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Episode

The Database Calls Are Coming From Inside the House With Grant Fritchey

Podcast
Arrested DevOps
Published
Oct 26, 2023
Duration seconds
2539
Processing state
processed
Canonical source
https://www.arresteddevops.com/database-calls-inside-the-house/
Audio
https://media.blubrry.com/arresteddevops/content.blubrry.com/arresteddevops/arrested-devops-podcast-episode195.mp3
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Markdown
/podcast/arrested-devops/the-database-calls-are-coming-from-inside-the-house-with-grant-fritchey.md

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Summary

The core thesis is that databases should be treated as code to enable modern automation and continuous delivery. By adopting a 'database as code' mentality, teams can overcome the persistent gap between application development and data management.

Topics

  • Database DevOps
  • Automation
  • Database as Code
  • Data Management
  • Continuous Delivery
  • Infrastructure as Code
  • Database Administration
  • Cloud Native Architecture

Highlights

  • Main idea: Databases are essentially large, complex pieces of code that require the same automated lifecycle as application code
  • Practical takeaway: Use automation to manage persistence, high availability, and multi-platform deployments to reduce manual toil
  • Failure mode: Treating data management as a separate, manual silo prevents teams from achieving true continuous delivery
  • Main idea: The role of the Database Administrator is evolving into Database DevOps Engineer (DVA) as automation increases
  • Practical takeaway: Focus on the 'how' and 'why' of data management to bridge the gap between infrastructure and development teams

Chapters

  1. 4:05 The Shift to Database DevOps: Grant discusses his recent focus on database automation and the growing importance of database DevOps.
  2. 7:00 The Gap in Data Management: An exploration of why many organizations still fail to apply DevOps principles to their data layers.
  3. 10:35 The Evolution of the DBA: Discussing the transition from traditional Database Administrators to automated data management roles.
  4. 13:30 Applying Orchestration to Data: How modern technologies like Kubernetes and containerization change how we reason about database infrastructure.
  5. 16:45 The Power of Automation: Addressing the fear that databases are too complex to automate and why that misconception is dangerous.
  6. 19:45 Databases as Code: The fundamental shift: treating database schemas, migrations, and configurations as versioned code.
  7. 29:25 Legacy Data Structures: Reflecting on how modern systems still rely on foundational data models from decades ago.
  8. 35:25 The Future of Data and AI: Looking ahead at the impact of AI on production environments and the future of the industry.