Amazon API Gateway
Postman
AWS Lambda
Apigee
Django REST framework
Apiary
Amazon S3
Gravitee.io
Saturn Cloud
Amazon SageMaker
Deepnote
Databricks Unified Analytics Platform
Apache Zeppelin
Azure Synapse Analytics
GeoSpock
Google BigQuery
Saturn Cloud is an award-winning ML platform with 75,000+ users, including NVIDIA, CFA Institute, Snowflake, Flatiron School, Nestle, and more. It is an all-in-one solution for data science & ML development, deployment, and data pipelines in the cloud. Users can spin up a notebook with 4TB of RAM, add a GPU, connect to a distributed cluster of workers, build large language models, and more in a completely hosted environment.
Data scientists and analysts work best using the tools they want to use. You can use your preferred languages, IDEs, and machine-learning libraries in Saturn Cloud. We offer full Git integration, shared custom images, and secure credential storage, making scaling and building your team in the cloud easy. We support the entire machine learning lifecycle from experimentation to production with features like jobs and deployments. These features and built-in tools are easily shareable within teams, so time is saved and work is reproducible.
Amazon API GatewaySmooth and bug free experience. There are ready data science images with pre loaded packages for most common scenarios, making you focus on the project/problem and leave the infrastructure part to Saturn Cloud.
True story, way better than just sweating Colab. The best and cheapest compute services there is.
I have started using this to run the computations which generally require like 64+GB of RAM, and the procedure to setup the enviroment is also nice. Got all the R packages running smoothly.
Based on our record, Amazon API Gateway seems to be a lot more popular than Saturn Cloud. While we know about 107 links to Amazon API Gateway, we've tracked only 7 mentions of Saturn Cloud. 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.
AWS API Gateway is Amazon’s managed gateway service, designed to work seamlessly within the AWS ecosystem. It supports both REST and WebSocket APIs, with HTTP APIs being the lightweight, lower-cost option for simple proxying and routing use cases. - Source: dev.to / 22 days ago
This opens up a world of customization options for controlling app access. For example, we can embed custom data in the ID token for the front-end client to use, enabling guards to restrict content. Alternatively, we can add custom scopes to the access token and implement fine-grained access control in an API Gateway API. All it takes is some Lambda function code, and Cognito triggers it at the right time. - Source: dev.to / about 1 month ago
When the built-in Amazon API Gateway authorization methods don’t fully meet our needs, we can set up Lambda authorizers to manage the access control process. Even when using Cognito user pools and Cognito access tokens, there may still be a need for custom authorization logic. - Source: dev.to / about 2 months ago
The API Gateway includes an endpoint structured like this:. - Source: dev.to / about 2 months ago
Amazon Web Services exemplifies this approach with automatic volume discounts that encourage increased usage while maximizing revenue at each consumption level. - Source: dev.to / about 2 months ago
After the MLOps tooling evaluation, our focus shifted to data engineering. Some teams in the company were already using tools like Dask and xarray to manage and process their datasets. The architect was determined to build a data lake for the organization. The vision was to make xarray datasets accessible via Intake, using a Dask-capable computing platform. For the compute platform, we explored services like... - Source: dev.to / 4 months ago
Not 100% sure of your intention, but if you work with python, and you're familiar with (or can spend the time learning) dask, and willing to pay, you can consider coiled.io or saturncloud.io that offer managed dask that you can scale and use GPUs etc (again, not sure if applicable to your use case). Source: about 2 years ago
SaturnCloud - Data science cloud environment, that allows to run Jupyter notebooks and Dask clusters. 30 hours free computation and 3 hours of Dask per month. - Source: dev.to / over 2 years ago
I think your site looks good and I have used the type of service you offer, but there are 2 potential problems. As SheepherderPatient51 said,Google already offers all of this for free (and so does https://kaggle.com and https://www.paperspace.com ). There are also other sites just like yours such as https://deepnote.com,https://saturncloud.io, and https://lambdalabs.com . Source: over 2 years ago
* How does it differ from other GPU cloud providers that offer ready to use Jupyter notebooks? (E.g. https://support.genesiscloud.com/support/solutions/articles/47001170102-running-jupyter-notebook-or-jupyterlab-on-your-instance or https://saturncloud.io/). - Source: Hacker News / about 3 years ago
Postman - The Collaboration Platform for API Development
Amazon SageMaker - Amazon SageMaker provides every developer and data scientist with the ability to build, train, and deploy machine learning models quickly.
AWS Lambda - Automatic, event-driven compute service
Deepnote - A collaboration platform for data scientists
Apigee - Intelligent and complete API platform
Databricks Unified Analytics Platform - One platform for accelerating data-driven innovation across data engineering, data science & business analytics
