DOCSLIB.ORG

Intro to AWS @UW Cloud

Total Page：16

File Type：pdf, Size：1020Kb

Download full-text PDF Read full-text
Intro to AWS @UW Cloud Research on AWS • Genomics Research • Statistical Analysis • Mathematical Modeling • Computational Fluid Dynamics • Grid/Cluster/High Performance Computing Research use cases on AWS (examples) “ We can create an algorithm that • Carat is an application for mobile devices that uses big data to can take 32, 64, 128 different analyze energy productivity and improve cell phone battery life cores, and make it accessible to • By using AWS, UC Berkeley’s anyone in the world. researchers are able to focus on research, analysis, and customer Howard Salis service instead of administering Ph.D., Assistant Professor, Penn State computing resources • The Biological Engineering Department scaled to meet” the demands of more than 6,000 users, who have designed more than 50,000 synthetic DNA sequences Global Impact Initiatives for Science AWS Research Grants AWS Hosted Public Datasets AWS SciCo Team •Dedicated team focusing on Scientific Computing & Research workloads •Globally focussed and engaged in Big Science projects like the SKA. •Leveraging AWS resources all over the world. •Ensuring the cloud is able to make a disruptive impact on • Grants to initiate & support science. development of cloud-enabled • Large and globally significant datasets hosted technologies. and paid for by AWS for community use. • Typically one-off grants of AWS • Data can be quickly and easily processed resources like EC2 (compute) or S3 & with elastic computing resources in the EBS (storage) or more exotic like Kinesis surrounding cloud. & twitter feeds. • AWS hopes to enable more innovation, more • Frequently results in reusable resources, quickly. like AMIs or open data, which we • Provided in partnership with content strongly encourage. owners, who curate the data. • Lowers the risk to try the cloud. Peering with global research networks Image courtesy John Hover - Brookhaven National Lab Universities All-In on AWS (examples) How? Begin with the end in mind Try it– migrate something you now to AWS Think Differently – bust paradigm Learn Collaborate with central IT Get help Learning Tools Social Media: Online: Resources: Twitter YouTube Channel Resources Official Blog Training and Webinars Google+ Certification Facebook Video Self-paced Labs Examples Learn more at: https://aws.amazon.com/education Big Data Collect Store Analyze Share Direct Connect S3 Amazon EC2 S3 EMR AWS Import/Export DynamoDB Amazon Data Pipeline Redshift AWS Big Data Portfolio Amazon Glacier Amazon Kinesis: A fu l l y managed service for real-time processing of streaming data, at any scale. 21 Storage, BacKup, and Archiving On-Premises Data Center AWS Storage Gateway File sharing and seamless backup of enterprise data to Amazon S3 Disaster Block File Archive Backup Amazon Elastic BlocK Store Recovery Persistent block storage for EC2 Amazon S3 Gateway Appliance/ Redundant, high-scale object storage AWS Storage Gateway Amazon Glacier Low-cost archive storage in the cloud Amazon EBS Amazon S3 Amazon Glacier 22 Disaster Recovery Primary Site On-Premises Data Center AWS Cloud Disaster Recovery Site AWS DR S cenari os • Backup and restore • Pilot light for simple Internet Amazon recovery into AWS Storage AWS Storage Files AMIs Snapshots Gateway EBS Volumes Gateway • Warm standby solutions • Multisite solution Amazon S3 Database App Server Server App Database Server Server Amazon Amazon Amazon VPC RDS RDS Amazon RDS Cross-Region Read Replicas: • Improved disaster-recovery operations A replication mechanism that produces • Readable copies for cross-region an exact copy of a source database, applications updated continuously in another region. • Easy migration between regions 23 Web, Mobile, and Social Apps EC2 EC2 Web and Amazon S3 Amazon RDS (Master) Mobile EC2 EC2 Apps on AWS EC2 EC2 Amazon RDS Amazon Amazon Elastic Load Elastic Load (Standby) Route 53 CloudFront Balancing EC2 Balancing EC2 Amazon AppStream A flexible, interactive application-streaming service for any device • Captures user input to send back to the cloud Amazon Amazon • Responsive and consistent experience across devices EC2 App (your app) Stream Compute and render the Efficiently stream user experience on EC2 the user experience 24 (Amazon STX protocol) Virtual DesKtops Amazon WorkSpaces: A managed desktop computing service in the cloud • Half the price of an on-premises virtual desktop infrastructure (VDI) NO NO Server VDI • No hardware or virtualization software Hardware Software • Access through browser or tablet device • Monthly pricing—no long-term NO NO commitments Storage VDI Infrastructure Administration • License software from AWS or bring your own licenses • Easy integration with Microsoft Active Directory • No storage infrastructure • No VDI administration 25 Website Migrations • Launched 30 e-commerce sites in 8 countries • Saved time and increased efficiency of server in under 2 years management • Tested and innovated faster with low • Reduced operating costs by an expected 30% investment and low risk • Increased the volume of data available; • Reduced time-to-market to less than 3 months decreased latency rates • Net profit rose by 5.5% in one year, despite • Provisioned new IT resources in minutes decline in domestic mail market versus days • Market cap more than doubled to $4.2 billion in • Scaled main website to align with fluctuating under 3 years traffic demands, tracking usage to determine expansion needs 26.
