Learn how open-source BI tools transform and improve DevOps pipelines by enhancing data visibility, automation, and collaboration for streamlined workflows.
Applications that are unable to publish messages to a Kafka topic or be consumed by downstream applications are considered to be experiencing an outage.
Explore rapid prototyping with GPT and custom BERT fine-tuning to extract targeted sentiment insights for nuanced text analysis and business applications.
AI has been improving learning management system development and producing more interesting and productive learning environments for contemporary students.
This article provides steps and scripts to apply permissions at the Unity Catalog table level, reducing manual effort related to permissions at table level.
This article explores different caching strategies, such as in-memory, distributed, and hybrid approaches, for optimizing performance in microservices or mono.
jMolecules uses annotations to enforce architectural rules, prevent software erosion, and simplify validation with tools like ArchUnit. It supports DDD, CQRS, and more.
A simple experiment with multiple collaborative AI Agents interacting via group chat to produce solutions architectures based on business requirements.
Using LSTM machine learning models for PostgreSQL databases can effectively predict resource usage, helping to prevent bottlenecks and improve efficiency.
Discover an OOP approach to effectively separate data from domain-specific logic in data-oriented programming, utilizing the Java Class Extension Library.
Learn what distributed parallel processing is and how to achieve it with Ray using KubeRay in Kubernetes to handle large-scale, resource-intensive tasks.
Learn about Interfaces and Unions in GraphQL, key concepts that simplify API development by allowing flexible data querying and improving query efficiency.
Use Dust Java Actors to create a pipeline that automatically finds, reads, and extracts specific info from news articles based on your topic of interest.
Let's discuss the multiple advantages of using cloud computing for big data processing, from scalability to cost-effectiveness and enhanced collaboration.
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