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Scaling PostgreSQL Reads: Implementing Read-Your-Write Consistency Using WAL-Based Replica Routing (Thu, 22 Jan 2026)
At a previous company, we hit a point where our PostgreSQL database was clearly becoming a bottleneck. The primary instance was responsible for every user-facing search request, including some heavy queries from long-time users with years of historical data. CPU usage kept climbing, and before long, we were already running on the largest instance size available. Vertical scaling had officially hit its limit. Naturally, the next step was to introduce read replicas. On paper, it sounded straightforward. In reality, it wasn’t.
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Feature Flags and Safe Rollouts With Azure App Configuration for Large SPA Teams (Thu, 22 Jan 2026)
When a new application starts, everything feels simple: features look straightforward, the architecture is clean, and launch day goes smoothly. Then the real work begins — a steady flow of new features, refactors, and bug fixes. You need to ship critical fixes fast without revealing unfinished pages or risky changes to customers. As the scope grows — multiple teams, shared dependencies, and large features — coordination gets harder. This is where feature flags help. Feature flags reduce risk by decoupling deployment from release. Azure App Configuration and Key Vault let you control rollouts safely, target by tenant/segment, and audit changes — without exposing secrets to the browser.
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Agentic AI with Bedrock and DynamoDB Integration (Thu, 22 Jan 2026)
Introduction Modern banking is rapidly moving toward intelligent, context-aware automation. Instead of relying solely on static rule-based chatbots or hard-coded APIs, today’s systems need to understand intent, reason across multiple data sources, and deliver personalized insights in real time. This is where Agentic AI — autonomous systems capable of planning, reasoning, and taking action — is transforming customer interactions. In this article, we’ll explore how to build a customer service agent that leverages Amazon Bedrock and Amazon DynamoDB, powered by Boto3, to deliver dynamic responses such as:
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Efficient Sampling Approach for Large Datasets (Thu, 22 Jan 2026)
Sampling is a fundamental process in machine learning that involves selecting a subset of data from a larger dataset. This technique is used to make training and evaluation more efficient, especially when working with massive datasets where processing every data point is impractical However, sampling comes with its own challenges. Ensuring that samples are representative is crucial to prevent biases that could lead to poor model generalization and inaccurate evaluation results. The sample size must strike a balance between performance and resource constraints. Additionally, sampling strategies need to account for factors such as class imbalance, temporal dependencies, and other dataset-specific characteristics to maintain data integrity.
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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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