In this study, cloud modernization means going beyond simply running workloads in the cloud and instead adopting a set of advanced services and architectures that change how you build, run, and operate technology. The research identifies six main modernization pathways: 1) Containers 2) Cloud Native applications 3) Managed Databases 4) Managed Analytics 5) Modern DevOps 6) Open Source platforms These pathways are evaluated using the Cloud Value Framework (CVF), which looks at four pillars of business performance: - Staff Productivity - Business Agility - Operational Resilience - Cost Savings Across 504 organizations surveyed (all with at least $250M in annual revenue, $500K in public cloud spend, and 500+ employees), the data shows that moving from basic cloud usage to these modern services helps organizations: - Work faster (e.g., up to 42% faster IT resource provisioning with Containers, 41% faster with Managed Databases) - Ship more frequently (e.g., 86% increase in weekly or faster feature deployments with Cloud Native) - Operate more reliably (e.g., 16–18% reductions in production failures and security incidents with Containers, Cloud Native, and Managed Databases) - Use resources more efficiently and reduce spend (e.g., 12–14% improvements in infrastructure and compute efficiency) Highly modernized organizations—those that adopt all six pathways—see broad improvements across all four CVF pillars, with staff productivity KPIs improving by up to 117% and business agility KPIs by up to 63%. In practical terms, cloud modernization matters because it helps you: - Free up teams from low‑value infrastructure work - Shorten the time from idea to production - Improve stability and security of applications - Optimize infrastructure and licensing costs It’s less about where your workloads run and more about reimagining how your teams build, deploy, and operate them.

Containers and cloud native services work together to streamline how you build, deploy, and operate applications. Containers Containers package application code, configuration, and dependencies into a portable unit that runs consistently across environments. Modern container services (like Amazon ECS or EKS) handle orchestration so teams can focus more on applications than infrastructure. From the study, organizations adopting containers report: - 42% reduction in time to provision IT resources - 27% increase in weekly (or faster) feature deployments - 29% reduction in lead time to commit code changes - 25% less time managing and coordinating multiple cloud environments - 18% faster time to insight from data - 14% increase in DevOps automation - 16% reduction in time to detect security incidents - 16% reduction in production failures for new features or services - 12% reduction in IT infrastructure spend - 11% improvement in compute utilization In practice, this means your teams can: - Spin up environments quickly and consistently - Move code from dev to test to production with fewer issues - Detect and respond to security and reliability problems faster - Use infrastructure more efficiently and reduce waste Cloud Native Cloud native approaches use managed, scalable services (e.g., AWS Lambda, ECS/EKS, API Gateway) and patterns like microservices, event‑driven design, and serverless computing. Organizations using cloud native services report: - 102% increase in number of databases managed per administrator - 86% increase in weekly (or faster) feature deployments - 31% increase in DevOps automation - 21% reduction in time spent coordinating across multiple environments - 11% increase in applications developed as cloud native - 18% reduction in security incidents - 14% improvement in compute utilization - 7% reduction in VMs reliant on proprietary licenses - 8% reduction in databases reliant on proprietary licenses Together, containers and cloud native services help you: - Deliver features more frequently with shorter lead times - Improve reliability through standardized packaging, automation, and self‑healing architectures - Simplify environment management and reduce coordination overhead - Strengthen security posture while optimizing infrastructure and licensing costs If your goal is to speed up delivery without sacrificing stability, these two pathways are central to rethinking your application and operations model.

Managed databases and managed analytics services are designed to offload operational work—such as setup, patching, backups, and scaling—so your teams can focus more on data use and application features rather than infrastructure. Managed Databases Services like Amazon Aurora and Amazon Redshift handle core database operations and scaling. Organizations using managed databases report: - 130% more databases managed per administrator - 41% faster IT resource provisioning - 25% faster time to insight from data - 11% reduction in lead time to commit code changes - 18% reduction in production failures for new features or services This translates into: - Higher DBA and engineering productivity: each administrator can manage significantly more databases. - Faster delivery: provisioning and code changes move more quickly, supporting shorter release cycles. - Better decision‑making: reduced time to insight means business teams get data faster. - Improved stability: fewer production failures tied to new releases. Managed Analytics Managed analytics services (for ETL, data lakes, BI, and reporting) are not detailed in the same depth in the excerpt, but the study notes that: - Managed analytics primarily drive cost savings, with KPIs improving by up to 15% in that pillar. In practice, organizations use managed analytics to: - Reduce the overhead of building and maintaining data pipelines and analytics platforms - Standardize and automate data processing - Provide more reliable, timely reporting to business stakeholders Combined Value When you pair managed databases with managed analytics, you: - Free technical staff from routine database and analytics platform maintenance - Shorten the path from raw data to actionable insight (25% faster time to insight with managed databases, plus up to 15% cost‑related improvements from managed analytics) - Improve resilience and reliability of data‑driven applications (18% fewer production failures) For organizations dealing with growing data volumes and complex workloads, these pathways help reimagine data operations—from infrastructure‑heavy to service‑driven—while improving both productivity and cost efficiency.