Orchestrating Agentic and Multimodal AI Pipelines with Apache Camel
The key components in the solution include LLM-based reasoning, retrieval-augmented generation (RAG), and image classification.
Grab Redesigns Counter Service Storage for 50% Lower P99 LatencyInfoq
The Async Multiprocessing Has Sound Foundations in Linux, But Further Testing is NeededInfoq
AI Agents with Cloud Credentials Are Outrunning Billing Guardrails Built for Human-Speed MistakesInfoq
How to Develop Software Engineering Skills in the Age of AIInfoq
CodeGuardian: a Model Context Protocol Server for AI-Assisted Code Quality Analysis and SecurityInfoq
Agility and Architecture: Balancing Minimum Viable Product and Minimum Viable ArchitectureInfoq
Explore and Visualize Data the Apache Superset WayThenewstack
Go Concurrency Patterns: Pipelines and cancellation - The Go Programming LanguageGo
Anthropic integration with Modal brings scalable compute to Claude ScienceModal
Hands-on: Create Your First Serverless Application in Apache OpenWhiskThenewstack
4 Ways to Get Your Code Back in Shape After Black FridayThenewstack
What is OCSF and How Do You Implement It?Datadoghq
Gemma 4 on Cerebras—The Fastest Inference is Now MultimodalCerebras
Kubernetes-Run Analytics at the Edge: Postgres, Kafka, DebeziumThenewstack
Bring Your Terraform Estate Into the Agentic EraPulumi
Kimi K3 by Moonshot now available on ModalModal
LLM-driven data pipelines with prompt() in MotherDuck and dbtMotherduck
ZS & Cerebras Set a New Bar in Enterprise Agentic AICerebras
Mastering Docker and Jenkins: Build Robust CI/CD Pipelines EfficientlyDocker
Accent Detection AI: How It Works & When Developers Need ItDeepgram
