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Tired of Reverse-Engineering Code? A Data-First Pattern for Legacy Modernization (Fri, 02 Jan 2026)
We have all faced the Monolith from Hell. It’s a 20-year-old system. The documentation is missing, the original architects retired a decade ago, and the codebase is a tangled mess of spaghetti logic. When tasked with modernizing such a system, the instinct is a function-first approach: read the source code, trace the logic, and try to replicate the existing functionality in a modern language.
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AutoML vs. LLMs: A Developer’s Guide to Efficient ML Pipeline Generation (Fri, 02 Jan 2026)
In the current AI landscape, the hype cycle is undeniably focused on large language models (LLMs). From code generation to reasoning, models like GPT-4 and Llama 3 have transformed how we interact with data. However, for machine learning (ML) engineers tasked with building robust, production-grade pipelines for tabular data or predictive analytics, LLMs are not always the silver bullet. Automated Machine Learning (AutoML) has quietly matured into a powerhouse technology, automating the tedious aspects of data science — feature engineering, model selection, and hyperparameter tuning.
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Cloud to Local Copilots: A Hybrid Path to Privacy and Control (Fri, 02 Jan 2026)
Software usage patterns have always evolved alongside hardware capabilities. In recent years, with the rise of GPUs and cloud-based AI copilots such as GitHub Copilot, this evolution has accelerated — offering developers real-time code suggestions, documentation support, and automated testing at scale. However, concerns around personal data privacy, the cost of copilot usage, and the need for greater autonomy have given rise to local AI copilots. By hosting models on a local device, developers gain tighter control over sensitive data, reduce dependency on cloud providers, and unlock performance benefits tailored to their device’s capabilities. Cloud Copilots vs. Local Copilots Cloud-based copilots have become the default entry point for many developers, especially in workplace settings, offering seamless integration with cloud-hosted repositories and services. However, there are trade-offs — namely recurring subscription costs and potential exposure of sensitive code or data.
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5 Challenges and Solutions in Mobile App Testing (Fri, 02 Jan 2026)
Testing is one of the final stages of mobile app development before you’re ready for launch. The finish line may seem close, but it might not be. If you encounter mobile app testing challenges unprepared, you may have to push your launch window back by days or even weeks. Here’s why mobile app testing is essential, the challenges you might encounter, and how to resolve them. The Importance of Mobile App Testing  The mobile app market is booming. By 2026, the Apple App Store is expected to see an estimated 38 billion downloads, while projections indicate the Google Play Store will reach approximately 143 billion downloads — representing 15% and 30% increases, respectively. Competition is intense, so you must prioritize comprehensive testing to attract and retain an audience.
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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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