360SOFTY

Insights

Engineering Insights

Practical writing on software architecture, SaaS products, AI automation, legacy modernisation, and the business of building reliable systems.

RSS

Curated links from external sources — not 360Softy original articles.

ExternalDevOps
Kubernetes Blog

Kubernetes v1.36: Advancing Workload-Aware Scheduling

AI/ML and batch workloads introduce unique scheduling challenges that go beyond simple Pod-by-Pod scheduling. In Kubernetes v1.35, we introduced the first tranche of workload-aware scheduling improvements, featuring the foundational Workload API alongside basic gang scheduling support built on a Pod-based framework, and an opportunistic batching feature to efficiently process identical Pods. Kubernetes v1.36 introduces a significant architectural evolution by cleanly separating API concerns: the

Kubernetes BlogRead original
ExternalAI
AWS Machine Learning Blog

Build financial document processing with Pulse AI and Amazon Bedrock

This post demonstrates how to build a documentation extraction and model fine-tuning pipeline that addresses challenges when processing the complex financial documents. By combining Pulse AI's advanced document understanding capabilities with the powerful AI services of Amazon Bedrock, organizations can achieve enterprise-grade accuracy and extract contextually relevant financial insights at scale.

Amazon BedrockAmazon Simple Storage Service (S3)Artificial Intelligence
AWS Machine Learning BlogRead original
ExternalAI
NVIDIA Technical Blog

Transform Video Into Instantly Searchable, Actionable Intelligence with AI Agents and Skills

In today’s data-driven world, organizations increasingly rely on video to capture critical information, yet extracting meaningful, real-time insights from... In today’s data-driven world, organizations increasingly rely on video to capture critical information, yet extracting meaningful, real-time insights from massive amounts of footage remains a challenge. NVIDIA Metropolis Blueprint for video search and summarization (VSS) overcomes this hurdle by transforming millions of live video streams o

NVIDIA Technical BlogRead original
ExternalAI
AWS Machine Learning Blog

Build real-time voice streaming applications with Amazon Nova Sonic and WebRTC

Building end-to-end live streaming applications with real-time voice interaction presents several challenges. This post introduces a solution based on Amazon Nova 2 Sonic (Nova Sonic) and Amazon Kinesis Video Streams WebRTC (WebRTC) that addresses these challenges. In this post, we’ll walk through the solution architecture, implementation patterns, and two real-world scenario examples.

Amazon NovaAWS IoT CoreIntermediate (200)
AWS Machine Learning BlogRead original
ExternalDatabase
AWS Database Blog

Zero-downtime DynamoDB construct migration: from Table to TableV2 with cdk orphan

In this post, we show you how to use the new cdk orphan command to safely migrate a DynamoDB table from the Table construct to TableV2 with zero downtime. Your data stays intact, streams keep flowing, and your application remains available throughout the process.

Advanced (300)Amazon DynamoDBAWS Cloud Development Kit
AWS Database BlogRead original
ExternalAI
AWS Machine Learning Blog

Securing AI agents: How AWS and Cisco AI Defense scale MCP and A2A deployments

The Cisco and AWS partnership addresses three challenges enterprises face when scaling AI agents: visibility gaps, security bottlenecks, and compliance risks. In this post, we explore how you can overcome AI security challenges through automated scanning and unified governance.

Customer Solutions
AWS Machine Learning BlogRead original
ExternalAI
AWS Machine Learning Blog

Fine-tune LLM with Databricks Unity Catalog and Amazon SageMaker AI

In this post, we demonstrate how to build a secure, complete LLM fine-tuning workflow that integrates Unity Catalog with Amazon SageMaker AI using Amazon EMR Serverless for preprocessing. The solution shows how to securely access governed data, maintain lineage across services, fine-tune the Ministral-3-3B-Instruct model, and register trained artifacts back into Unity Catalog. With this approach, you can continue using your existing services while preserving central governance, tracking data lin

Advanced (300)Amazon SageMaker AIArtificial Intelligence
AWS Machine Learning BlogRead original

Work with 360Softy

Building a SaaS product, AI system, or business platform?

Book a free consultation and we will tell you honestly whether we can help.