MicroVMs and sandboxed compute gaining practical traction
A thread on MicroVMs for isolated sandboxes with full lifecycle control drew comparisons to Google Cloud Run gen2, E2B, and other sandboxed compute primitives. The key questions in the thread were about GPU support and how the lifecycle control compares to existing tools. GPU support is not there yet, which is a significant gap for AI workloads.
The broader pattern is that sandboxed, ephemeral compute is moving from a niche infrastructure concern to a mainstream building block, driven largely by agent and AI workloads that need to run untrusted code safely. E2B being a reference point in the thread is notable because it started as a very specific AI-agent-focused product and is now being used as the benchmark for a general infrastructure comparison.
DeepSeek's inference optimization thread also touched on speculative decoding with small specialized models, which implies more compute orchestration complexity, not less. The demand for fine-grained sandboxed execution is going to keep growing.
So what?
If you are building anything that executes model-generated code or runs agent loops, sandboxed compute is not optional infrastructure, it is the trust boundary for your whole product. The current tooling is still maturing, especially on GPU support, which means there is room for a product that solves this cleanly.