GCP Cloud Foundations #Whoami
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Understanding the Value of Arts & Culture | the AHRC Cultural Value
Understanding the value of arts & culture The AHRC Cultural Value Project Geoffrey Crossick & Patrycja Kaszynska 2 Understanding the value of arts & culture The AHRC Cultural Value Project Geoffrey Crossick & Patrycja Kaszynska THE AHRC CULTURAL VALUE PROJECT CONTENTS Foreword 3 4. The engaged citizen: civic agency 58 & civic engagement Executive summary 6 Preconditions for political engagement 59 Civic space and civic engagement: three case studies 61 Part 1 Introduction Creative challenge: cultural industries, digging 63 and climate change 1. Rethinking the terms of the cultural 12 Culture, conflict and post-conflict: 66 value debate a double-edged sword? The Cultural Value Project 12 Culture and art: a brief intellectual history 14 5. Communities, Regeneration and Space 71 Cultural policy and the many lives of cultural value 16 Place, identity and public art 71 Beyond dichotomies: the view from 19 Urban regeneration 74 Cultural Value Project awards Creative places, creative quarters 77 Prioritising experience and methodological diversity 21 Community arts 81 Coda: arts, culture and rural communities 83 2. Cross-cutting themes 25 Modes of cultural engagement 25 6. Economy: impact, innovation and ecology 86 Arts and culture in an unequal society 29 The economic benefits of what? 87 Digital transformations 34 Ways of counting 89 Wellbeing and capabilities 37 Agglomeration and attractiveness 91 The innovation economy 92 Part 2 Components of Cultural Value Ecologies of culture 95 3. The reflective individual 42 7. Health, ageing and wellbeing 100 Cultural engagement and the self 43 Therapeutic, clinical and environmental 101 Case study: arts, culture and the criminal 47 interventions justice system Community-based arts and health 104 Cultural engagement and the other 49 Longer-term health benefits and subjective 106 Case study: professional and informal carers 51 wellbeing Culture and international influence 54 Ageing and dementia 108 Two cultures? 110 8. -
Coursera Machine Learning Andrew Ng Assignment Solution
Coursera Machine Learning Andrew Ng Assignment Solution Compartmentalized Rey nichers something, he blackbirds his pigmentation very depreciatingly. Todd sibilated acquiescingly if one Duncan interveins or reticulating. Hamel deplane viperously? But you will walk you can ask doubts of them mere hours per week that machine coursera learning andrew solution assignment solutions of certain exercises according In contrast, we can use variants of gradient descent and other optimization methods to scale to data sets of unlimited size, so for machine learning problems this approach is more practical. In my case the support was fantastic! Machine Learning Coursera second week assignment solution. Big Data Specialization from University of California San Diego is an introductory learning path for the Big Data world. Not be able to see solutions for the weekly assignments throughout the course we have to go through quiz. One of the most highly sought after skills in tech see solutions all. Google searches to figure out some of the individual things that you need to do. Recommend only one course of machine learning problem in order to apply the appropriate set of. Notes, programming assignments and quizzes from all courses within the Coursera Deep Learning specialization offered by deeplearning. What does the chemist obtains the coursera machine learning andrew ng assignment solution assignment is my knowledge within those languages? Will need to use Octave or MATLAB is just only one problem of the code for imports data! If you are caught cheating, your Coursera account will be deactivated and certificates voided. The classifier is likely to now have higher precision. -
Author Hub Google Hangout Tips for Engaging with Readers and Making Yourself More Discoverable Author Hub Google Hangout 2/19
Author Hub Google Hangout Tips for engaging with readers and making yourself more discoverable Author Hub Google Hangout 2/19 Panellists Amy Watson: Brand Development and Market Analysis Marketing Executive at Cambridge University Press Andrew Martin: Senior Inbound Marketing Executive at Cambridge University Press Sue Keogh: founder of Sookio – a Cambridge-based business offering copy writing, web content and social media services to clients. Sue also runs regular workshops for writing for the web and social media and sharing practical tips on engaging audiences. For more information, please visit: www.sookio.com Ashley Hewitt: Account Manager for Zazzle Media – a creative digital marketing agency that offers a variety of services including content strategy, digital PR, search engine optimisation (SEO) and data insight to help drive audience growth. For more information, please visit: www.zazzlemedia.co.uk Author Hub Google Hangout 3/19 Questions Covered in this Session: Q1. Why should I use social media as an author, and how does it allow me to engage with readers? Watch the video Q2. I don’t feel comfortable using social media as a way of selling my book so how else can I use it as a way to market myself and my work? Watch the video Q3. What are the differences between the main online tools authors can use to engage with readers, both in terms of audiences and control over content? Watch the video Q4. What advice can you give me in terms of adding content to my website and keeping it updated to engage readers? Watch the video Q5. -
