We’ve had an idea for years since we first had to deal with the problem everyone who works with cloud services encountered. We ended up locked into public cloud providers and moving was just too complicated. Our developers were spending a lot of time on managing the cloud infrastructure they could instead dedicate to the innovations they wanted to build.
Then it struck us. What if you could just migrate between cloud providers in seconds while achieving the best cost and performance combination? Can you deploy your application to the cloud in one day or maybe even in a few hours? Is it even possible? In theory, yes. But will it work?
It took us some time to answer all these questions, but today we are happy to announce the first multi-cloud platform called CAST AI.
We built CAST AI with a few ideas in mind:
- Developers should have a tool to take advantage of everything that AWS, Azure, and other public cloud vendors offer.
- Moving between cloud services should be easy so that developers can always benefit from the best combination of cost and performance.
- Companies should never end up wasting the cloud resources they pay for again.
- We want to save thousands of developer lifetimes and billions of company expenses on cloud computing.
CAST AI connects AWS, Azure, and Google Cloud into one multi-cloud platform, allowing its users to deploy, manage, and cost-optimize applications in multiple clouds simultaneously. On a single cluster.
After months of hard work, we’re finally ready to show it to you.
What can you expect from CAST AI?
Multi-cloud capabilities
We connect the clouds via a secure network mesh so that any cloud services of one provider are available on any other cloud. No more vendor lock-in, no more cloud waste. You can finally take advantage of everything that AWS, Azure, and Google Cloud have to offer.
Autoscaling
An autoscaler that follows policies you set for it adjusts compute resources in real time – adding workload replicas when the application needs it. You get an infrastructure that is constantly resized to fit your application’s needs.
Opinionated and production-ready
When creating a Kubernetes cluster in CAST AI, you get a few predetermined configuration choices that take you a step closer to production. We made some choices about logging, metrics, and health checks using our many years of Kubernetes expertise. The networking configuration allows for maximum observability while maintaining excellent performance.
Auto-healing
If anything goes wrong or a component is accidentally deleted, you don’t need to worry. CAST AI will bring your cluster back to a healthy state.
Built-in observability
Your cluster will automatically come with Prometheus for Metrics collection, ElasticSearch and Filebeat for log collection and indexing, and a single sign-on to observability frontends (Kibana for logs and Grafana for metrics).
You can leave anytime
Want to stop using CAST AI? No problem, you can leave anytime. Your cluster will stay operational even if you’ve been using our multi-cloud features.
Early birds: everyone is welcome to join for Free
Early birds get up to 20 CPUs for free and pay no subscription fee. Our Engineering and product teams are looking forward to your feedback. We are building CAST AI to make developers’ jobs easier, so don’t hesitate to ping us with any suggestions and join our community.
We’re an open community of cloud users, so feel free to join us and have a chat with our engineers and founders on Slack.
Start optimizing your cluster
CAST AI automates Kubernetes cost, performance, and security management in one platform, achieving over 60% cost savings for its users.
Join us for this journey and fight.
Yours,
Yuri Frayman
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