Advanced

  • Data Product Contract Template

    This template helps Data Platform Engineer teams define contracts for schema, quality, lineage, and ownership using Schema, quality, lineage, ownership in Google Cloud environments. It emphasizes separate ingestion reliability from consumption semantics and provides implementation decisions that can be reviewed without relying on vendor or customer claims.

  • Landing Zone Guardrail Definition Template

    This template helps Cloud Governance Lead teams treat account structure, identity, network, logging, and policy as a product using Control objective, policy, test, exception in AWS environments. It emphasizes version guardrails and exception paths and provides implementation decisions that can be reviewed without relying on vendor or customer claims.

  • Recovery Exercise Evidence Collector

    This tool helps Resilience Engineer teams design recovery around business services, dependencies, and tested objectives using Recovery runbook and evidence log in Hybrid Cloud environments. It emphasizes protect backup identity and immutability boundaries and provides implementation decisions that can be reviewed without relying on vendor or customer claims.

  • Kubernetes Platform Readiness Evaluator

    This tool helps Platform Engineering Lead teams build self-service capabilities around paved paths and clear contracts using Cluster, delivery, security, and operations review in Kubernetes environments. It emphasizes treat platform APIs and documentation as products and provides implementation decisions that can be reviewed without relying on vendor or customer claims.

  • Illustrative Case Study: Standardizing Kubernetes Delivery in Manufacturing

    This illustrative case study helps Platform Engineering Lead teams build self-service capabilities around paved paths and clear contracts using OpenShift GitOps and policy automation in OpenShift environments. It emphasizes treat platform APIs and documentation as products and provides implementation decisions that can be reviewed without relying on vendor or customer claims.

  • Illustrative Case Study: Establishing a Healthcare Data Landing Zone

    This illustrative case study helps Cloud Governance Lead teams treat account structure, identity, network, logging, and policy as a product using Policy, private connectivity, data controls in Microsoft Azure environments. It emphasizes version guardrails and exception paths and provides implementation decisions that can be reviewed without relying on vendor or customer claims.

  • Illustrative Case Study: Modernizing a Regional Payments Platform

    This illustrative case study helps Enterprise Architect teams align decomposition with product ownership and operational boundaries using Containers, managed database, event integration in AWS environments. It emphasizes modernize delivery and observability with runtime architecture and provides implementation decisions that can be reviewed without relying on vendor or customer claims.

  • Data Platform Operating Models That Scale

    This ebook helps Data and Analytics Leader teams offer governed data capabilities through repeatable platform interfaces using Data products, platform services, governance in Google Cloud environments. It emphasizes design isolation, lineage, and lifecycle policies into the platform and provides implementation decisions that can be reviewed without relying on vendor or customer claims.

  • Building Governed GenAI Systems

    This ebook helps AI Architect teams choose model and orchestration patterns from task risk and evidence needs using Model gateways, RAG, evaluation, guardrails in Private Cloud environments. It emphasizes protect prompts, context, tools, and outputs as data flows and provides implementation decisions that can be reviewed without relying on vendor or customer claims.

  • Platform Engineering Patterns for Kubernetes Teams

    This ebook helps Platform Engineering Lead teams build self-service capabilities around paved paths and clear contracts using Golden paths, GitOps, policy, observability in Kubernetes environments. It emphasizes treat platform APIs and documentation as products and provides implementation decisions that can be reviewed without relying on vendor or customer claims.