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I carved one Azure H100 into virtual “cubicles” using MIG (Multi-Instance GPU), compared it to an A100, ran Triton inference workloads, and captured both latency and cost. The verdict – The H100 with MIG delivers better latency and consistency, while the A100 is more cost-effective at scale, depending on your workload.

Everyone is talking about Model Context Protocol (MCP). The promise – let models talk directly to systems instead of building endless glue code. I wanted to see how it can solve several existing challenges, both internally and for our customers. So, I ran two real-world projects: Both solutions moved beyond theory; they’re running in production today.