COMMUNICATOR the Journal of Indian Institute of Mass Communication Volume LIII, Number-4, October-December, 2018 ISSN: 0588-8093 Message from Editor-In-Chief
COMMUNICATOR The Journal of Indian Institute of Mass Communication Volume LIII, Number-4, October-December, 2018 ISSN: 0588-8093 Message From Editor-in-Chief At the outset, I wish to express my gratitude to all the academicians and scholars who participated and presented papers at the National Seminar on “The State of Indian Language Journalism and Training” organised by IIMC with support from Indian Council of Social Sciences and Research (ICSSR) on October, 29 and 30, 2018 at IIMC Campus. K. G. Suresh The conference was organised to Editor-in-Chief commemorate the silver jubilee of Director General, IIMC our Eastern Regional Campus at Dhenkanal, Odisha from where we started our first language journalism programme in Odia. In the last three years, we have given a major push to language journalism launching a Malayalam Journalism programme at our Kottayam, Kerala campus and Marathi Journalism programme at Amravati, Maharashtra campus. This apart, we have upgraded the Certificate programme in Urdu Journalism to a full fledged Diploma programme. We have even started a three months Advanced Certificate Programme in Sanskrit Journalism in collaboration with the Shri Lal Bahadur Shastri Rashtriya Sanskrit Vidyapeeth besides setting up the Department of Indian Language Journalism. Future plans include starting Hindi and Urdu Journalism programmes from our Jammu campus and Bangla from our Odisha campus. Apart from the papers presented at the conference, many eminent academicians have also contributed to this volume. I am confident that this special issue on the state of Indian language journalism and training would be a collector’s issue for both students and scholars as also media persons across the country and would help them in better understanding of the issues at stake and take requisite steps to improve the quality and standard of both language journalism and training at a time when language journalism is growing by leaps and bounds. -
State of 2017
STATE OF MODERN APPLICATIONS IN THE CLOUD 2017 Introduction — The Rise of Modern Applications What is the Modern Application? Today’s leading enterprises are striving to deliver high performance, highly scalable and always-on digital services. These services are built on custom “modern architectures” – an application stack with new tiers, new technologies, microservices and typically running on cloud platforms like Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform, etc. What does this report provide? The goal of this report is to provide data-driven insights, best practices and trends by analyzing technology adoption among Sumo Logic customers who run massive mission-critical modern applications on cloud platforms like AWS, Azure, and Google Cloud. Who should read this report? Cloud architects, Operations, DevOps and Security leaders and practitioners should leverage the learnings from this report to build, operate and secure modern applications effectively. Data Methodology and Assumptions • This data is derived from 1500+ Sumo Logic customers running applications on cloud platforms like AWS, Azure, Google Cloud, etc. All customer specific data is anonymized. • Customers use Sumo Logic to manage production applications and underlying infrastructure. Hence, this report provides a snapshot of the production application state. • The Sumo Logic analytics service runs on AWS. The experience and expertise of running this mission critical and massive service is also leveraged in this report. This report assumes that an app or -
2013 State of Media
UNDERSTANDING GROWTH TARGETING THE NEW MOBILE AUDIOAND FRAGMENTATION 26 CONSUMER82 STATE OF MEDIA 2013 ANALYTICS DEATH OF BIG DATA, RISE OF SMART DATA 68 ESPN: End of an Empire? 34 02 VIDEO EVERYWHERE FACT, FICTION & FUTURE Letter from the President For me, working in the discussions that will continue this industry has to drive growth and progress. always been an exciting adventure. Offline and online are cohabitating It still is to this now more than ever to earn day. Nevertheless, viewers’ time, so let’s examine the continuous shakeup of content and provider advancements models. Today technologies like in the media Dish Network’s Hopper and landscape Aereo (page 6) are stirring the can make pot, but tomorrow, who knows? our jobs and the task of tracking I also happen to be a tablet addict, trends a challenging endeavor. so it’s been enjoyable to see my These rapid changes are what favorite magazines adapting to the encouraged us to write our very ever-increasing push for crossover first STATE OF MEDIA (SOM) content (page 22). This process has four years ago, and I am proud to already made for some truly creative say our mission to keep business uses of the medium and I can’t wait partners, clients, new friends and to see what’s next. Again, it all ourselves informed has successfully reminds me that we should dispel continued to this day. Now, just the premonitions and instead look like the industry in which we work, at the opportunities a more unified KSM is evolving our publication media ecosystem will produce. -
