Cloud Migration Planning Agent
Analyzes on-premises application portfolios and generates dependency-aware, sequenced migration plans for moving workloads to the cloud.
On-premises to cloud migrations frequently stall or run over budget because organizations underestimate the complexity of application interdependencies, discovering mid-migration that a workload they planned to move early actually depends on a dozen other systems still running on-premises
Manual application discovery and dependency mapping across hundreds of legacy systems is slow and error-prone, and migration wave planning based on incomplete dependency data leads to sequencing mistakes that cause outages or force costly rework
Cost estimation for cloud target environments is often wildly inaccurate when based on simple lift-and-shift assumptions rather than actual application resource utilization patterns
Without a data-driven plan, migration programs lose executive confidence when early waves run into unexpected blockers that proper upfront analysis would have caught
The agent discovers and maps the on-premises application portfolio, analyzing network traffic, configuration data, and resource utilization to build an accurate dependency graph between applications, databases, and infrastructure. It clusters interdependent applications into logical migration waves that minimize cross-wave dependencies, models right-sized cloud target configurations based on actual observed utilization rather than current provisioned capacity, and estimates cost and migration effort per wave. The agent continuously updates the plan as discovery reveals new dependencies or as early waves complete, keeping the migration roadmap grounded in current reality.
Application Discovery and Dependency Mapping
- Discover applications and infrastructure across the on-premises estate
- Analyze network traffic to map inter-application dependencies
- Incorporate configuration and database connection data
- Build a comprehensive, visualized dependency graph
Migration Wave Clustering
- Cluster tightly-coupled applications into shared migration waves
- Minimize cross-wave dependencies to reduce migration risk
- Sequence waves by business criticality and technical readiness
- Flag applications requiring re-architecture before migration
Cloud Target Sizing and Cost Modeling
- Analyze actual resource utilization rather than provisioned capacity
- Model right-sized cloud target configurations per workload
- Estimate migration cost and effort per wave
- Compare lift-and-shift versus re-platform cost tradeoffs
Continuous Plan Refinement
- Update the dependency graph as new information is discovered
- Incorporate lessons learned from completed migration waves
- Re-sequence remaining waves based on updated risk data
- Report migration progress and plan changes to stakeholders