Cloudamize Data Collection Methodologies: Full Comparison Guide

Overview

To build a highly precise cloud migration strategy, Cloudamize offers several data collection methods designed to fit different corporate security policies, network architectures, and infrastructure environments. Data can be captured directly at the operating system (OS) level using Agent-Based or Agentless collection, or at the virtualization layer using vCenter Integration and Hyper-V Integration.

Selecting the right data collection approach ensures that you accurately capture performance metrics while aligning with your organization's security posture.

Data Collection & Capability Mappings

Technical Infrastructure Prerequisites & Ports

The table below lists the minimum machine requirements, internal ports for machine discovery, and egress communication parameters to the Cloudamize servers:

Product Lifecycle Stage & Feature Matrix

The matrix below shows how core features map across the Discover, Analyze, Plan, Migrate, and Extensions stages of your project lifecycle:

Collected Data Points & Telemetry Depth

The following matrix tracks the precise granularity of data elements captured internally from your environment:

Detailed Telemetry Descriptions

1. System Information

• Processor Details: Captures full string descriptors (e.g., "Intel(R) Xeon(R) CPU X5482 @ 3.20GHz"), clock rates, processor families, and exact allocated core counts.

• Operating System: Exact deployment tracking down to specific version levels (e.g., Microsoft Windows [Version 6.2.9200]).

• System Identification Data: Tracks DNS host names, system domains, workgroups, domain membership status (True/False), parent VM names, MAC addresses, IP addresses, and NIC hardware type details (e.g., Intel(R) 82574L Gigabit Network Connection).

• System Operational Status: Monitors last shutdown time, last boot time, and storage interface characteristics (Disk interface type, manufacturer, serial numbers, descriptions, and logical disk names).

2. System Performance

Monitors real-time utilization baselines across core resource groups to inform the right-sizing engine:

• CPU usage

• Memory usage

• Disk operations

• Network usage

• Cache usage

3. Process Information

Peers directly into the operating system process scheduler to track what software layers are running inside your inventory nodes:

• Process Identification: Captures individual executable names, software vendors, product names, descriptions, and vendor reference URLs.

• Process-Level Resource Performance: Isolates performance footprints per process, tracking isolated CPU usage, memory usage, disk usage, network usage, and application-specific performance counters.

Hybrid Data Collection & Deduplication

Organizations are not forced to pick just one collection method across their data center. Cloudamize completely supports Hybrid Data Collection loops.

For example, a customer can connect via vCenter Integration to rapidly discover their massive multi-thousand node virtual footprint, while simultaneously deploying Agents or Agentless configurations specifically on critical production databases or multi-tier web arrays. The Cloudamize portal automatically deduplicates the virtual and physical entries, combining the deep OS telemetry with the hypervisor structural data cleanly under a single interface view.

If you have any queries, please get in touch with the helpdesk via our Helpdesk Portal or by email at helpdesk@cloudamize.com.