CircleCI
Jenkins
Codeship
Travis CI
Bamboo
Bitrise
TeamCity
Buddy
Lambda Face Recognition API
Mattermost
Vast.ai
ipinfo.io
Grafana
Platform.sh
PostHog
Causal App
CircleCI Lambda Face Recognition APINo Lambda Face Recognition API videos yet. You could help us improve this page by suggesting one.
Based on our record, CircleCI should be more popular than Lambda Face Recognition API. It has been mentiond 83 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.
CircleCI is another popular and mature platform, with extensive support for plugins / reusable workflows in the form of "orbs". - Source: dev.to / 8 months ago
Everyone is free to use alternative CI/CD workflow pipelines. These are often better than Github Actions. There include - https://circleci.com/ - https://www.travis-ci.com/ - Gitlab Anyone can complain as much as they want, but unless they put the money where their mouth is, it's just noise. - Source: Hacker News / 8 months ago
CircleCI Account: You need an active CircleCI account connected to your GitHub repository where the application code resides. If you donโt have one, sign up at circleci.com. - Source: dev.to / about 1 year ago
In this guide, you will explore how to build a fully automated pipeline for processing and updating a vector database using AWS Lambda and CircleCI. The solution involves extracting text from PDFs, generating embeddings with OpenAI, and storing them in Zilliz Cloud, a managed vector database. You will also set up AWS infrastructure (S3, ECR, and Lambda) and implement a CI/CD pipeline with CircleCI to automate... - Source: dev.to / about 1 year ago
CircleCI: Still solid, but watch pricing and concurrency limits. - 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
Jenkins - Jenkins is an open-source continuous integration server with 300+ plugins to support all kinds of software development
Mattermost - Mattermost is an open source alternative to Slack.
Codeship - Codeship is a fast and secure hosted Continuous Delivery platform that scales with your needs.
Vast.ai - GPU Sharing Economy: One simple interface to find the best cloud GPU rentals.
Travis CI - Simple, flexible, trustworthy CI/CD tools. Join hundreds of thousands who define tests and deployments in minutes, then scale up simply with parallel or multi-environment builds using Travis CIโs precision syntaxโall with the developer in mind.
ipinfo.io - Simple IP address information.
