DZone.com Feed

AWS Bedrock vs. SageMaker: Choosing the Right GenAI Stack in 2026 (Thu, 26 Feb 2026)
By 2026, the landscape of Generative AI has shifted from simple prompt engineering to complex agentic workflows, autonomous RAG (Retrieval-Augmented Generation) pipelines, and highly specialized small language models (SLMs). For architects and developers building on Amazon Web Services (AWS), the central question remains: Should you use the managed simplicity of Amazon Bedrock or the granular control of Amazon SageMaker? This article provides a deep-dive technical comparison of these two powerhouses, helping you navigate the trade-offs in performance, cost, and operational overhead.
>> Read More

I Watched an AI Agent Fabricate $47,000 in Expenses Before Anyone Noticed (Thu, 26 Feb 2026)
September 2024. A fintech company in Austin — I can't name them, NDA — invited me to review their AI agent deployment. They'd built an expense processing system that was supposed to handle receipt scanning, categorization, approvals. Worked great in testing. Three months into production, it was generating fake restaurants. Their accountant found it during routine reconciliation. "The Riverside Bistro" at an address that Google Maps showed as a parking garage. "Maria's Taqueria" at a location that had been a Chase Bank for eight years. The agent couldn't parse certain receipt formats — faded thermal prints, handwritten receipts, images with glare. Instead of flagging them for review, it filled in plausible details and moved on.
>> Read More

The Hidden Cost of Custom Logic: A Performance Showdown in Apache Spark (Thu, 26 Feb 2026)
I still remember the first time I killed a production pipeline with a single line of code. I was migrating a legacy ETL job from a single-node Python script to PySpark. The logic involved some complex string parsing that I had already written in a helper function. Naturally, I did what any deadline-pressured engineer would do: I wrapped it in a udf(), applied it to my DataFrame, and hit run. The job, which processed 50 million rows, didn't just run slow — it crawled. What should have taken minutes took hours. I spent the next day staring at the Spark UI, wondering why my 20-node cluster was being outpaced by my laptop.
>> Read More

Terraform AWS Provider Explained Like You’re Five (With Real Code) (Thu, 26 Feb 2026)
Imagine you have a giant box of LEGO. AWS is that giant box full of pieces like servers, databases, networks, buckets, and more. Terraform is like having a magical instruction book that tells AWS exactly what to build for you. But here’s the catch: Terraform can’t talk to AWS directly. It needs a helper, a translator something that understands AWS language. That helper is called the AWS Provider. Without it, Terraform has no idea how to build anything inside AWS.
>> Read More

DevOps Cafe Podcast

DevOps Cafe Ep 79 - Guests: Joseph Jacks and Ben Kehoe (Mon, 13 Aug 2018)
Triggered by Google Next 2018, John and Damon chat with Joseph Jacks (stealth startup) and Ben Kehoe (iRobot) about their public disagreements — and agreements — about Kubernetes and Serverless. 
>> Read More

DevOps Cafe Ep 78 - Guest: J. Paul Reed (Mon, 23 Jul 2018)
John and Damon chat with J.Paul Reed (Release Engineering Approaches) about the field of Systems Safety and Human Factors that studies why accidents happen and how to minimize the occurrence and impact. Show notes at http://devopscafe.org
>> Read More

DevOps Cafe Ep. 77 - Damon interviews John (Wed, 20 Jun 2018)
A new season of DevOps Cafe is here. The topic of this episode is "DevSecOps." Damon interviews John about what this term means, why it matters now, and the overall state of security.  Show notes at http://devopscafe.org
>> Read More