Assess

Upgrading core mainframes or orchestrating multi-cloud container deployments without an accurate inventory of system behaviors leads to fragile application integrations, broken deployment tracks, and massive cloud resource waste. The Survey phase is our deep-dive engineering audit and telemetry collection period. Before modifying a single application server or deploying an AI model, our team profiles your active workloads, catalogs existing data layouts, and maps system dependencies to build a risk-assessed technological roadmap.

• Application & Workload Profiling: We analyze computing resource draw, thread utilization, and application performance metrics across on-premise mainframes, virtual environments, and cloud nodes.
• Dependency & Core Interconnection Mapping: We map data-flow perimeters and connectivity linkages between legacy systems (like COBOL programs running on z/OS) and external consumer-facing applications.
• Data Schema & Asset Ingestion Cataloging: We audit distributed data models across Db2 warehouses, relational servers, and object storage tiers to classify record structures and pinpoint data debt.
• Vulnerability & Compliance Baseling: We run automated non-intrusive scans to flag unencrypted network protocols, outdated operating systems, and exposed sensitive records across all infrastructure perimeters.

The Survey phase eliminates technical blind spots before they cause project delays. Unearthing legacy technical debt, undocumented configurations, and system dependencies early ensures your target cloud-native footprints are accurately configured. This protects your enterprise from costly mid-project redesigns and establishes clear performance metrics to measure your transformation success.