Workload Profile and Metric Analysis
Current resource usage (CPU, RAM, Disk I/O, Network Throughput), peak usage times, and data growth rates are measured.
Server infrastructure consulting is a service that involves the end-to-end planning and scaling of the most optimal physical, virtual, or cloud-based compute, storage, and network architectures to meet current and future application and data workload requirements for organizations.
Improperly designed server investments can lead to high maintenance costs, underutilized resources, or system bottlenecks during critical load periods. Server architecture is not just about selecting CPU and RAM quantities.
The process includes analyzing disk IOPS values, latency, High Availability (HA) requirements, licensing models, automated backups, scalability, data growth rates, and single points of failure (SPOF). Physical hardware, virtualization, and cloud alternatives are analyzed from a Total Cost of Ownership (TCO) perspective to determine the most suitable architecture for the workload.
Current resource usage (CPU, RAM, Disk I/O, Network Throughput), peak usage times, and data growth rates are measured.
On-premise hardware, data center colocation, virtual server (VPS/Bare-Metal), and Public/Private Cloud options are compared in terms of cost, performance, and authorization parameters.
Compute, storage architecture (SAN/NAS/NVMe), network bandwidth, cluster clustering, backup, and disaster recovery scenarios are designed.
Hardware/service supply, data transfer, testing, go-live, and acceptance criteria are prioritized to minimize risks.
Assess the current environment, target and dependencies
Document scope, risks, acceptance and rollback
Implement, validate and document
There is no single correct answer. Deciding between cloud and physical hardware without considering factors such as data traffic, licensing costs, expected growth rates, data privacy regulations (GDPR, etc.), and the operational expertise of the internal team can lead to inefficient budget utilization.
User count or concurrent session numbers alone are insufficient for capacity planning. Calculations should be based on actual CPU/RAM trend data from the existing infrastructure, real-time disk read/write (IOPS) values, network bandwidth consumption, and a 12-36 month projected growth forecast.
No, not all workloads require the same level of HA architecture. A tiered availability model is designed based on the financial and operational costs of potential disruptions, the tolerance for maximum downtime (RTO), and the allocated budget.
We review your current environment, target and technical requirements in a 20–30 minute call. Scope, assumptions, deliverables and pricing are documented before work begins.
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