Load more

Recommended publications
  • Commvault on AWS Comprehensive Cloud Data Management for Hybrid IT Table of Contents
    Commvault on AWS Comprehensive Cloud Data Management for Hybrid IT Table of Contents The Data Management Challenge 3 Commvault and Amazon Web Services 4 Benefits 7 Case Study: Dow Jones 8 Getting Started 9 2 The Data Management Challenge Today, more data is being generated than ever before. Keeping up with the rapid pace of data growth presents a series of challenges. Enterprise organizations are collecting petabytes of customer and application data that must be backed up and accessible to meet compliance requirements. Increased regulation around data retention policies make it more difficult to manage backup and archive storage, as critical data may be required to be kept for years and maybe difficult to find. Further complicating matters, point solutions often overlap and leave gaps where data is unprotected and require additional staff to manage them. These issues lead to increased costs, yet many IT departments are facing budget cuts and cannot expand upon their capital to meet increased performance demands. Today’s hybrid IT organizations realize cloud can help solve many data storage issues. With cloud storage comes the need for a comprehensive data management platform to manage data both on-premises and in the cloud. Savvy organizations streamline IT operations and reduce cloud waste with flexible orchestration to automate resource provisioning, policies and routine tasks. This eBook will demonstrate how Commvault and Amazon Web Services (AWS) deliver a cost-effective data management solution that addresses all of these challenges with a single, scalable solution. 3 Commvault and Amazon Web Services Unlike most backup and recovery solutions, Commvault offers a single data platform solution for all backup and recovery needs; as opposed to having to several point solutions for each use case (i.e.
    [Show full text]
  • AWS Managed Services (AMS)
    AWS Managed Services (AMS) Application Developer's Guide AMS Advanced Operations Plan Version September 16, 2020 AWS Managed Services (AMS) Application Developer's Guide AMS Advanced Operations Plan AWS Managed Services (AMS) Application Developer's Guide: AMS Advanced Operations Plan Copyright © Amazon Web Services, Inc. and/or its affiliates. All rights reserved. Amazon's trademarks and trade dress may not be used in connection with any product or service that is not Amazon's, in any manner that is likely to cause confusion among customers, or in any manner that disparages or discredits Amazon. All other trademarks not owned by Amazon are the property of their respective owners, who may or may not be affiliated with, connected to, or sponsored by Amazon. AWS Managed Services (AMS) Application Developer's Guide AMS Advanced Operations Plan Table of Contents Application Onboarding to AMS Introduction ........................................................................................ 1 What is Application Onboarding? ................................................................................................. 1 What we do, what we do not do .................................................................................................. 1 AMS Amazon Machine Images (AMIs) ............................................................................................ 2 Security enhanced AMIs ...................................................................................................... 4 Key terms .................................................................................................................................
