Author name: Marcelo Acosta

The AI agent worked perfectly in the demo. It could answer questions, search through documents, and even schedule meetings by talking to Slack. But when the enterprise AI team tried to deploy it for 500 users across multiple departments, everything broke. Authentication failed. Memory leaked between sessions. The integration with Salesforce required custom middleware. Observability […]

The CFO’s question was direct: “Why are we still paying 40% more for database performance we could get cheaper on Graviton?” The engineering team had been putting off the migration for months, citing complexity and uncertainty about .NET compatibility. But the numbers from AWS’s latest Graviton 4 benchmarks made the conversation impossible to avoid. In

The attack happened at 3:17 AM on a Tuesday. A healthcare startup’s AWS root account fell to a sophisticated phishing campaign that bypassed their SMS-based MFA. Within hours, attackers had spun up cryptocurrency mining instances across multiple regions and exfiltrated patient data from their RDS databases. This scenario plays out more often than AWS customers

The notification arrived at 3 AM: “Critical SOC 2 audit finding – unauthorized data access detected.” What started as a routine quarterly review had uncovered a fundamental architectural flaw that threatened the company’s largest enterprise contract. The issue wasn’t a security breach or a failed control—it was an architectural decision made eighteen months earlier that

Machine learning engineers know the frustration well. You’ve spent weeks perfecting a model that achieves impressive accuracy in training, only to discover it crawls when deployed for real-time predictions. The choice becomes stark: accept poor performance or spend months manually optimizing for your target hardware. Amazon SageMaker Neo eliminates this painful trade-off entirely. The service

When nearly half of senior executives admit they can’t see what’s in their software supply chain, we have a problem. A new global survey of 1,500 C-suite and senior executives reveals that 49% lack the visibility needed to understand their software supply chain risks. More troubling: 80% of those with poor visibility experienced a breach

Serverless computing started in the cloud, but it’s not staying there. A recent special issue in Ad Hoc Networks explores how researchers are combining edge computing with serverless architectures, and the results suggest we’re about to see a fundamental shift in how distributed applications work. The research, led by teams from institutions across India, Australia,

The data collaboration problem has always been tricky. Companies want to build better models together, but sharing sensitive customer data feels risky. What if there was a way to train machine learning models on combined datasets without anyone actually seeing the raw data? AWS Clean Rooms ML just added Parquet file format support, and this

When Swami Sivasubramanian stepped onto the AWS Summit New York stage in July 2025, the announcement about Amazon Nova customization through SageMaker seemed like another incremental feature release. But buried within the technical details lies a more significant shift: AWS is democratizing foundation model customization through pre-built recipes, potentially transforming how organizations approach AI model

When Prime Minister Keir Starmer shared the stage with Nvidia CEO Jensen Huang at London Tech Week in June 2025, the symbolism was unmistakable. Britain’s announcement of a £1 billion ($1.34 billion) investment in AI computing infrastructure represents more than national ambition—it signals a fundamental shift in how governments worldwide are approaching the AI hardware