sustain fast flow of work by implementing continuous delivery i. Create the foundation of our deployment pipeline ii. Enabling fast & reliable automated testing iii. Enabling & practicing continuous Integrating objectives of QA & Operations to improve outcomes 2. Ch. 9 – Create the Foundations of Our Deployment Pipeline a. Enterprise Data Warehouse program by Em Campbell-Pretty - $200M, All streams of work INCLUDE RUNNNING IN PRODUCTION-LIKE ENVIRONMENTS i. In general, the longer the interval between deployment, the worse the outcome ii. Ensure Dev & QA routinely integrate with prod-like environments at

standards for libraries, infrastructure, and environments 2. Deployment tools 3. Testing standards and tools, including security 4. Deployment pipeline tools 5. Monitoring and analysis tools 6. Tutorials Integrate security with our deployment pipeline iv. Integrate security with our telemetry for better detection and recovery v. Protect our deployment pipeline vi. Integrate our deployment activities with our that are pre- approved and appropriately configured and secured. f. INTEGRATE SECURITY INTO OUR DEPLOYMENT PIPELINE i. Hardening the application after development completes is not acceptable. Left issues

..................................................................................... 48 14 Deployment/Sustainment .................................................................................. estimate.  Deployment – An Agile release deploys new capabilities every 6–12 months. The degree of change and level of complexity of each release may require further consideration of deployment costs. For certification/accreditation communities to design processes that support rapid development and deployment cycles. Ensuring early and active involvement of testers and certifiers in the planning stages

VALUE OF DEVOPS i. Code and change deployments (thirty times more frequent) ii. Code and change deployment lead time (two hundred times faster) iii. Production deployments (sixty times higher change success where an entire year’s worth of code that Development has worked on is released to production deployment. Like in manufacturing, this large batch release creates sudden, high levels of WIP and massive progress from deployment lead times measured in months or quarters to lead times measured in minutes, the constraint usually follows this progression: a. Environment creation: b. Code deployment: c. Test

TELEMETRY GAPS i. Expand metrics from business, application, infrastructure, client software, and deployment pipeline levels 1. With every production incident identify missing telemetry that could help TELEMETRY TO MAKE DEPLOYMENTS SAFER i. Actively monitor production telemetry whenever anyone performs deployment; focus on the metrics associated with the feature. ii. If negative results, ideally feature toggle Traditional change controls 1. Lead to long lead times and diminish effectiveness of feedback from the deployment process 2. Increase friction by adding more steps/approvals which tends to increase batch size

Conclusion 22 More resources 24 2 AI in the EnterpriseA new way 
 to work As an AI research and deployment company, OpenAI prioritizes partnering with global companies because our models will increasingly ChatGPT Enterprise and our API. And our Deployment Team takes these products into companies to address their most pressing use cases. We use iterative deployment to learn quickly from customer use cases vary by company and industry but the lessons apply across all markets. The common theme: AI deployment benefits from an open, experimental mindset, backed by rigorous evaluations, and safety guardrails

requirement to be delivered and deployed. Deployment speed: how fast a new version of the application can be deployed into the production environment. Deployment frequency: how often a new release can be actions.  Automate as much of the development and deployment activities as possible.  Adopt common tools from planning and requirements through deployment and operations.  Leverage agile software principles

Control our destiny  Started to engineer solutions for issues related to product configuration and deployment  Built a strong relationship with development (built empathy)  Development began to see operational innovation and optimization.  Environment homogenization and assimilation – no snowflakes  Deployment methodologies, automation, monitoring, and management tested continuously. Steve Barr steve.barr@csgi Scrum, Craig Larman  Continuous Delivery: Reliable Software Releases through Build, Test, and Deployment Automation, Jez Humble and David Farley  The Phoenix Project: A Novel About IT, DevOps, and

2025… …To reflect the urgency of this effort, Dr. Makary has directed all FDA centers to begin deployment immediately, with the goal of full integration by the end of June. - USA FDA Press Release, and how it reshapes institutions, labor, and decision-making will depend on the safeguards and deployment frameworks that accompany it. The productivity upside may be significant, but unevenly distributed Developer Use Cases = Broad & Varied Note: CI / CD pipelines are continuous integration / continuous deployment pipelines. Source: IBM, ‘AI in Software Development’ (2024); Anthropic; Katalon; AccelQ; Monday;