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Based on our record, Lambda Face Recognition API seems to be a lot more popular than Spot.io. While we know about 27 links to Lambda Face Recognition API, we've tracked only 2 mentions of Spot.io. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Third-party tools: Don't be afraid to look beyond native AWS. Platforms like Finout or Spot.io offer more granular cost visibility and attribution, which can be invaluable for large teams. - Source: dev.to / about 1 year ago
+1 In my previous stint, I had worked with Spot (https://spot.io/) as one of our vendors. Absolutely great product, amazing customer support and ability to take feature requests, or otherwise address our pain points quickly and effectively. - Source: Hacker News / over 2 years ago
FWIW, I am also a big spot.io fan for our workload. During the holidays I run 30-50% spot instances and run 100% spot most of the year. Source: over 3 years ago
Also, you definitely should look into Reservations, and (sale pitch coming) Spot can help you manage those. Source: over 3 years ago
All of this is on spot-instances. We used spot.io (I believe the product is called "Ocean") and they basically took care of all the backend logic to make spot-instances available for the ECS cluster. Source: over 4 years ago
Setup time matters too. The delta between Runpod and bare-metal providers like Lambda Labs is large. Reaching an equivalent setup on a bare VM requires provisioning the instance, configuring the OS and CUDA drivers, installing Docker, setting up your orchestration layer (Kubernetes or Slurm), deploying your inference container, configuring autoscaling rules, and wiring up your load balancer. Thatโs a realistic... - Source: dev.to / 5 months ago
Let's do the math for a representative setup: GPT-OSS-120B via Together.ai ($0.15/$0.60) vs self-hosting on H100s from Lambda Labs at $2.99/hr ($2,183/mo). A single H100 running a 70B model produces roughly 50 tokens/second on average, which works out to about 130M tokens per month. - Source: dev.to / 6 months ago
How does this compare to https://lambdalabs.com/. - Source: Hacker News / about 3 years ago
Another option is to pay for AWS server with a beefy GPU and enough RAM. It's not too cheap, but isn't expensive either if you aren't planning to run it 24/7. Or get a GPU cluster from a company that offers stuff for ML specifically, it might be easier to set up compared to AWS and in some cases cheaper. Like, for example, lambdalabs that offers H100 gpu for 2 bucks per hour. Source: about 3 years ago
I used some of the cloud GPUs on Vast.ai, but I also tried Lambda Labs, and these days I have my own docker container setup which can be deployed to a VM on Google Cloud and used more programatically. Source: over 3 years ago
Terraform - Tool for building, changing, and versioning infrastructure safely and efficiently.
Mattermost - Mattermost is an open source alternative to Slack.
Puppet Enterprise - Get started with Puppet Enterprise, or upgrade or expand.
Vast.ai - GPU Sharing Economy: One simple interface to find the best cloud GPU rentals.
Packer - Packer is an open-source software for creating identical machine images from a single source configuration.
ipinfo.io - Simple IP address information.