Lambda Face Recognition API
Mattermost
Vast.ai
ipinfo.io
Grafana
Platform.sh
PostHog
Causal App
Google Cloud Run
AWS Lambda
Spot.io
Fission.io
Google App Engine
Knative
APeX
Nuclio
It is well-suited for developers and businesses looking to deploy microservices, RESTful APIs, or containerized applications without managing servers. It is particularly beneficial for applications experiencing variable workloads or requiring high scalability.
Based on our record, Google Cloud Run should be more popular than Lambda Face Recognition API. It has been mentiond 93 times since March 2021. 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.
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
Every single one of them ran on Cloud Run. - Source: dev.to / 5 months ago
Frontend (Chainlit on Cloud Run): A Python-based UI that handles user sessions, chat history, and authentication. - Source: dev.to / 6 months ago
I built the server, which I call my podcast-assistant-mcp, using FastMCP and Google's GenAI libraries, all containerized via Docker and ready for deployment to Cloud Run. - Source: dev.to / 10 months ago
The future is getting weird in a good way. New technologies like AWS Firecracker and serverless containers (AWS Fargate, Google Cloud Run) are basically giving you VM-level security with container-level performance. - Source: dev.to / about 1 year ago
AWS Fargate, Google Cloud Run and Azure Container Apps offer services to deploy containers serverless in the cloud. The three providers are the biggest in the industry, but how do their prices compare? One thing all 3 providers have in common: Their pricing is pretty complicated and it can be hard to keep the overview. - Source: dev.to / over 1 year ago
Mattermost - Mattermost is an open source alternative to Slack.
AWS Lambda - Automatic, event-driven compute service
Vast.ai - GPU Sharing Economy: One simple interface to find the best cloud GPU rentals.
Spot.io - Build web, mobile and IoT applications using AWS Lambda and API Gateway, Azure Functions, Google Cloud Functions, and more.
ipinfo.io - Simple IP address information.
Fission.io - Fission.io is a serverless framework for Kubernetes that supports many concepts such as event triggers, parallel execution, and statelessness.