Understanding Log Analytics at Scale O'reilly Report | Pure Storage
C om p lim e nt s of SECOND EDITION Understanding Log Analytics at Scale Log Data, Analytics & Management Matt Gillespie & Charles Givre REPORT SECOND EDITION Understanding Log Analytics at Scale Log Data, Analytics, and Management Matt Gillespie and Charles Givre Beijing Boston Farnham Sebastopol Tokyo Understanding Log Analytics at Scale by Matt Gillespie and Charles Givre Copyright © 2021 O’Reilly Media, Inc.. All rights reserved. Printed in the United States of America. Published by O’Reilly Media, Inc., 1005 Gravenstein Highway North, Sebastopol, CA 95472. O’Reilly books may be purchased for educational, business, or sales promotional use. Online editions are also available for most titles (http://oreilly.com). For more infor‐ mation, contact our corporate/institutional sales department: 800-998-9938 or [email protected]. Acquisitions Editor: Jessica Haberman Proofreader: Abby Wheeler Development Editor: Michele Cronin Interior Designer: David Futato Production Editor: Beth Kelly Cover Designer: Randy Comer Copyeditor: nSight, Inc. Illustrator: Kate Dullea May 2021: Second Edition February 2020: First Edition Revision History for the Second Edition 2021-05-05: First Release The O’Reilly logo is a registered trademark of O’Reilly Media, Inc. Understanding Log Analytics at Scale, the cover image, and related trade dress are trademarks of O’Reilly Media, Inc. The views expressed in this work are those of the authors, and do not represent the publisher’s views. While the publisher and the authors have used good faith efforts to ensure that the information and instructions contained in this work are accurate, the publisher and the authors disclaim all responsibility for errors or omissions, including without limitation responsibility for damages resulting from the use of or reliance on this work. -
Gigaom Radar for Cloud Observability V1.0
MARKET RADAR GigaOm Radar for Cloud Observability v1.0 ANDY THURAI | FEB 26, 2021 - 10:57 AM CST TOPIC: CLOUD INFRASTRUCTURE CREDIT: BAGOTAJ GigaOm Radar for Cloud Observability TABLE OF CONTENTS 1 Summary 2 Market Categories and Deployment Types 3 Key Criteria Comparison 4 GigaOm Radar 5 Vendor Insights 6 Analyst’s Take 7 About Andy Thurai 8 About GigaOm 9 Copyright GigaOm Radar for Cloud Observability v1.0 2 1. Summary Observability is an emerging set of practices, platforms, and tools that goes beyond monitoring to provide insight into the internal state of systems by analyzing external outputs. It’s a concept that has its roots in 19th century control theory concepts and is rapidly gaining traction today. Of course, monitoring has been a core function of IT for decades, but old approaches have become inadequate for a variety of reasons—cloud deployments, agile development methodology, continuous deployments, and new DevOps practices among them. These have changed the way systems, infrastructure, and applications need to be observed so events and incidents can be acted upon quickly. At the heart of the observability concept is a very basic premise: quickly learn what happens within your IT to avoid extended outages. And in the unfortunate event of an outage, you need to ensure that you can get to the root cause of it fast. Outages are measured by Mean Time To Resolution (MTTR) and it is the goal of the observability concept to drive the MTTR value to as close to zero as possible. No surprise, building resilient service delivery systems that are available with high uptime is the ultimate end goal for any business. -
Rewind: 2012 in Review
the REPORT Issue 308 | 19 December 2012 Contents: PAGE 2: Artists versus digital services » PAGE 3: Fans as the fulcrum » PAGE 4: Labels in 2012 » PAGE 5: Tech giants » PAGE 6: New services » PAGES 7 – 9: Rewind: 2012 In Review Startups » PAGE 10: Digital marketing » PAGE 11: Social music » PAGE 12: Measurements » PAGE 13: Piracy battles » PAGES 14 & 15: Country profiles » REWIND: 2012 IN REVIEW the REPORT | 19 December 2012 | Page 2 Artists versus digital services It’s become a cliché in recent be portrayed as a greedy Goliath itself by digital ecosystem. prominent songwriters. High-profile albums years to suggest that the were withheld from There were many negative aspects to these streaming services, connection between artists debates in 2012, with name-calling, willful often to the barely- and fans is the fulcrum of misunderstanding and a concerning lack concealed frustration of transparency making for an unhealthy the music industry, with of their labels. mixture. everyone else a middleman Yet artists were Yet a more positive take on 2012 would be to pushing the who needs to justify their mark the importance of having artists and boundaries too, position in the value chain. songwriters take a more prominent role in the seeking new models. debates around new digital music business Usually it’s labels fielding the most criticism Whether it’s Cazzette models. under that line of argument, but in 2012 the launching their career spotlight turned to the current generation of As FAC co-CEO Crispin Hunt noted in Music on Spotify, DJ Shadow streaming music services, with Spotify and Ally’s end-of-year debate: “As the digital releasing a BitTorrent Pandora taking the brunt of the attacks. -
Application Data Analytics for Modern Applications How Sumo Logic’S Unified Machine Data Platform Changes the Management Game
