A developer workstation is not the same as a gaming PC. Games benefit from GPU power and raw single-core speed. Development workloads — compiling code, running multiple containers, operating a local dev environment with several services, managing large Git repositories — benefit from core count, RAM capacity, fast NVMe storage, and reliable sustained performance.
Developer workstations built to spec in South Africa for real development workloads.
A developer workstation needs to run a Docker environment, a full IDE, a local database, and a browser with 30 tabs open without becoming a bottleneck. We spec and build them right.
What makes a good developer workstation
We build custom developer workstations for South African developers who are tired of machines that become a bottleneck instead of a tool. Every build is specced around your actual workflow — the languages you use, the containers you run, whether you need GPU compute for ML workloads, and how much RAM your typical working state actually consumes.
What we spec for developer workstations
AMD Ryzen 9 or Intel Core i9 with 12-24 physical cores for parallel compilation
32GB-128GB DDR5 RAM for VM and container-heavy workflows
2TB+ NVMe SSD (Gen 4 or Gen 5) for fast Docker image pulls and build caches
Secondary NVMe or SSD for project storage and Git repositories
Efficient mid-range GPU (or professional GPU for CUDA/OpenCL workloads)
Quiet cooling — a workstation that fans loudly all day is a distraction
Multiple USB-A and USB-C ports for peripherals and external storage
Developer workstation configurations
Standard dev workstation
8-12 core CPU, 32GB DDR5, 1TB NVMe. Handles most web development, mobile development, and light containerised workloads without compromise.
Heavy compilation and CI build machine
16-24 core CPU, 64GB DDR5, 2TB NVMe. Built for teams running local CI pipelines, large monorepos, or C++/Rust/Java projects with long compile times.
ML and AI development workstation
High-core CPU, 64-128GB DDR5, professional or prosumer GPU (RTX 4090, RTX 6000 Ada), fast NVMe. For PyTorch, TensorFlow, and local model training or inference.
Virtualisation host workstation
ECC-capable CPU, 64-128GB RAM, multiple NVMe drives. For developers running multiple full VMs locally — macOS VMs, Windows test environments, or lab setups.
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View service ->Get a developer workstation spec and quote
Tell us your development stack, typical workloads, and budget. We'll spec a machine that fits your workflow.
Questions you probably have.
Should a developer workstation have a high-end GPU?
How much RAM does a developer workstation need?
Is NVMe storage important for development?
Do you build Linux-compatible developer workstations?
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