    [Show full text]
  • Performance Efficiency Pillar
    Performance Efficiency Pillar AWS Well-Architected Framework Performance Efficiency Pillar AWS Well-Architected Framework Performance Efficiency Pillar: AWS Well-Architected Framework Copyright © Amazon Web Services, Inc. and/or its affiliates. All rights reserved. Amazon's trademarks and trade dress may not be used in connection with any product or service that is not Amazon's, in any manner that is likely to cause confusion among customers, or in any manner that disparages or discredits Amazon. All other trademarks not owned by Amazon are the property of their respective owners, who may or may not be affiliated with, connected to, or sponsored by Amazon. Performance Efficiency Pillar AWS Well-Architected Framework Table of Contents Abstract and Introduction ................................................................................................................... 1 Abstract .................................................................................................................................... 1 Introduction .............................................................................................................................. 1 Performance Efficiency ....................................................................................................................... 2 Design Principles ........................................................................................................................ 2 Definition .................................................................................................................................
    [Show full text]
  • Migrating to Google Cloud Storage Nearline from Amazon Glacier
    Migrating to Google Cloud PAUL NEWSON | 07/23/15 Storage Nearline ​ Migrating to Google Cloud Storage Nearline From Amazon Glacier Page 1 Migrating to Google Cloud PAUL NEWSON | 07/23/15 Storage Nearline ​ Migrating to Google Cloud Storage Nearline From Amazon Glacier Table of contents: Summary Overview Prerequisites Create a Workspace and Staging Area Create a Bucket Using the Nearline Storage Class Choose a Naming Convention Begin Storing New Data in Cloud Storage Nearline Migrating Data Stored Directly in Amazon Glacier Get an Inventory of Archives Make an Archive Available for Download Download the Archive to a Staging Area Upload Data to Cloud Storage Nearline Migrating in Batches Migrating Data Stored in Amazon Glacier via Amazon S3 Get an Inventory of Archives Make an Archive Available for Download Upload Data to Cloud Storage Nearline Migrating in Batches Understanding the Cost of Retrieving Data from Amazon Glacier Recommendations Appendix A: Creating a Workspace and Staging Area Create or Select a Cloud Platform Project Install and Configure the Cloud SDK Create and Configure a Compute Engine Instance References Page 2 Migrating to Google Cloud PAUL NEWSON | 07/23/15 Storage Nearline ​ Page 3 Migrating to Google Cloud PAUL NEWSON | 07/23/15 Storage Nearline ​ Summary Google Cloud Storage Nearline is a low cost storage class available in Google Cloud Storage which is attractive for archival workloads, such as cold storage and disaster recovery. Amazon Glacier also provides a storage service suitable for archival workloads, but retrieval latency in Amazon Glacier is measured in hours whereas Google Cloud Storage Nearline provides retrieval latency measured in seconds.
    [Show full text]
  • Amazon Mechanical Turk Requester UI Guide Amazon Mechanical Turk Requester UI Guide
    Amazon Mechanical Turk Requester UI Guide Amazon Mechanical Turk Requester UI Guide Amazon Mechanical Turk: Requester UI Guide Copyright © 2014 Amazon Web Services, Inc. and/or its affiliates. All rights reserved. The following are trademarks of Amazon Web Services, Inc.: Amazon, Amazon Web Services Design, AWS, Amazon CloudFront, Cloudfront, Amazon DevPay, DynamoDB, ElastiCache, Amazon EC2, Amazon Elastic Compute Cloud, Amazon Glacier, Kindle, Kindle Fire, AWS Marketplace Design, Mechanical Turk, Amazon Redshift, Amazon Route 53, Amazon S3, Amazon VPC. In addition, Amazon.com graphics, logos, page headers, button icons, scripts, and service names are trademarks, or trade dress of Amazon in the U.S. and/or other countries. Amazon©s trademarks and trade dress may not be used in connection with any product or service that is not Amazon©s, in any manner that is likely to cause confusion among customers, or in any manner that disparages or discredits Amazon. All other trademarks not owned by Amazon are the property of their respective owners, who may or may not be affiliated with, connected to, or sponsored by Amazon. Amazon Mechanical Turk Requester UI Guide Table of Contents Welcome ..................................................................................................................................... 1 How Do I...? ......................................................................................................................... 1 Introduction to Mechanical Turk .......................................................................................................
