Description
Book SynopsisModern enterprises must address three concurrent challenges: rapid technological advancement, increasing regulatory requirements, and heightened customer expectations. In this context, the concept of cloud has evolved from a destination to an operating model. Pega Cloud 3 exemplifies this transformation. It provides a cloud-native execution environment, including pods for strict isolation, externalized stateful services for enhanced performance, Kubernetes for automated recovery and continuous delivery, and integrated low-code decisioning with governance. Pega Agentic AI on Cloud 3 synthesizes these components into a structured methodology, enabling agentic artificial intelligence (AI) that operates with evidence-based planning and defined safeguards. Key features of the book include:
- Priority is given to actionable decisions over extensive definitions. Where terminology could become ambiguous, a default is provided along with justification for any deviations, facilitating team progress.
- Evidence is treated as the primary deliverable. Automated pipelines are emphasized over static screenshots, and audits are structured as exportable data rather than informal searches.
- Rollbacks are occasionally necessary. Rollback procedures are designed, rehearsed, and standardized to maintain operational confidence.
The book is a practical guide focusing on actionable methodologies rather than theoretical concepts. Each architectural pattern supports incremental adoption, with all controls implemented programmatically, and every change is subject to audit and review. The book features a continuous case study, Northstar Enterprises, a diversified organization that adopted Cloud 3 to accelerate delivery, efficiently demonstrate compliance, and align scaling with measurable customer outcomes.
