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Cloud Run (GCR) -- the latest serverless platform; OCI-compliant containers (Docker, Buildpacks, etc.) Cloud Functions (GCF) -- originally serverless functions to compete with AWS Lambda; latest generation rebranded as Cloud Run Functions. - Source: dev.to / 9 months ago
One of the best benefits of Docker is that it helps you make your software multi-environment friendly, so you can use the same (or similar) config from local dev to production. Having a Dockerfile for every environment kind of defeats the purpose. Optimizing it means using env vars and keeping the overall architecture more abstract. - Source: dev.to / 11 months ago
Before we begin, ensure you have Docker installed on your system. You can download it from Docker's official website. - Source: dev.to / 12 months ago
You can use Docker to spin up an instance of WordPress on your local computer and in the cloud. But does it make sense to use WordPress in Docker? - Source: dev.to / about 1 year ago
Ghost is an open source blogging and newsletter platform designed for professional publishers. In this guide, I want to show you, how you can spin up and deploy your own instance of Ghost using Docker and Sliplane. - Source: dev.to / about 1 year 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
Kubernetes - Kubernetes is an open source orchestration system for Docker containers
Mattermost - Mattermost is an open source alternative to Slack.
Google App Engine - A powerful platform to build web and mobile apps that scale automatically.
Vast.ai - GPU Sharing Economy: One simple interface to find the best cloud GPU rentals.
Apache Karaf - Apache Karaf is a lightweight, modern and polymorphic container powered by OSGi.
ipinfo.io - Simple IP address information.