Mystic AI

Hey PH! I'm Oscar, co-founder of Mystic AI, and I want to share why Turbo Registry is a game changer. Since 2020, we've been in the serverless GPU space, and one persistent challenge has been cold-starts. When you're running custom ML models—like LLMs, image-gen, or video-gen—you need varying numbers of GPUs based on traffic. The issue? When demand spikes, you need more GPUs fast, but cold-starts can slow you down. This process involves three stages: getting GPU access from the cloud provider, loading the necessary code (usually a Docker image), and finally loading the model into GPU memory. The most time-consuming part is often the second stage: loading Docker images. Depending on the size of the image, this can take several minutes. That's where Mystic Turbo Registry shines, reducing this time by up to 15x. Check out these benchmarks: 5GB Docker images load in 10.23 seconds (down from 82.21 seconds with a standard Docker Registry). 10GB Docker images load in 14.75 seconds (down from 147 seconds). 20GB Docker images load in 23.72 seconds (down from 270.47 seconds). We've achieved this with a Rust-based Docker registry and a custom containerd adapter that optimizes image loading. Sounds impressive, right? Accessing this Docker Registry is simple—it's already available to our serverless API users. Just sign up with Mystic, choose the tier that fits your workload, and enjoy up to 15x faster cold-starts today! To celebrate, we're offering 50% off your first month's payment.

Congrats on this amazing launch! 🚀 That speed boost for loading ML models is a game changer. Excited to see the impact on cold start times!

Impressive launch! Reducing cold start times by 90% with your custom Docker registry is a game changer for ML deployment. Can't wait to see how this boosts overall ROI for the community. Upvoted!