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Koyeb – Deploy code to production, everywhere, in minutes

Hacker News

Koyeb – Deploy code to production, everywhere, in minutes

Hi HN! We’re Yann, Edouard, and Bastien from Koyeb ( https://www.koyeb.com/ ). We’re building a platform to let you push code to production, everywhere, and on high-performance hardware, in minutes. We aim to provide a “global serverless feeling”, without the hassle of re-writing all your apps or managing k8s complexity [1]. We built Scaleway, a cloud service provider where we designed ARM servers and provided them as cloud servers. During our time there, we saw customers struggle with the same issues while trying to deploy full-stack applications and APIs resiliently. As it turns out, deploying applications and managing networking across a multi-data center fleet of machines (virtual or physical) requires an overwhelming amount of orchestration and configuration. At the time, that complexity meant that multi-region deployments were simply out-of-reach for most businesses. When thinking about how we wanted to solve those problems, we tried several solutions. We briefly explored offering a FaaS experience [2], but from our first steps, user feedback made us reconsider whether it was the correct abstraction. In most cases, it seemed that functions simply added complexity and required learning how to engineer using provider-specific primitives. In many ways, developing with functions felt like abandoning all of the benefits of frameworks. Another popular option these days is to go with Kubernetes. From an engineering perspective, Kubernetes is extremely powerful, but it also involves massive amounts of overhead. Building software, managing networking, and deploying across regions involves integrating many different components and maintaining them over time. It can be tough to justify the level of effort and investment it takes to keep it all running rather than work on building out your product. We believe you should be able to write your apps and run them without modification with simple scaling, global distribution transparently managed by the provider, and no infrastructure or orchestration management. Koyeb is a cloud platform where you come with a git repository or a Docker image, we build the code into a container (when needed), run the container inside of Firecracker microVMs, and deploy it to multiple regions on top of bare metal servers. There is an edge network in front to accelerate delivery and a global networking layer for inter-service communication (service mesh/discovery) [3]. We took a few steps to get the Koyeb platform to where it is today: we built our own serverless engine [4]. We use Nomad and Firecracker for orchestration, and Kuma for the networking layer. In the last year, we spawned two regions in Washington, DC and Frankfurt, added support for native workers, gRPC, HTTP/2 [5], WebSockets, and custom health checks. We are working next on databases, autoscaling, and adding four new regions (US West, Singapore, Tokyo, and Paris). We’re super excited to show you Koyeb today and we’d love to hear your thoughts on the platform and what we are building in the comments. To make getting started easy, we provide $5.50 in free credits every month so you can run up to two services for free. P.S. A payment method is required to access the platform to prevent abuse (we had hard months last year dealing with that). If you’d like to try the platform without adding a card, reach out at support@koyeb.com or @gokoyeb on Twitter. [1] https://www.koyeb.com/blog/the-true-cost-of-kubernetes-peopl... [2] https://www.koyeb.com/blog/the-koyeb-serverless-engine-docke... [3] https://www.koyeb.com/blog/building-a-multi-region-service-m... [4] https://www.koyeb.com/blog/the-koyeb-serverless-engine-from-... [5] https://www.koyeb.com/blog/enabling-grpc-and-http2-support-a...

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Indie HackersFits the IH revenue-focused audience · Strong signals: started · Missing: supports, reddit linkedin, podcasting
93%93% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Hacker NewsStrong engagement from HN community · Strong signals: excited, ide, io · Missing: https docs, just released, exist
81%81% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Product HuntOn track for Day 1 leaderboard · Strong signals: mac, apps, user · Missing: agents, macos, agent
73%73% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: platform · Missing: plus, intuitive, reviews
33%33% predicted probability of success on AppSumo, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: apps, month, way · Missing: mobile apps, ios, personal
31%31% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue
16%16% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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