deployment and management of cloud infrastructure is crucial for ensuring the high uptimes that customers expect. Understand the DevOps lifecycle and the basics of infrastructure management in Microsoft Azure. Learn about cloud security best practices to keep infrastructure secure. Leverage modern technologies to create robust and repeatable deployments in Microsoft Azure.
Automated Deployment of high quality software using DevOps principles is a critical skill in the cloud era. Master the theory and practice of Agile project management with hands-on examples. Execute a Python centric Continuous Integration strategy that uses testing best practices, including open source code quality tools such as pylint and pytest. Couple Infrastructure-as-Code (IaC) with Continuous Delivery using Azure Pipelines to streamline the deployment of applications to Azure.
Applications that have been built and released into the cloud need to be evaluated to ensure proper performance. Test cloud-based application performance and functionality within the pipeline itself, as well as after it has been deployed by using different types of test suites such as Selenium and Postman. Exercise those test suites against a variety of endpoints, including a sample eCommerce UI, and REST APIs. Build a systemic application monitoring process based on alert triggers in Azure Monitor and custom log files in Azure Log Analytics.
Founder of Pragmatic AI Labs
Noah Gift teaches and consults at top universities and companies globally, including Duke and Northwestern. His areas of expertise are Machine Learning, MLOps, A.I., Data Science, and Cloud Architecture. Noah has authored several bestselling books, including Python for DevOps.
Principal AI Researcher | Rapid7
Erick Galinkin is a hacker and scientist specializing in Applying Artificial Intelligence to Cybersecurity problems and the Theory of Machine Learning. He is also a researcher at the Montreal AI Ethics Institute focusing on applying DevOps principles to the security and ethics of machine learning systems.
DevOps Engineer, Goodyear Tire & Rubber Company
Nathan has worked on implementing DevOps solutions for the past 8 years across the financial, educational, logistics, and manufacturing industries.
Start learning today! Switch to the monthly price afterwards if more time is needed.
Start learning today! Get maximum flexibility to learn at your own pace.