DevOps, DBSs, and DBaaS : Managing Data Platforms to Support Continuous Integ...

Learn how DBAs in a DevOps environment manage data platforms and change requests to support and optimize continuous integration, delivery, testing, and deployment in the application development life cycle.

On the Dev side, DBAs evaluate change requests to ensure compliance with organizational best practices and guard against degradation of database performance and the validity of dependent objects. On the Ops side, DBAs perform release and troubleshooting activities in support of the application, manage the data platform’s access and security, and monitor and maintain performance of the databases that they have designed and provisioned.

DevOps, DBAs, and DBaaS investigates the complex intersection between DBA functions and DevOps processes. DevOps teams traditionally viewed DBAs as process outliers who disrupt and retard SDLC timelines. At each touch point, veteran DBA Mike Cuppett shows how DBAs can most effectively contribute to decreasing release cycle times and improving product resiliency by applying automation, orchestration, and DBaaS solutions to database administration in ways that dovetail with DevOps requirements and metrics.

At a high level, Cuppett demonstrates the importance of leveling silo walls in the IT supply chain and of measuring application performance holistically by reference to satisfaction of customer requirements and end-user experience. At a technical level, he drills into topics and case studies on diagnosing and resolving problems commonly encountered by DBAs and DevOps teams when meshing database management with application delivery.

• Understand techniques and best practices at all points of collaboration between DBAs and DevOps teams in product development
  
• Use tools for measuring DBA inputs to DevOps processes by using the holistic criteria of end-user experience and business requirement
  
• Integrate open source database technologies with DevOps
  
• Know when to decouple application and database layers and move to DBaaS models
  
• Overcome language and mindset barriers between DBAs and DevOps teams