Kubernetes recipes: Maintenance and troubleshooting
Recipes that deal with various aspects of troubleshooting, from debugging pods and containers, to testing service connectivity, interpreting a resource’s status, and node maintenance.
All of our Ideas and Learning material from all of our topics.
Recipes that deal with various aspects of troubleshooting, from debugging pods and containers, to testing service connectivity, interpreting a resource’s status, and node maintenance.
Bitcoin Badness, True Platform, Hardware Details, and Continuous Game of Life
Ben Brown on why messaging design will become as important as responsive design.
One of our goals is to bring Jupyter’s enterprise use cases and practices into one place.
The O’Reilly Data Show Podcast: A special episode to mark the 100th episode.
Successful projects will think seriously about what blockchains mean, and how to use them effectively.
The personal robot temi refactors robotic human behaviors we encounter in the “iPhone Slump,” and moves those back to actual robots.
Biosynthesising Nanomaterials, OS X Age, Debugging Machine Learning, and Deepfake Detection
Mick Hollison, Sven Löffler, and Robert Neumann explain how Deutsche Telekom is harnessing machine learning and analytics in the cloud to build Europe’s largest IoT data marketplace.
Pierre Romera explores the challenges in making 1.4 TB of data securely available to journalists all over the world.
Watch highlights covering machine learning, GDPR, data protection, and more. From the Strata Data Conference in London 2018.
Eva Kaili outlines the fundamentals of GDPR and applications of blockchain.
Jean-François Puget explains why human context should be embraced as a guide to building better and smarter systems.
May 25 is an important day for data protection in the EU and elsewhere. Alison Howard explains how Microsoft has prepared for May 25 and beyond.
It’s time to sort the sheep from the goats, or the willing from the unwilling.
Remote Work, AWS Production Checklist, Proof of Work, and Face Recognition
Don’t pigeonhole blockchain as a technology that’s primarily useful for finance.
The O'Reilly Podcast: Knowing your audience and then appropriately focusing the performance of your application is critical.
Professional Growth, Mental Models, Battleships Over BGP, and Policy Engine
Quantum Computing, E-Waste, Artificial Senses, and Inside printf
Efficient Meetings, Mixed Reality in Unity, Design Power, and AI's Exponential Curve of Cost
Unpacking the complexity of blockchain, term by term.
SEC's ICO, Feeling, Win95 for iOS, and Monocular Performance Capture
Dave Patterson and other industry leaders discuss how MLPerf will define an entire suite of benchmarks to measure performance of software, hardware, and cloud systems.
MLPerf is a new set of benchmarks compiled by a growing list of industry and academic contributors.
Answers to the three most commonly asked questions about maintaining GDPR-compliant machine learning programs.
Paul McAleer discusses practical strategies for designing for mobile.
Right to Repair, Entrepreneurial Privilege, Bash Style, and The Botnet Business Model
O’Reilly Media Podcast: JP Phillips, platform engineer at IBM Cloud, on problem solving with containers and Kubernetes, and how developers can get started.
Data to Sound, Black Mirror, Emulation, and PGP Vulnerability
Learn how to build fast, secure, accessible experiences at the O’Reilly Fluent Conference this June.
A step-by-step guide through the essential ingredients of discovery.
Ridesharing Suburbia, Dunbar's Number, Event Sourcing, and Product Failures
The O’Reilly Podcast: Brendan Eich on disrupting advertising, decentralizing payments, and privacy by design.
The O'Reilly Velocity Conference in San Jose will cover what you need to know to build high-performance, resilient, and secure systems.
Get insights on rebuilding the web, neuroevolution, data engineers vs. data scientists, the blockchain, and design thinking.
Perspectives, hard-earned lessons, and strategies from design leaders offer insight into the inner workings of their paths to success.
Leaked Secrets, WFH Productivity, Developer Growth, and Capture the Flag
The O’Reilly Data Show Podcast: Jason Dai on the first year of BigDL and AI in China.
Game Development, Fake Reviews, Super-Resolution, and Speech Synthesis
Federated load balancing makes hosting resilient applications and operating at scale in the public cloud manageable.
Fact Verification Data Set, Forecasting Software, Image Enhancement, and Effective Teamwork
Infrastructure Testing, Algorithm Check, Parallel Texts, and Dead Pixels
We are likely to see more open interfaces and metaframeworks emerge, but they have their drawbacks.
Why it’s best to keep people’s lifestyles and environment in mind when designing products and devices.
Teaching Programming Languages, Security Training, Manager READMEs, and Digital Expression
There’s no (ethical) way to avoid having the user consciously choose whether or not to act, but products can change the nature of that choice.
Data Science Ethics, Networks and Markets, Chinese Sesame, and Refactoring Into Microservices
The O’Reilly Fluent and Velocity conferences are teaming up to create a unique learning opportunity that addresses the full web experience.
Using machine learning, deep learning, and cognitive computing in concert can help enterprises gain competitive edges.
Privacy-preserving analytics is not only possible, but with GDPR about to come online, it will become necessary to incorporate privacy in your data products.
MySQL Migrations, 3D Faces, Economics of Privacy, and Peter Principle
Get a basic overview of machine learning and then go deeper with recommended resources.
George Church discusses the IARPA MICrONS project, which aims to revolutionize machine learning by reverse-engineering the algorithms of the brain.
Ron Bodkin explains what a tensor is and why you should care.
Thomas Reardon offers an overview of brain-machine interface (BMI) technology and shares CTRL-Labs’s transformative and noninvasive neural interface approach.
Dario Gil explores state-of-the-art computing for AI as it exists today as well as an innovation that will lead us into the decades to come: quantum computing for AI.
Abhijit Deshpande explains how to use machine learning to identify root causes of problems in minutes instead of hours.
Meihong Wang explains how Facebook thinks about personalization and how the company uses machine learning to provide personalized experiences.
Olga Russakovsky explains how her organization, AI4ALL, aims to increase diversity and inclusion in AI development and research.