    [Show full text]
  • Using Amazon Web Services for Disaster Recovery October 2014
    Amazon Web Services – Using AWS for Disaster Recovery October 2014 Using Amazon Web Services for Disaster Recovery October 2014 Glen Robinson, Attila Narin, and Chris Elleman Page 1 of 22 Amazon Web Services – Using AWS for Disaster Recovery October 2014 Contents Introduction ...............................................................................................................................................................3 Recovery Time Objective and Recovery Point Objective ................................................................................................4 Traditional DR Investment Practices ............................................................................................................................4 AWS Services and Features Essential for Disaster Recovery ...........................................................................................5 Example Disaster Recovery Scenarios with AWS ...........................................................................................................9 Backup and Restore ................................................................................................................................................9 Pilot Light for Quick Recovery into AWS ................................................................................................................. 11 Warm Standby Solution in AWS ............................................................................................................................. 14 Multi-Site Solution Deployed
    [Show full text]
  • AWS Cost and Usage Reports User Guide AWS Cost and Usage Reports User Guide
    AWS Cost and Usage Reports User Guide AWS Cost and Usage Reports User Guide AWS Cost and Usage Reports: User Guide Copyright © Amazon Web Services, Inc. and/or its affiliates. All rights reserved. Amazon's trademarks and trade dress may not be used in connection with any product or service that is not Amazon's, in any manner that is likely to cause confusion among customers, or in any manner that disparages or discredits Amazon. All other trademarks not owned by Amazon are the property of their respective owners, who may or may not be affiliated with, connected to, or sponsored by Amazon. AWS Cost and Usage Reports User Guide Table of Contents What are AWS Cost and Usage Reports? ............................................................................................... 1 How it works ............................................................................................................................. 1 Using the data dictionary ............................................................................................................ 1 Download AWS CUR ................................................................................................................... 2 AWS Organizations users ............................................................................................................ 2 Creating reports ................................................................................................................................. 3 Setting up an Amazon S3 bucket for Cost and Usage Reports .........................................................
    [Show full text]
  • October 25, 2012—Amazon.Com, Inc
    AMAZON.COM ANNOUNCES THIRD QUARTER SALES UP 27% TO $13.81 BILLION SEATTLE—(BUSINESS WIRE)—October 25, 2012—Amazon.com, Inc. (NASDAQ: AMZN) today announced financial results for its third quarter ended September 30, 2012. Operating cash flow increased 8% to $3.37 billion for the trailing twelve months, compared with $3.11 billion for the trailing twelve months ended September 30, 2011. Free cash flow decreased 31% to $1.06 billion for the trailing twelve months, compared with $1.53 billion for the trailing twelve months ended September 30, 2011. Common shares outstanding plus shares underlying stock-based awards totaled 469 million on September 30, 2012, consistent with 469 million one year ago. Net sales increased 27% to $13.81 billion in the third quarter, compared with $10.88 billion in third quarter 2011. Excluding the $348 million unfavorable impact from year-over-year changes in foreign exchange rates throughout the quarter, net sales grew 30% compared with third quarter 2011. Operating loss was $28 million in the third quarter, compared with operating income of $79 million in third quarter 2011. The unfavorable impact from year-over-year changes in foreign exchange rates throughout the quarter on operating loss was $3 million. Net loss was $274 million in the third quarter, or $0.60 per diluted share, compared with net income of $63 million, or $0.14 per diluted share, in third quarter 2011. The third quarter 2012 includes a loss of $169 million, or $0.37 per diluted share, related to our equity-method share of the losses reported by LivingSocial, primarily attributable to its impairment charge of certain assets, including goodwill.
    [Show full text]
  • AWS Pricing Overview
    How AWS Pricing Works June 2018 (Please consult http://aws.amazon.com/whitepapers/ for the latest version of this paper) Amazon Web Services – How AWS Pricing Works June 2018 Table of Contents Introduction ................................................................................................................................................................................... 4 Key Principles ................................................................................................................................................................................. 4 Understand the fundamentals of pricing ............................................................................................................................. 4 Start early with cost optimization .......................................................................................................................................... 4 Maximize the power of flexibility ........................................................................................................................................... 5 Use the right pricing model for the job ................................................................................................................................ 5 Get started with the AWS Free Tier ........................................................................................................................................... 6 Pricing details for individual services ........................................................................................................................................
