Understanding how the Kubernetes scheduler makes scheduling decisions is critical to ensure consistent performance and optimal resource utilization.
Crystal Hirschorn discusses how organizations can benefit from combining established tech practices with incident planning, post-mortem-driven development, chaos engineering, and observability. Watch highlights from expert talks covering Kubernetes, chaos engineering, deep learning, and more. Anne Currie says excessive and dirty energy use in data centers is one of the biggest ethical issues facing the tech industry.
Mike Roberts explores ideas for trying serverless as well as a framework for evaluating its effectiveness within your organization. Stefan Tilkov looks at common software architecture pitfalls and explains how they can be avoided. Trisha Gee shares advice and lessons she learned the hard way while managing her career as a developer, lead, and technical advocate. Liz Rice outlines the security implications of microservices, containers, and serverless. Sarah Wells explains how the Financial Times migrated microservices between container stacks without affecting production users.
Watch highlights from expert talks covering microservices, Kubernetes, serverless, and more. Alon Kaufman on the interplay between machine learning, encryption, and security. As lists are the raw material of strategy and technology architecture, MECE list-making is one of the most useful tools you can have in your tool box.
A look at the roles of architect and strategist, and how they help develop successful technology strategies for business. Our most-used Python resources will help you stay on track in your journey to learn and apply Python.
Create a coherent BI strategy that aligns data collection and analytics with the general business strategy. This collection of serverless resources will get you up to speed on the basics and best practices. Supasorn Suwajanakorn discusses the possibilities and the dark side of building artificial people. Kristian Hammond maps out simple rules, useful metrics, and where AI should live in the org chart. Jason Knight offers an overview of the state of the field for scaling training and inference across distributed systems.
Cassie Kozyrkov shares machine learning lessons learned at Google and explains what they mean for applied data science. Jacob Ward on the interplay between psychology, decision-making, and AI systems. Ben Lorica and Roger Chen highlight recent trends in data, compute, and machine learning. Ashok Srivastava draws upon his cross-industry experience to paint an encouraging picture of how AI can solve big problems.
Watch highlights from expert talks covering artificial intelligence, machine learning, automation, and more. Yangqing Jia talks about what makes AI software unique and its connections to conventional computer science wisdom. Ian Massingham discusses the application of ML and AI within Amazon, from retail product recommendations to the latest in natural language understanding.
Amy Heineike explains how Primer created a self-updating knowledge base that can track factual claims in unstructured text. A new report examines the state of infrastructure and anticipated near-term developments through the eyes of infrastructure experts. Michael Bernstein offers an unflinching look at some of the fallacies that developers believe about marketing.
Tammy Butow explains how companies can use Chaos Days to focus on controlled chaos engineering. Jaana Dogan explains why Google teaches its tracing tools to new employees and how it helps them learn about Google-scale systems end to end. Roger Magoulas shares insights from O'Reilly's online learning platform that point toward shifts in the systems engineering ecosystem. Practical techniques to ensure developers can actually do the things you want them to do using your API.
What is neural architecture search? Deep automation in machine learning We need to do more than automate model building with autoML; we need to automate tasks at every stage of the data pipeline. A quick and simple definition Get a basic understanding of distributed systems and then go deeper with recommended resources.
Survey reveals the opportunities and realities of microservices A new report explores how far companies have come with microservices. Managing risk in machine learning Considerations for a world where ML models are becoming mission critical.
Kubernetes' scheduling magic revealed Understanding how the Kubernetes scheduler makes scheduling decisions is critical to ensure consistent performance and optimal resource utilization. What changes when we go offline-first? The misinformation age Jane Adams examines the ways data-driven recruiting fails to achieve intended results and perpetuates discriminatory hiring practices. The freedom of Kubernetes Kris Nova looks at the new era of the cloud native space and the kernel that has made it all possible: A new vision for the global brain: Deep learning with people instead of machines Omoju Miller outlines a vision where we harness human action for a better future.
Incognito mentorship Katrina Owen says the valuable skills that experienced professionals lack are at the vital margins of their careers. Deriving meaning in a time of chaos: The intersection between chaos engineering and observability Crystal Hirschorn discusses how organizations can benefit from combining established tech practices with incident planning, post-mortem-driven development, chaos engineering, and observability. Highlights from the O'Reilly Velocity Conference in London Watch highlights from expert talks covering Kubernetes, chaos engineering, deep learning, and more.
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