Systems | Development | Analytics | API | Testing

Using Apache Flink for Model Inference: A Guide for Real-Time AI Applications

As real-time data processing becomes a cornerstone of modern applications, the ability to integrate machine learning model inference with Apache Flink offers developers a powerful tool for on-demand predictions in areas like fraud detection, customer personalization, predictive maintenance, and customer support. Flink enables developers to connect real-time data streams to external machine learning models through remote inference, where models are hosted on dedicated model servers and accessed via APIs.

Best Open Source LLMs in 2025

Open source LLMs continue to compete with proprietary models on performance benchmarks for natural language tasks like text generation, code completion, and reasoning. Despite having fewer resources than closed models, these open LLMs offer cutting-edge AI without the high costs and restrictions of proprietary models. However, running these open-source models in production and at scale remains a challenge.

Your Enterprise Data Needs an Agent

Snowflake is expanding its AI capabilities with the public preview of Cortex Agents, to help retrieve data insights by orchestrating across structured and unstructured datasets. Cortex Agents streamlines agentic application data access and orchestration for more reliable AI-driven decisions by building on top of enhancements to our Cortex AI retrieval services.

How to Run an Automated CI/CD Workflow for ML Models with ClearML

If you are working with ML models, having a reliable CI/CD (Continuous Integration and Continuous Deployment) workflow isn’t just a nice-to-have, it’s essential. Your team needs a robust, automated process to validate data, train models, and deploy them without human error slowing things down. That’s where ClearML comes in, offering a seamless solution to orchestrate, monitor, and automate your ML pipelines.

Building High Throughput Apache Kafka Applications with Confluent and Provisioned Mode for AWS Lambda Event Source Mapping (ESM)

Confluent and AWS Lambda can be used to build scalable and real-time event-driven architectures (EDAs) that respond to specific business events. Confluent provides a streaming SaaS solution based on Apache Kafka and built on Kora: The Cloud-Native Engine for Apache Kafka, allowing you to focus on building event-driven applications without operating the underlying infrastructure.

How to Choose a Tech Stack for Mobile App Development

Mobile apps have become an essential part of daily life. You need a mobile application for almost everything these days. Investing in mobile app development makes sense as an entrepreneur or business owner. However, developing a successful mobile application requires making smart technical decisions from the start. Choosing the tech stack is a significant activity during the mobile app development process. A tech stack is a suite of tools and technologies you can use to develop a mobile app.

Lenses.io Introduces Streaming Data Replicator

New York City, US - February 12, 2025 - Lenses.io, a data streaming innovation leader whose software helps developers power the world’s largest businesses, today announces the development of an enterprise grade and vendor-agnostic Kafka-to-Kafka replicator. It will enable organizations to share streaming data across different domains, in order to keep up with real-time data demands as AI adoption grows.

The Hidden Cost of AI Efficiency

AI is changing the way developers and writers work, but not always in the ways we expected. Here’s what’s really happening in 2025: Developers are now spending more time reviewing AI-generated code than writing it. Faster isn’t always better. Writers who used to rely on peer feedback are getting instant AI edits—but at the cost of real collaboration. AI is a powerful tool, but it’s shifting roles instead of eliminating work. The question isn’t if you use AI, it’s how you integrate it.

EP 10: 2025 Predictions

What’s the Forecast? A look at data and AI in 2025 2025 is set to be a year of growth and change, particularly in the AI space. Over the last couple of years, AI has evolved from a niche technology to a driving force behind business strategies, innovation, and efficiency in almost every industry. Its impact is felt far and wide. It is not only shaping how we search for information, but how we digest and react to the world around us.