Application Data Analytics for Modern Applications How Sumo Logic’s Unified Machine Data Platform Changes the Management Game An ENTERPRISE MANAGEMENT ASSOCIATES® (EMA™) White Paper Prepared for Sumo Logic July 2016 IT & DATA MANAGEMENT RESEARCH, INDUSTRY ANALYSIS & CONSULTING Application Data Analytics for Modern Applications: How Sumo Logic’s Unified Machine Data Platform Changes the Management Game Table of Contents Overview ................................................................................................................................................. 1 Telemetry, Big Operational Data, and the Real-Time Business ................................................................ 2 Modern Application Environments Require a New Approach to Application Management ................... 4 Sumo Logic: Cloud-Native Unified Logs and Metrics ............................................................................. 6 EMA Perspective ...................................................................................................................................... 8 ©2016 Enterprise Management Associates, Inc. All Rights Reserved. | www.enterprisemanagement.com Application Data Analytics for Modern Applications: How Sumo Logic’s Unified Machine Data Platform Changes the Management Game Overview telemetry – an automated communications process by which measurements and other data are collected at remote or inaccessible points and are subsequently transmitted to receiving equipment for monitoring1 The word “telemetry” has traditionally -
Designing Phelkstat: Big Data Analytics for System Event Logs
Designing PhelkStat: Big Data Analytics for System Event Logs Mohammed Salman∗, Brian Welch∗ and Joseph Tront∗ David Raymondy, Randy Marchanyy ∗Department of Electrical and Computer Engineering y IT Security Office Virginia Tech, Blacksburg Virginia Tech, Blacksburg Abstract—With wider adoption of micro-service based archi- tectures in cloud and distributed systems, logging and monitoring costs have become increasingly relevant topics of research. There are a large number of log analysis tools such as the ELK(ElasticSearch, Logstash and Kibana) stack, Apache Spark, Sumo Logic, and Loggly, among many others. These tools have been deployed to perform anomaly detection, diagnose threats, optimize performance, and troubleshoot systems. Due to the real- time and distributed nature of logging, there will always be a need to optimize the performance of these tools; this performance can be quantified in terms of compute, storage, and network utilization. As part of the Information Technology Security Lab at Virginia Tech, we have the unique ability to leverage production data from the university network for research and testing. We analyzed the workload variations from two production systems at Virginia Tech, finding that the maximum workload is about four times the average workload. Therefore, a static configuration can lead to an inefficient use of resources. To address this, we propose PhelkStat: a tool to evaluate the temporal and spatial attributes of system workloads, using clustering algorithms to categorize the current workload. Using PhelkStat, system parameters can be automatically tweaked based on the workload. This paper reviews publicly available system event log datasets from supercomputing clusters and presents a statistical analysis of these datasets. -
Leveraging Clustering and Natural Language Processing to Overcome Variety Issues in Log Management
Leveraging Clustering and Natural Language Processing to Overcome Variety Issues in Log Management Tobias Eljasik-Swoboda1 a, and Wilhelm Demuth2 1ONTEC AG, Ernst-Melchior-Gasse 24/DG, 1100 Vienna, Austria 2SCHOELLER NETWORK CONTROL GmbH, Ernst-Melchior-Gasse 24/DG, 1100 Vienna, Austria [email protected], [email protected] Keywords: Industrial Applications of AI, Intelligence and Cybersecurity, Machine Learning, Natural Language Processing, Trainer/Athlete Pattern, Log Analysis, Log Management, Event Normalization, Security Information and Event Management, Big Data Abstract: When introducing log management or Security Information and Event Management (SIEM) practices, organizations are frequently challenged by Gartner’s 3 Vs of Big Data: There is a large volume of data which is generated at a rapid velocity. These first two Vs can be effectively handled by current scale-out architectures. The third V is that of variety which affects log management efforts by the lack of a common mandatory format for log files. Essentially every component can log its events differently. The way it is logged can change with every software update. This paper describes the Log Analysis Machine Learner (LAMaLearner) system. It uses a blend of different Artificial Intelligence techniques to overcome variety issues and identify relevant events within log files. LAMaLearner is able to cluster events and generate human readable representations for all events within a cluster. A human being can annotate these clusters with specific labels. After these labels exist, LAMaLearner leverages machine learning based natural language processing techniques to label events even in changing log formats. Additionally, LAMaLearner is capable of identifying previously known named entities occurring anywhere within the logged event as well identifying frequently co-occurring variables in otherwise fixed log events.