The Effect of Cloud Computing on Growth of Startups and Entrepreneurship

This document discusses how companies can optimize costs and achieve profitability when moving to AWS. It outlines how AWS pricing models like Reserved Instances, Spot Instances, and cost-aware architectural strategies can help reduce costs of compute, storage, databases and testing/development over time. An example is provided of an APAC enterprise software company that was able to reduce unit costs by 54% working closely with AWS to optimize its architecture.

- The document discusses strategies for scaling a web application architecture to support 10 million users. - It recommends starting with a well-designed two-tier architecture using SQL databases for reliability and scalability, and adding services like S3, CloudFront, and EMR to optimize performance and enable analytics at larger scales. - Example architectures are presented starting with basic infrastructure and adding optimizations over time to support growing user bases from 10,000s to millions of users.

This document discusses cost optimization strategies on AWS. It provides examples of cost savings achieved by companies that migrated applications to AWS including a 14 million dollar annual savings for GE. It outlines approaches for architecting efficiently for cost, optimizing usage costs over time, and taking advantage of AWS pricing benefits like reserved instances, spot instances, and different storage options. The document emphasizes optimizing through proactive monitoring and billing tools, leveraging the various EC2 pricing plans, and combining options for further savings.

The document summarizes a presentation about deploying deep learning models on Amazon ECS. It begins with an introduction to deep learning and its applications. It then demonstrates building an AI model with AWS and discusses DevOps concepts. The presentation shows how to build a continuous integration and continuous deployment (CI/CD) toolchain for deep learning models using AWS services like CodePipeline, CodeBuild, CloudFormation, ECS and ECR. This allows deep learning applications to be deployed reliably and at scale.

The document summarizes a presentation about deploying deep learning models on Amazon ECS. It begins with an introduction to deep learning and its applications. It then demonstrates building an AI model with AWS and discusses DevOps concepts. The presentation shows how to build a continuous integration and continuous deployment (CI/CD) toolchain for deep learning models using AWS services like CodePipeline, CodeBuild, CloudFormation, ECS and ECR. This allows deploying models in a scalable and reliable way.

Both Azure and AWS are fundamentally same in their work mechanisms, there are some notably distinctive aspects.

This document introduces core concepts of AWS through a sample standard web architecture. It discusses what AWS is, how and why Amazon launched it, and provides examples of key AWS services like VPC, EC2, EBS, ELB, and managed services. It also covers AWS architecture concepts like regions, availability zones, and infrastructure as code.

The document discusses how higher education institutions like UMUC and George Washington University have transitioned from traditional desktops to using Amazon WorkSpaces as a cloud desktop solution. It provides examples of how the schools are using WorkSpaces to provide faculty, staff and students access to applications from anywhere, and to manage desktops securely. UMUC discusses projects using WorkSpaces to provide specialized software access for academic experiences and in classrooms. GWU shares how WorkSpaces helped support the needs of faculty, staff and students both on and off campus. The panel discusses the benefits of WorkSpaces like cost control, easy setup and provisioning, and a unified user experience.

Amazon EC2 provides you with the flexibility to cost optimize your computing portfolio through purchasing models that fit your business needs. With the flexibility of mix-and-match purchasing models, you can grow your compute capacity and throughput and enable new types of cloud computing applications with the lowest TCO. In this session, we will explore combining pay-as-you-go (On-Demand), reserve ahead of time for discounts (Reserved), and high-discount spare capacity (Spot) purchasing models to optimize costs while maintaining high performance and availability for your applications. Common application examples will be used to demonstrate how to best combine EC2’s purchasing models. You will leave the session with best practices you can immediately apply to your application portfolio.

This document provides an introduction and overview of Amazon Web Services (AWS). It discusses what the cloud is and how AWS infrastructure works with regions and availability zones. It then focuses on explaining Amazon Elastic Compute Cloud (EC2), describing what EC2 is, the terminology used, how resources are shared, and the differences between local disks vs Elastic Block Store storage. The document concludes with a thank you and mentions future sessions will provide more in-depth coverage of specific AWS services.

This document discusses using AWS for visual effects (VFX) rendering. It describes the typical VFX rendering pipeline including 3D software, production management tools, rendering software, and storage. It then outlines how to build a scalable render farm on AWS using EC2 compute instances, S3 object storage, and automation tools. Specific examples are provided for using Autodesk Mental Ray rendering software and Thinkbox Deadline render management software on AWS.

