Amazon AWS
Google Cloud Platform
DigitalOcean
Microsoft Azure
Linode
Heroku
Vultr
CloudFlare
Dask
Pandas
NumPy
Apache Airflow
SciPy
Anaconda
PySpark
Burla
Amazon AWSYou could say a lot of things about AWS, but among the cloud platforms (and I've used quite a few) AWS takes the cake. It is logically structured, you can get through its documentation relatively easily, you have a great variety of tools and services to choose from [from AWS itself and from third-party developers in their marketplace]. There is a learning curve, there is quite a lot of it, but it is still way easier than some other platforms. I've used and abused AWS and EC2 specifically and for me it is the best.
Based on our record, Amazon AWS seems to be a lot more popular than Dask. While we know about 486 links to Amazon AWS, we've tracked only 16 mentions of Dask. 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.
In conclusion, Cloudflare Workers and AWS Lambda are two popular edge computing solutions that offer a range of benefits, including reduced latency, improved performance, and enhanced security. By understanding the key differences between these solutions, businesses can make informed decisions about which one to use. Whether you're building a real-time analytics application or a serverless API, Cloudflare Workers... - Source: dev.to / about 1 month ago
> but it's still a singleton instance, so where do you run it? Most hardware doesn't give you enough uptime for what you need here, because what you actually needed was a re-architecture for distribution / failover / whatever, and while you could ask your LLM to do that you aren't going to run your bank on the result. If only we had a way to solve these issues with tools capable of running Rust programs in that... - Source: Hacker News / 2 months ago
Not because infrastructure isn't important. It is. Not because Amazon Web Services (AWS) is a bad platform. It isn't. - Source: dev.to / 3 months ago
The AWS S3 documentation covers all of these in detail. The configuration takes about an hour to get right the first time and rarely needs changes after. - Source: dev.to / 3 months ago
The first pattern is direct-to-storage. The client uploads chunks directly to an object storage service like Amazon S3 using pre-signed URLs. The application server creates the upload session and grants permission but never sees the file bytes. This pattern scales well because the application servers do not handle the upload bandwidth. - Source: dev.to / 3 months ago
We're using a lot of Python. In addition to these, gridMET, Dask, HoloViz, and kerchunk. Source: over 4 years ago
I wrote this for speeding up the RPC messaging in dask, but figured it might be useful for others as well. The source is available on github here: https://github.com/jcrist/msgspec. Source: over 4 years ago
Dask: Distributed data frames, machine learning and more. - Source: dev.to / over 4 years ago
To do that, we are efficiently using Dask, simply creating on-demand local (or remote) clusters on task run() method:. - Source: dev.to / over 4 years ago
I’m quite sure dask helps and has a pandas like api though will use disk and not just RAM. Source: almost 5 years ago
Google Cloud Platform - Google Cloud provides flexible infrastructure, end-to-security, modern productivity, and intelligent insights engineered to help your business thrive.
Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.
DigitalOcean - Simplifying cloud hosting. Deploy an SSD cloud server in 55 seconds.
NumPy - NumPy is the fundamental package for scientific computing with Python
Microsoft Azure - Windows Azure and SQL Azure enable you to build, host and scale applications in Microsoft datacenters.
Apache Airflow - Airflow is a platform to programmaticaly author, schedule and monitor data pipelines.
