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Zero Trust for Agents: Implementing Context Lineage in the Enterprise Data Mesh (Wed, 28 Jan 2026)
Challenge: When Agentic Bots Become Primary Data Reader In large data platforms, AI agents now execute more data queries than human users. For teams that are running thousands of internal services, it is very common to have hundreds or thousands of agentic bots querying data: a "Supply Chain Optimizer" reading manufacturing logs, a "System Quality Analyst" agent querying usage metrics, or a "Sales Forecaster" aggregating regional sales data, finally passing or interacting with some models. In a decentralized data mesh, domain owners need a way to detect whether an agent that they allowed to read critical data has been altered or compromised since its identity was issued. In such cases, mTLS authenticates the caller service but provides no details about the agent's prior actions or execution context, such as which model or service it is, or what actions it has performed with the data in the past.
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Building an OCR Data Pipeline: From Unstructured Images to Structured Data (Wed, 28 Jan 2026)
The Problem: Unstructured Data Is Everywhere If you've ever tried to pull data out of a scanned document or image, like receipts, invoices, restaurant menus, or even handwritten forms, you know the pain. OCR tools (like Tesseract or AWS Textract) are great at recognizing text, but they just output unstructured chaos. Recently, we faced this problem while extracting restaurant menu data from PDFs and photos. Each menu had a different layout, font, and price format, and what I got back from the OCR models was a wall of unstructured text: random words, misaligned prices — useless for queries, pricing analysis, or downstream systems. 
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The Serverless Ceiling: Designing Write-Heavy Backends With Aurora Limitless (Wed, 28 Jan 2026)
For years, serverless architectures have solved one half of the scalability problem. Compute is no longer the bottleneck. Platforms like AWS Lambda can absorb sudden traffic spikes without advance provisioning. But the moment the compute layer needs to persist data in a relational database, the model starts to strain. Thousands of concurrent functions quickly converge on a single write endpoint, and what looked like elastic scale turns into contention.
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Claude Cowork: AI Agents’ Email Moment for Non-Coders (Wed, 28 Jan 2026)
TL; DR: Claude Cowork  AI agents have long promised productivity gains, but until now, they demanded coding skills that most agile practitioners lack or are uncomfortable with. In this article, I share my first impressions on how Claude Cowork removes that barrier, why it is a watershed moment, and how you could integrate AI Agents into your work as an agile practitioner. Why Claude Cowork Changes How Knowledge Work Will Be Done There are rarely stop-the-press moments in technology. Most “announcements” are incremental improvements dressed up in marketing language. Claude Cowork is different. Anthropic released it on January 12, 2026, and it marks a turning point for how non-developers can work with AI.
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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. 
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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
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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
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