Infrastructure teams face a fragmented tooling landscape. VM migration requires one vendor, disk conversion another, Kubernetes management a third, and GPU compute yet another. Each tool brings its own API surface, its own authentication model, and its own operational overhead.

Today we are announcing that the HyperSDK platform has grown to eleven products -- a complete infrastructure lifecycle from export through deployment, observation, and optimization.

There are 300,000+ VMware customers who need to migrate off VMware. Most of them do not have the internal expertise to do it. That is your opportunity.

Air-gapped networks -- environments with no physical or logical connection to the internet -- present unique challenges for VM migration. Standard migration tools assume network connectivity for package downloads, driver repositories, and cloud API calls. HyperSDK was designed from the ground up to operate in fully disconnected environments, making it the platform of choice for government, defense, and compliance-restricted organizations.

Data centers account for roughly 1-1.5% of global electricity consumption, and that number is rising. Every VM migration involves sustained disk I/O, network transfer, and CPU-intensive format conversion -- all of which consume energy. What if your migration platform could automatically schedule those workloads for times when the electrical grid is cleanest? That is exactly what HyperSDK's carbon-aware scheduling does.

One of the most common concerns we hear from organizations migrating from VMware to KVM is GPU support. VMware's vSphere has mature GPU passthrough and vGPU capabilities, and teams running AI/ML training, inference, VDI, or scientific computing workloads need assurance that these capabilities transfer to KVM. The answer is straightforward: KVM's GPU passthrough via VFIO delivers 98%+ of bare-metal GPU performance, and HyperSDK automates the configuration that traditionally requires manual kernel and libvirt setup.

When you need to upload a 50 GB VM disk image through a web browser, a single HTTP POST is not going to work. Network interruptions, browser tab crashes, and corporate proxy timeouts all conspire to make large uploads fail. HyperSDK solves this with a chunked upload protocol that splits files into 10 MB pieces and supports resume from the last successful chunk.

When we set out to build HyperSDK's observability layer, we had a clear constraint: no external dependencies. No Prometheus node exporter, no collectd, no StatsD sidecar. The daemon had to collect, store, analyze, and serve system metrics entirely on its own. This is the story of how we built a self-contained observability stack in Go using nothing but /proc, /sys, and a ring buffer.

VM migration is inherently complex. You are dealing with multiple source and target hypervisors, disk format conversions, network reconfiguration, and dozens of jobs running in parallel. A CLI is great for automation, but when you need to understand the state of a migration at a glance, a well-designed web interface makes all the difference. That is why HyperSDK ships with 45 dashboard views covering every aspect of the migration lifecycle.

When we started building hyper2kvm, the VM conversion engine that powers HyperSDK migrations, we assumed we would use libguestfs for disk image manipulation. It is the standard tool, backed by Red Hat, with a mature API and wide Linux distribution support. Six months in, we replaced it entirely with VMCraft -- a pure Python VM manipulation engine that reads and writes disk images directly without booting an appliance. This post explains why, and what we gained.

VM migration projects fail most often due to inadequate planning, not technical limitations. Whether you are migrating 20 VMs or 2,000, following a structured checklist ensures nothing falls through the cracks. This guide covers every phase of a production VM migration, from initial assessment through post-migration validation.