As cloud systems grow complex and data becomes vital to decisions, reliable deployments demand automated quality checks at every stage. This talk demonstrates how to embed infrastructure and data validations into your CI/CD workflows. While Azure DevOps is the example platform, the concepts and patterns apply equally to GitHub Actions, GitLab, and other tools.

By blending PowerShell-based infrastructure tests (via Pester) with data validations (via Great Expectations), you’ll learn how to structure tests, manage secrets, parameterise for multiple environments, and generate actionable outputs. The result is a resilient, transparent pipeline that fosters trust, continuous improvement, and shared ownership.

Talk Structure:
1. Setting the Stage: Why post-deployment testing matters and how it aligns with DevOps values.
2. Infrastructure Validation: Ensuring resource integrity and configurations with Pester.
3. Data Quality Checks: Validating assumptions and maintaining data integrity with Great Expectations.
4. Practical Integration: Step-by-step guidance for embedding these tests in Azure DevOps YAML pipelines.
5. Scaling & Culture: How automated checks reinforce a blameless culture, reliability, and team empowerment.

Relevance:
* DevOps Practitioners: Learn patterns to improve release quality.
* Culturally Minded Leaders: See how embedding checks fosters trust and shared ownership.
* Data Teams: Ensure data integrity for accurate analytics and ML workflows.

Format:
A mix of conceptual explanation, hands-on demonstration, and practical examples-no vendor pitches, just proven methods and open-source tools.