Systems | Development | Analytics | API | Testing

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Announcing Moesif API Analytics and Monetization For Gravitee.io

We are thrilled to announce that Moesif now offers full plugin support for Gravitee.io! This new integration provides Gravitee.io users with advanced API analytics and monetization capabilities, empowering you to gain deeper insights into your API usage and optimize your API strategy. Whether you’re looking to monitor performance, understand user behavior, or implement flexible monetization models, Moesif’s robust feature set is now at your fingertips within the Gravitee.io ecosystem.

How to use Flink SQL, Streamlit, and Kafka: Part 1

Market data analytics has always been a classic use case for Apache Kafka. However, new technologies have been developed since Kafka was born. Apache Flink has grown in popularity for stateful processing with low latency output. Streamlit, a popular open source component library and deployment platform, has emerged, providing a familiar Python framework for crafting powerful and interactive data visualizations. Acquired by Snowflake in 2022, Streamlit remains agnostic with respect to data sources.

How to build a Rails API with rate limiting

APIs are the bread and butter of the internet. The ability to interact with our applications programmatically enables interoperability and makes our lives as developers easier. Unfortunately, web applications are vulnerable to malicious actors that seek to misuse them or degrade their performance, which is why rate limiting is an important part of any API.

Scaling Ruby on Rails Using Containerization and Orchestration

After Twitter moved from Ruby to Scala in 2009, the story was born that Ruby on Rails can’t scale. The story goes that it lacks robustness, is a memory hog, and lacks the concurrency features you need to grow an application. This has been the prevailing wisdom for over a decade. And then along came Shopify, showing that, as Lutke says, Ruby on Rails is a framework that can process billions of events per day and evidently does scale. Ruby on Rails is an excellent candidate for scaling.

A Monumental Year for Qlik's Data Integration and Quality Business

At Qlik World 2023, Mike Capone stood on stage and proudly announced the acquisition of Talend to form Qlik’s Data Business Unit. The Data BU had the charter to combine the best of Qlik Data Integration with Talend and Stitch Data to deliver market-leading data integration and quality solutions.

Snowflake Massively Expands Types of Applications That Can Be Built, Deployed and Distributed on Snowflake

Apps are the way to democratize AI: to make it accessible to everyone and streamline customers’ experiences with faster time to insights. According to a recent IDC survey, AI applications is currently the largest category of AI software, accounting for roughly one-half of the market’s overall revenue in 2023.

Introducing Polaris Catalog: An Open Source Catalog for Apache Iceberg

Open source file and table formats have garnered much interest in the data industry because of their potential for interoperability — unlocking the ability for many technologies to safely operate over a single copy of data. Greater interoperability not only reduces the complexity and costs associated with using many tools and processing engines in parallel, but it would also reduce potential risks associated with vendor lock-in.

5 Reasons You Need to Add Atlas to Microsoft Dynamics

Originally created in the 1890s, the Swiss army knife was a logical solution to officers’ need to be able to repair their weapons, open their canned food, and cut things as needed. Since then, simple items that offer multiple solutions to achieve a goal are often referred to as being the Swiss army knife of their kind.

How to Identify and Manage Software Testing Risks

As software releases are expected to happen faster, testers are placed under more pressure. Pressure to find and eradicate bugs earlier in the release cycle, to avoid them being costly and delaying release timelines. That said, if companies want to stay ahead of the competition, it's important from the outset their testing processes are free from risks and vulnerabilities. Can automated testing best ensure thorough validation? How can team procedures proactively avoid risk?