Many customers choose AWS because they need a highly reliable, scalable, and low-cost platform on which to run their applications. Low “pay only for what you use” pricing and frequent price decreases are just the beginning of how AWS can help you optimize your usage and achieve lower costs. In this session, you will learn about a few simple tools for monitoring and managing your AWS resource usage that you can start using right away, as well as some innovative features that can help you operate at lower costs programmatically. Cost allocation reporting, detailed usage reports, billing alerts, EC2 Auto Scaling, Spot and Reserved Instances, and idle resource detection are just a few of the tools and features we will cover.

Once you are at scale, it is even more important to focus on costs and run lean on AWS. This talk with explain the various purchasing models available, and will then address how to size your application for AWS. We will take you through various architectural best practices, such as auto-scaling, caching etc. to save costs and run lean by making the best decisions.

Amazon has three main businesses: online retail, selling technology infrastructure to other companies, and cloud computing services. Amazon Web Services (AWS) provides on-demand access to computing resources and services through its global infrastructure, aiming to reduce upfront costs and allow customers to scale up or down easily. AWS has a variety of services for computing, storage, databases, applications and analytics.

This is the presentation contains of the introduction about the cloud computing and amazon web service

This document discusses how to optimize costs when using AWS. It recommends: 1) Architecting for cost efficiency by "paying for what you think you need"; 2) Optimizing usage costs by "paying for what you use"; and 3) Taking advantage of benefits over time by "paying for what you really need". It provides examples of using the right instance types, reserved instances, spot instances, and services to reduce costs. It also recommends monitoring billing closely and using tools like Trusted Advisor and the TCO calculator to find additional savings.

Runa is a SaaS startup that uses machine learning and big data techniques to dynamically insert personalized promotions on e-commerce merchants' websites in real-time. They capture activity data from every merchant page view and store it indefinitely as the number of merchants grows. Their tech challenges include handling the step function increase in data from adding merchants, batch processing for analytics, and real-time rule-based promotions. They initially prototyped on AWS for its flexibility and low costs, and have since incrementally added more scalable technologies like Hadoop, HBase, and Chef on AWS to handle their growing infrastructure needs.

This document provides an overview of cloud computing, including why organizations use cloud computing, what cloud computing is, how it works, and examples of Amazon cloud services. Specifically, it discusses that cloud computing allows businesses to focus on applications rather than operations, offers flexibility to grow and shrink as needed, and provides instant scalability and low costs by paying only for resources used. It also defines infrastructure as a service (IaaS), platform as a service (PaaS), and software as a service (SaaS) and describes Amazon Web Services regions and security. The document concludes with discussing potential cloud-based projects.

This document provides an introduction to cloud computing. It defines cloud computing as providing an illusion of infinite computing resources that can be accessed on-demand in a pay-per-use model. The document discusses the evolution of cloud computing and key terms like public cloud, SaaS, PaaS, and IaaS. It provides examples of major cloud players like Amazon Web Services, Google Apps, and Microsoft Azure and how they offer infrastructure and platform services. Drivers and inhibitors for cloud adoption are also summarized.

Cloud computing allows users to access data and programs over the internet rather than on a local hard drive. Amazon Web Services (AWS) is a major provider of cloud computing infrastructure and services. A case study describes how Netflix uses AWS to host its video streaming platform, taking advantage of AWS's scalable and cost-effective resources. The document discusses concepts of cloud computing and outlines some of AWS's core services like EC2, S3, and advantages they provide to users.

This document provides an overview of moving applications to the cloud. It discusses various cloud opportunities including cost reduction, enterprise growth, and fast innovation. It also covers managing desktops and devices in the cloud, as well as popular applications that can be used in the cloud like email, conferencing software, and CRM. Finally, it summarizes several cloud platforms including Amazon Web Services, Microsoft Azure, Google Apps, and Amazon cloud services like EC2, S3, SQS, and RDS.

Introduction to Cloud Computing and Amazon Web Services. If you like it, please visit my speaker's page, and review it: http://bit.ly/i7DQFs Thanks!

This presentation from the AWS Lab at Cloud Expo Europe 2014 contains details of newly announced services from Amazon Web Services, including Amazon Kinesis, Amazon WorkSpaces, AWS CloudTrail (beta), Amazon AppStream and Amazon RDS for PostgreSQL (beta)

This document provides an overview of Amazon Web Services (AWS), including: - AWS offers on-demand computing infrastructure services including computing power, storage, databases, and content delivery. - AWS grew out of Amazon's own need for scalable infrastructure and now has hundreds of thousands of customers using its services. - Developers are attracted to AWS because of its reliability, scalability, low latency, ease of use, and low costs compared to managing their own infrastructure.