Amazon API Gateway might be a bit more popular than Apache Airflow. We know about 107 links to it since March 2021 and only 75 links to Apache Airflow. 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 / 8 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 / 28 days 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 1 month ago
The API Gateway includes an endpoint structured like this:. - Source: dev.to / about 1 month 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 1 month ago
Is this really true? Something that can be supported by clear evidence? I’ve seen this trotted out many times, but it seems like there are interesting Apache projects: https://airflow.apache.org/ https://iceberg.apache.org/ https://kafka.apache.org/ https://superset.apache.org/. - Source: Hacker News / 2 months ago
Apache Airflow offers simplicity when it comes to scheduling, authoring, and monitoring ML workflows using Python. The tool's greatest advantage is its compatibility with any system or process you are running. This also eliminates manual intervention and increases team productivity, which aligns with the principles of Platform Engineering tools. - Source: dev.to / 3 months ago
Data orchestration tools are key for managing data pipelines in modern workflows. When it comes to tools, Apache Airflow, Dagster, and Flyte are popular tools serving this need, but they serve different purposes and follow different philosophies. Choosing the right tool for your requirements is essential for scalability and efficiency. In this blog, I will compare Apache Airflow, Dagster, and Flyte, exploring... - Source: dev.to / 3 months ago
Data pipelines: Apache Kafka and Airflow are often used for building data pipelines that can continuously feed data to models in production. - Source: dev.to / 4 months ago
This article demonstrates how to work with near real-time and historical data using the dlt package. Whether you need to scale data access across the enterprise or provide historical data for post-event analysis, you can use the same framework to provide customer data. In a future article, I'll demonstrate how to use dlt with a workflow orchestrator such as Apache Airflow or Dagster.``. - Source: dev.to / 5 months ago
AWS Lambda - Automatic, event-driven compute service
Make.com - Tool for workflow automation (Former Integromat)
Postman - The Collaboration Platform for API Development
ifttt - IFTTT puts the internet to work for you. Create simple connections between the products you use every day.
Apigee - Intelligent and complete API platform
Microsoft Power Automate - Microsoft Power Automate is an automation platform that integrates DPA, RPA, and process mining. It lets you automate your organization at scale using low-code and AI.