    [Show full text]
  • Istanbul Technical University Faculty of Computer and Informatics a Study
    ISTANBUL TECHNICAL UNIVERSITY FACULTY OF COMPUTER AND INFORMATICS A STUDY ON TRENDS IN INFORMATION TECHNOLOGIES USING BIG DATA ANALYTICS Graduation Project Mahmut Ali ÖZKURAN 040000815 Department: Computer Engineering Advisor: Asst. Prof. Dr. Ayşe Tosun Mısırlı May 2015 This Page Intentionally Left Blank ISTANBUL TECHNICAL UNIVERSITY FACULTY OF COMPUTER AND INFORMATICS A STUDY ON TRENDS IN INFORMATION TECHNOLOGIES USING BIG DATA ANALYTICS Graduation Project Mahmut Ali ÖZKURAN 040000815 Department: Computer Engineering Advisor: Asst. Prof. Dr. Ayşe Tosun Mısırlı May 2015 This Page Intentionally Left Blank I Özgünlük Bildirisi 1. Bu çalışmada, başka kaynaklardan yapılan tüm alıntıların, ilgili kaynaklar referans gösterilerek açıkça belirtildiğini, 2. Alıntılar dışındaki bölümlerin, özellikle projenin ana konusunu oluşturan teorik çalışmaların ve yazılım/donanımın benim tarafımdan yapıldığını bildiririm. İstanbul, 29.05.2015 Mahmut Ali ÖZKURAN II This Page Intentionally Left Blank III A STUDY ON TRENDS IN INFORMATION TECHNOLOGIES USING BIG DATA ANALYTICS (SUMMARY) We are living in an information era from Twitter [1] to Fitocracy [2]; every episode of peoples’ life is converted to numbers. That abundance of data is also available in information technologies. From Stackoverflow [3] to GitHub [4] many big data sources are available about trends in Information Technologies. The aim of this research is studying information technology trends and compiling useful information about those technologies using big data sources mentioned above. Those collected information might be helpful for decision makers or information technology professionals to decide where to invest their time and money. In this research we have mined and analyzed StackExchange and GitHub data for creating meaningful predictions about information technologies. Initially StackExchange and GitHub data were imported into local data repositories.
    [Show full text]
  • Overview of AWS Security - Storage Services
    Overview of AWS Security - Storage Services June 2016 (Please consult http://aws.amazon.com/security/ for the latest version of this paper) © 2016, Amazon Web Services, Inc. or its affiliates. All rights reserved. Notices This document is provided for informational purposes only. It represents AWS’ current product offerings and practices as of the date of issue of this document, which are subject to change without notice. Customers are responsible for making their own independent assessment of the information in this document and any use of AWS’ products or services, each of which is provided “as is” without warranty of any kind, whether express or implied. This document does not create any warranties, representations, contractual commitments, conditions or assurances from AWS, its affiliates, suppliers or licensors. The responsibilities and liabilities of AWS to its customers are controlled by AWS agreements, and this document is not part of, nor does it modify, any agreement between AWS and its customers. Page 2 of 9 Storage Services Amazon Web Services provides low-cost data storage with high durability and availability. AWS offers storage choices for backup, archiving, and disaster recovery, as well as block and object storage. Amazon Simple Storage Service (Amazon S3) Security Amazon Simple Storage Service (S3) allows you to upload and retrieve data at any time, from anywhere on the web. Amazon S3 stores data as objects within buckets. An object can be any kind of file: a text file, a photo, a video, etc. When you add a file to Amazon S3, you have the option of including metadata with the file and setting permissions to control access to the file.
    [Show full text]
  • Amazon Web Services: Overview of Security Processes August 2015
    Amazon Web Services – Overview of Security Processes August 2015 Amazon Web Services: Overview of Security Processes August 2015 (Please consult http://aws.amazon.com/security/ for the latest version of this paper) Page 1 of 75 Amazon Web Services – Overview of Security Processes August 2015 Table of Contents Introduction ............................................................................................................................................................................ 5 Shared Security Responsibility Model .................................................................................................................................... 5 AWS Security Responsibilities ............................................................................................................................................. 6 Customer Security Responsibilities ..................................................................................................................................... 6 AWS Global Infrastructure Security ........................................................................................................................................ 7 AWS Compliance Program .................................................................................................................................................. 7 Physical and Environmental Security .................................................................................................................................. 8 Fire Detection and Suppression
    [Show full text]