# Heroku vs AWS: Pick the Best Platform to Deploy > See which is better among Heroku or AWS for deployment in 2026. Compare pros, cons, and see how Kuberns combines the best of both and gives the AI power. - **Author**: parth-kanpariya - **Published**: 2025-07-20 - **Modified**: 2026-03-23 - **Category**: Alternatives - **URL**: https://kuberns.com/blogs/heroku-vs-aws/ --- [Heroku](https://kuberns.com/blogs/what-is-heroku/) vs AWS, which one should you choose? If you are searching for this answer, you are likely deciding between simplicity and control.  But the honest answer to this is that neither Heroku nor AWS is truly ideal for modern deployments. Heroku makes deployment easier. AWS gives you full control over servers and networking, but requires significantly more setup and operational knowledge. So while both platforms solve part of the problem, they leave you managing operational work. Instead of choosing between convenience and control, developers are now looking for platforms powered by AI automation. This is where [Agentic AI-powered deployment platforms](https://kuberns.com/blogs/what-is-kuberns-the-simplest-way-to-build-deploy-and-scale-full-stack-apps/) come in. So, now, instead of choosing between Heroku’s simplicity and AWS’s control, with AI, you can deploy your application in one click, and the system manages the complexity for you. In this guide, we break down Heroku vs AWS in detail. We will also show you why many teams are moving toward [Agentic AI platforms like Kuberns](https://kuberns.com/) to eliminate manual deployment work completely. ### TL;DR If you want simplicity without limits and control without complexity, this guide helps you make the best decision and choose the smarter option. * Heroku is easier than managing AWS directly, but it still requires manual configuration. You choose dyno sizes, manage add-ons, and adjust scaling as traffic grows. Costs can increase quickly as you add more dynos and services. * AWS gives you full infrastructure control and flexibility. However, you are responsible for setup, architecture decisions, scaling logic, and ongoing infrastructure management. It requires DevOps knowledge and operational effort. * Both platforms solve part of the deployment problem, but neither removes manual infrastructure work completely. * [Kuberns](https://kuberns.com/) offers the best option to deploy than Heroku and AWS. Powered by Agentic AI, it deploys your application in one click and automatically handles configurations, provisioning, and optimisation. No manual infrastructure setup needed. ## Why Heroku and AWS Fall Short in 2026? ![challenges in heroku and aws](https://kuberns-blogs.s3.ap-south-1.amazonaws.com/challenges-in-heroku-and-aws.png) Both Heroku and AWS helped define modern application hosting. But developer expectations have changed. In 2026, teams are not just looking for cloud platforms that automate a part of deployment. But they are looking for platforms that remove friction from the entire deployment process. Here is how Heroku and AWS work for you and against you. ### Heroku: Legacy Platform, But Expensive and Limited Heroku became popular because it made deployment simpler than managing raw cloud infrastructure. You could push code and get an app running. But that simplicity comes with boundaries. Since the free tier ended, even small projects require paid plans. As applications grow, dyno upgrades and add-ons increase monthly costs quickly. Scaling means adding more dynos, which becomes expensive over time. Customisation is also limited. If your deployment needs are outside standard buildpacks or workflows, you often need workarounds. CI/CD is basic, so many teams rely on external tools to build proper pipelines. Heroku reduces complexity, but it does not eliminate operational work. You still make decisions about scaling, add-ons, and cost management as traffic grows. It works well early on. It becomes restrictive later. ### AWS: Powerful, But Operationally Heavy AWS offers the opposite experience. You get full control over infrastructure. You can configure networking, optimise compute resources, and design highly scalable architectures. For teams with DevOps expertise, that flexibility is powerful. But control comes at a cost. Setting up even a basic deployment pipeline requires configuring services, permissions, networking, and compute resources. You manage containers or virtual machines. You maintain configuration files. You monitor usage and tune infrastructure over time. Pricing can also be difficult to predict. While individual services may seem inexpensive, misconfigured or unused resources can quietly increase costs. Watch this Quick video to know the best alternative to Heroku in 2026: