The sources provide practical guidance for setting up a development environment on laptops that rely either on integrated graphics (iGPU) or on an Nvidia RTX 4050 dGPU. Both articles emphasize configuring WSL2 resource limits on Windows to prevent the virtualized environment from consuming all system RAM, which can cause slowdowns or crashes when running containers. They recommend creating or editing a .wslconfig file to cap WSL2 memory, CPU processors, and swap space, and to enable autoMemoryReclaim. For GPU-accelerated workflows, the articles state that users with an RTX 4050 should install the NVIDIA Container Toolkit to enable Docker GPU passthrough. At the same time, they highlight the practical limitation of the RTX 4050’s VRAM (described as commonly around 6GB), warning against workloads that require larger amounts of GPU memory. The sources also cover thermal management: using Balanced or Silent profiles for regular coding, and switching to Performance/Turbo for heavier build, render, or training tasks—while noting that GPU workloads benefit from being plugged in to reach maximum TGP. They mention that fan noise and heat increase during heavy Docker or build activity, and suggest monitoring for thermal throttling.