CAST AI is driven by a vision of decentralizing the cloud industry to free innovators from the limitations of cloud service providers. Our AI-powered cloud optimization engine delivers a cost-efficient, high-performing, and resilient infrastructure for every Kubernetes workload. Its unique blend of automation and optimization algorithms empowers innovators to build future-ready products and embrace the autonomous cloud. No more vendor lock-in or downtime, the cloud just got solved.
Based on our record, Amazon EC2 should be more popular than Cast.ai. It has been mentiond 73 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.
These packages are not limited to Lambda. You can use them to validate tokens in Express servers running on EC2 instances or containers, for example. - Source: dev.to / 30 days ago
📌 Get started with EC2: https://aws.amazon.com/ec2/. - Source: dev.to / about 1 month ago
By adopting Docker, you can seamlessly deploy to platforms such as Railway and leverage AWS services like Elastic Container Registry (ECR) and Elastic Compute Cloud (EC2). Docker also integrates smoothly with modern CI/CD workflows and Infrastructure as Code, aligning perfectly with DevOps best practices. - Source: dev.to / about 2 months ago
Note: When you launch the SageMaker Studio instance, it essentially spins up an EC2 instance behind the scene to run the Jupyter notebook environment. SageMaker manages the EC2 instance for you and handles provisions and scaling of the underlying infrastructure based on your project needs. It is also best practices to terminate (delete) an EC2 instance once the project completion and the instance is no longer... - Source: dev.to / 3 months ago
Why Amazon Web Services (AWS)? I am currently building both the frontend (Android) and the backend service (SpringBoot) of a product (unfortunately, I can’t give too many details about this). After researching various cloud platforms, I chose AWS for its robust ecosystem and flexibility. For my project, I decided to use the free tier of two key AWS products: Amazon RDS for my PostgreSQL database and Amazon EC2... - Source: dev.to / 5 months ago
There are tools CastAI (https://cast.ai/) and KubeCost (https://www.kubecost.com/) which helps you get these values. I haven't tried it personally, but they are promising. There are other tools as well. One of the approach OP suggested, monitor the values over a period of time to determine the right requests value, is really good one. I would modify it a bit. Generally take the p95 value for requests and 1.5-2x... Source: almost 2 years ago
Not sire if this helps but someone just showed me this free tool that looks at cost for Kube https://cast.ai/. Source: about 2 years ago
Curious about what about cast.ai sets it apart for you? I went with spot because it is owned by a big company and knew it wasn't going to disappear. I think cast was still in invite only mode, as well. Source: over 2 years ago
I found that cast.ai seems to have this functionality but am wondering if there is a free option. Also pursuing gMaestro but they're not available on arm64 yet. Source: over 2 years ago
If you're using Kubernetes, CAST AI is the fastest way to significantly reduce your compute bill and keep it there. It manages compute capacity automatically and has dedicated support to get you started even faster. The best part - Kubernetes cost monitoring and security insights are free. Source: over 2 years ago
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