Resultaten voor 'richard murphy'

1. Betsy , Beyer
2. Chris , Jones
3. Christof , Leng

Site Reliability Engineering

Google pioneered the discipline of Site Reliability Engineering, applying reliability to the entire user journey for consumer, enterprise, and infrastructure systems. In the years since, many organizations have followed suit, guided by the tenets laid out in this practical book. This fully revised edition brings Site Reliability Engineering up-to-date with fresh insights on engineering techniques, organizational processes, and case studies that will help you promote and implement greater reliability throughout the engineering lifecycle. In this collection of essays and articles, key members of Google's Site Reliability Engineering team explore the company's current SRE practices and explain how they've evolved in the decade since the initial publication. New updates cover the value of reliability, cloud reliability, and the impact of AI. You'll learn the principles and practices that enable Google engineers to make some of the world's largest systems scalable, reliable, and efficient--lessons directly applicable to your organization. Train new Site Reliability Engineers based on the latest practices in the field Develop engineering organizations that support reliability as a feature Build online services that incorporate reliability principles Use AI to improve SRE across the organization and optimize critical areas such as automation and incident detection

1. Richard Murphy

THE ULTIMATE COFFE RECIPES COOKBOOK IN LESS THAN 5 MINUTES

Why do we love coffee so much? Well, apart from the fact that it's super delicious!A steaming cup of coffee is the first thing millions of people reach for every morning and there are a multitude of reasons these people do so on a daily basis. The caffeine in it plays two roles in why people drink coffee. First, the caffeine in coffee helps to get people' blood moving and makes them feel energized. Early morning workers tend to rely on their coffee to help them get through their work day.The other reason caffeine is a reason that people drink coffee is that it is addictive. There are many chemicals in coffee that lend to its addictive properties and caffeine is the main one. Caffeine withdrawal can cause headaches and irritability and many people prefer not to give up their coffee.Coffee has become a very social drink similar in popularity to alcohol. Mornings at the local coffee shop are the place to hang out with friends or meet to discuss business. People tend to drink coffee at these gatherings whether or not they like it which eventually helps them to develop a taste for it and then it becomes addictive.Coffee drinkers say they drink coffee to relax. While this may seem like an oxymoron considering that coffee is a stimulant, a hot cup of decaffeinated coffee or, for some people, even regular coffee can relax the senses and help them wind down and calm their nerves. Researchers attribute the calming effect to the stimulation of the senses which aids in creativity and mental stimulus which in turn helps calm some people down.

1. Cathy , Chen
2. D. , Sculley
3. Kranti , Parisa

Reliable Machine Learning

Whether you're part of a small startup or a multinational corporation, this practical book shows data scientists, software and site reliability engineers, product managers, and business owners how to run and establish ML reliably, effectively, and accountably within your organization. You'll gain insight into everything from how to do model monitoring in production to how to run a well-tuned model development team in a product organization. By applying an SRE mindset to machine learning, authors and engineering professionals Cathy Chen, Kranti Parisa, Niall Richard Murphy, D. Sculley, Todd Underwood, and featured guest authors show you how to run an efficient and reliable ML system. Whether you want to increase revenue, optimize decision making, solve problems, or understand and influence customer behavior, you'll learn how to perform day-to-day ML tasks while keeping the bigger picture in mind. You'll examine: What ML is: how it functions and what it relies on Conceptual frameworks for understanding how ML "loops" work How effective productionization can make your ML systems easily monitorable, deployable, and operable Why ML systems make production troubleshooting more difficult, and how to compensate accordingly How ML, product, and production teams can communicate effectively

The Site Reliability Workbook

An expansion on the understanding of Google SRE, providing 'worked examples' for each essential facet of this area of IT prepared in co-operation with Google cloud customers based on their experiences. Instructs on methodology for running services at scale and starting SRE in greenfield or brownfield fashion.