End-to-end migration of existing AI/ML workloads to PaletteAI. Three structured phases ensure nothing falls through the cracks -- from Cluster Profile design through cutover and optimization.
The Workload Migration service executes the end-to-end migration of assessed workloads onto PaletteAI. Migration always follows a completed Workload Assessment and is delivered in three structured phases. Each migration is custom-quoted based on the assessment findings.
Every migration includes a 30-day post-migration support trial so you're never left on your own during the critical stabilization period.
Phase 1: Cluster Profile Preparation & Packaging
Design Cluster Profiles per workload class. Package workloads by migration strategy (Rehost, Re-package, Re-platform, Re-architect). Prepare data and storage. Validate everything in non-production.
Phase 2: Migration Execution
10-step per-workload checklist: pre-migration snapshot, cluster profile deployment, namespace/RBAC setup, storage provisioning, workload deployment, GPU verification, network validation, monitoring integration, functional validation, performance baseline. Full rollback procedures for every workload type.
Phase 3: Post-Migration Optimization & Handover
GPU utilization optimization (right-sizing, MIG, time-slicing, Kueue). Observability and alerting setup. Operational runbooks. Team enablement sessions. 30-day post-migration support trial.
This service is for organizations that have completed a Workload Assessment and are ready to execute the migration. It's designed for teams that need expert hands to move production AI/ML workloads without disruption.
The migration team works closely with your platform engineers and data scientists throughout the engagement.
Every migration starts with an Assessment. Contact us to scope your project.
