Modal
vagon
Google Cloud Platform
LangChain
Saasufy
Mimic
Autocode
Banana.dev
Deployment.io
Harness
Jenkins
GitHub Actions
Render UIKit
Heroku
Vercel
1-Click Deploy
Deployment simplifies continuous code integration and delivery automation for startups and agile engineering teams on the AWS cloud, eliminating the need for DevOps engineering. A developer can deploy static sites, web services, and environments without knowledge of AWS or DevOps. Deployment supports previews on pull requests and automatic deployments on code push without manual setup or scripting. It enables engineering teams to focus on tasks that add customer value instead of worrying about DevOps-related grunt work.
Modal Deployment.ioNo features have been listed yet.
Deployment.io's answer:
I led engineering teams at early-stage startups and realized that startups waste 70% of valuable engineering time on tedious, non-coding tasks that they can easily automate.
To solve this problem, we've built Deployment.io so engineering teams at startups can focus on writing more code that adds value and helps them achieve PMF faster.
Deployment.io's answer:
ReactJs using Typescript, GatsbyJs using Typescript, GoLang, and AWS
Deployment.io's answer:
Deployment.io is built and designed for startups. Our customers can onboard in 5 minutes and start deploying apps to AWS without any DevOps or AWS knowledge. Other platforms are complex and require scripting or DevOps knowledge. They are built for bigger companies with a lot of resources.
Deployment.io's answer:
Startups and agile engineering teams should choose Deployment.io for the simplicity and ease of use. Our competitors are complex and are designed for bigger companies.
Deployment.io's answer:
For startups, speed and focus are crucial. Our primary audience is engineering teams at startups that want to focus on building code that adds value and not on DevOps related grunt work.
Deploying web apps on AWS has never been this easy and it also takes care of scaling based on usage.
Based on our record, Modal seems to be more popular. It has been mentiond 22 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.
Motivated to find a solution that balanced cost with performance, Martin explored using dlt, a tool known for its simplicity in building data pipelines. By combining dlt with asynchronous operations and using Modal for managed execution, the improvements were substantial:. - Source: dev.to / 3 days ago
The analysis above shows that despite the powerful services offered by large cloud service providers like AWS, there's still a significant learning curve for developers to effectively utilize these services. This might explain the emergence of AI Infra products like LangSmith, Modal, and LaptonAI, which aim to be one-stop service providers for AI applications. We, on the other hand, take a different approach by... - Source: dev.to / about 1 month ago
I'm going to make a left field suggestion and say Modal Labs if you're mostly Python based: https://modal.com/ It should work with other languages through Docker and their Python API, but I can't speak to the ease of deployment in that case. - Source: Hacker News / about 2 months ago
I recommend checking out https://modal.com It’s “serverless” and You only pay for the compute you use. - Source: Hacker News / 2 months ago
Apart from Supabase, I use Modal. I consider it the best hosting service for running ML and AI processes in Python. - Source: dev.to / 2 months ago
vagon - vagon is the simplest high-performance computer that anyone can use.
Harness - Automated Tests For Your Web App
Google Cloud Platform - Google Cloud provides flexible infrastructure, end-to-security, modern productivity, and intelligent insights engineered to help your business thrive.
Jenkins - Jenkins is an open-source continuous integration server with 300+ plugins to support all kinds of software development
LangChain - Framework for building applications with LLMs through composability
GitHub Actions - Automate your workflow from idea to production