Systems | Development | Analytics | API | Testing

We’re excited to talk about our vision for Tableflow, which makes it push-button simple to take Apache Kafka® data and feed it directly into your data lake, warehouse, or analytics engine as Apache Iceberg® tables. Making operational data accessible to the analytical world is traditionally a complex, expensive, and brittle process and we believe we can do better to unify the operational and analytical estates.

Last year, we announced our plan to build a cloud-native Apache Flink® service to meet the growing demand for scalable and efficient stream processing solutions in the cloud. Today, we're thrilled to announce the general availability of Confluent Cloud for Apache Flink across all three major clouds. This means that you can now experience Apache Kafka® and Flink as a unified, enterprise-grade platform to connect and process your data in real time, wherever you need it.

We’re excited to share the latest and greatest features on Confluent Cloud, in our first launch of 2024. This Cloud Launch comes to you from Kafka Summit London, where we talked about the latest updates highlighted in our launch, including serverless Apache Flink®, some exciting pricing changes, updates to connectors, and more! We also shared our vision for a future offering, Tableflow.

In this post, we'll add file upload capabilities to a Phoenix LiveView application and directly upload files to Amazon S3. Without further ado, let's get started!

In iOS, WebSockets enable real-time communication between a client (an iOS app) and a server. Unlike traditional HTTP connections which are stateless, short-lived and request data on demand, WebSockets use a single long-lived connection to send and receive data simultaneously. This significantly reduces response times which is crucial for apps that rely on instant updates and live data to support functions such as chat and multiplayer games.

If you are into programming, you might have used commands like cp, mv, cat, etc, to perform different operations using a text interface like bash or Windows PowerShell. This article discusses implementing command-line applications in Python with functionalities such as keyword arguments, flags, positional arguments, and mode selection. It also discusses how to implement the Linux head command in Python.

In this blog post, explore the unique challenges of Continuous Deployment in native mobile apps, including the complexities of app store distribution and rollback limitations, and discover insights on navigating these hurdles while striving for efficient CI/CD workflows in mobile development.

The first time I learned about snapshot testing was in the context of front-end testing. It made a lot of sense. Writing an assertion-based test to check if a component was correctly rendered as HTML is tricky. And difficulty grows with the complexity of the output. Snapshot testing seemed a reasonable technique to get the job done, even with some caveats.

The editorial team of Hitachi Vantara sat down for an interview with our Chief Product Officer, Octavian Tanase, to learn about his vision and strategy for AI in the enterprise.

In just a few months, enterprise AI has rapidly evolved into a strategic partner for organizations that want to stay ahead of the disruption curve. Whether enterprises are leveraging predictive analytics for strategic decision-making, using machine learning algorithms for supply chain optimization, or applying generative AI and large language models to enhance customer service, it’s clear AI will help business in many ways.