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FinOps and GreenOps offer a well-defined path to more efficient use of cloud resources and lower environmental impact. Join us in Bristol on 30 October to see how we can get control over what cloud is costing us and how we can limit its climate impact.

Hosted by Just Eat in Bristol, this Meetup will look at practical ways we can control how we use cloud to maximise its benefits and minimise the problems

Here's the agenda: 5:00 pm Reception 5:30 pm Introduction & Welcome 5:40 pm Keynote Address "What shall we do about Cloud Waste?" - Mike Bradbury\, FinOps Certified Professional 6:00 pm 5-minute Lightning talks from industry experts: - Ben Percy\, Just Eat - Andy Foley\, Nationwide BS - Mark Wilson\, Walgreens-Boots Alliance - Greg Holmes\, Apptio - Kevin Barnes\, Version1 6:45 pm Interactive Breakout Sessions 7:15 pm Informal networking

FinOps and GreenOps in the South West
Big Data 2015-04-30
James Warren – author , Nathan Marz – author

Big Data teaches you to build big data systems using an architecture that takes advantage of clustered hardware along with new tools designed specifically to capture and analyze web-scale data. It describes a scalable, easy-to-understand approach to big data systems that can be built and run by a small team. Following a realistic example, this book guides readers through the theory of big data systems, how to implement them in practice, and how to deploy and operate them once they're built. About the Technology About the Book Web-scale applications like social networks, real-time analytics, or e-commerce sites deal with a lot of data, whose volume and velocity exceed the limits of traditional database systems. These applications require architectures built around clusters of machines to store and process data of any size, or speed. Fortunately, scale and simplicity are not mutually exclusive. Big Data teaches you to build big data systems using an architecture designed specifically to capture and analyze web-scale data. This book presents the Lambda Architecture, a scalable, easy-to-understand approach that can be built and run by a small team. You'll explore the theory of big data systems and how to implement them in practice. In addition to discovering a general framework for processing big data, you'll learn specific technologies like Hadoop, Storm, and NoSQL databases. What's Inside Introduction to big data systems Real-time processing of web-scale data Tools like Hadoop, Cassandra, and Storm Extensions to traditional database skills About the Reader This book requires no previous exposure to large-scale data analysis or NoSQL tools. Familiarity with traditional databases is helpful. About the Authors Nathan Marz is the creator of Apache Storm and the originator of the Lambda Architecture for big data systems. James Warren is an analytics architect with a background in machine learning and scientific computing. Quotes Transcends individual tools or platforms. Required reading for anyone working with big data systems. - Jonathan Esterhazy, Groupon A comprehensive, example-driven tour of the Lambda Architecture with its originator as your guide. - Mark Fisher, Pivotal Contains wisdom that can only be gathered after tackling many big data projects. A must-read. - Pere Ferrera Bertran, Datasalt The de facto guide to streamlining your data pipeline in batch and near-real time. - Alex Holmes, Author of "Hadoop in Practice"

data data-engineering AI/ML Analytics AWS Lambda Big Data Cassandra Hadoop NoSQL
Alex Holmes – author

Hadoop in Practice collects 85 Hadoop examples and presents them in a problem/solution format. Each technique addresses a specific task you'll face, like querying big data using Pig or writing a log file loader. You'll explore each problem step by step, learning both how to build and deploy that specific solution along with the thinking that went into its design. As you work through the tasks, you'll find yourself growing more comfortable with Hadoop and at home in the world of big data. About the Technology Hadoop is an open source MapReduce platform designed to query and analyze data distributed across large clusters. Especially effective for big data systems, Hadoop powers mission-critical software at Apple, eBay, LinkedIn, Yahoo, and Facebook. It offers developers handy ways to store, manage, and analyze data. About the Book Hadoop in Practice collects 85 battle-tested examples and presents them in a problem/solution format. It balances conceptual foundations with practical recipes for key problem areas like data ingress and egress, serialization, and LZO compression. You'll explore each technique step by step, learning how to build a specific solution along with the thinking that went into it. As a bonus, the book's examples create a well-structured and understandable codebase you can tweak to meet your own needs. What's Inside Conceptual overview of Hadoop and MapReduce 85 practical, tested techniques Real problems, real solutions How to integrate MapReduce and R About the Reader This book assumes you've already started exploring Hadoop and want concrete advice on how to use it in production. About the Author Alex Holmes is a senior software engineer with extensive expertise in solving big data problems using Hadoop. He has presented at JavaOne and Jazoon and is a technical lead at VeriSign. Quotes Interesting topics that tickle the creative brain. - Mark Kemna, Brillig Ties together the Hadoop ecosystem technologies. - Ayon Sinha, Britely Comprehensive … high-quality code samples. - Chris Nauroth, The Walt Disney Company Covers all of the variants of Hadoop, not just the Apache distribution. - Ted Dunning, MapR Technologies Charts a path to the future. - Alexey Gayduk, Grid Dynamics

data data-engineering Hadoop Big Data
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