Scalable Web Architecture

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Scalable Web Architecture: LAMP, AWS, S3, CloudFront, EC2, caching strategy, scaling database, hight availibility, fault tolerant, horizontal scalability

Technology

Scalable web architecture LAMP (& AWS infrastructure) Aleksandr Tsertkov

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SD: Caching strategy ,[object Object],[object Object]

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SD: High-CPU app servers ,[object Object],[object Object],[object Object]

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SD: Static files strategy ,[object Object],[object Object],[object Object],[object Object]

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As organizations look to improve application performance and decrease costs, they are increasingly looking to migrate from commercial database engines into open source. Amazon Aurora is a MySQL-compatible relational database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. In this webinar, we will cover how to use Database Migration Service (DMS) to go about the migration, and how to use the schema conversion tool to convert schemas into Amazon Aurora. We’ll then follow with a quick demo of the entire process, and close with tips and best practices. Learning Objectives: Understand how AWS Database migration can help you migrate from a commercial database into Amazon Aurora to improve application performance and decrease database costs.

Migrate from SQL Server or Oracle into Amazon Aurora using AWS Database Migra...

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DOWNLOAD THE PRESENTATION TO SEE THE ANIMATIONS PROPERLY. Amazon Aurora has been the fastest growing service in AWS history since 2016! Amazon Aurora is a cloud relational database built from the ground up with a new, ingenious architecture. This video is part of a series. Section 1.0 here on Amazon Aurora has 16 videos! Skip over the quizzes if you'd like. Amazon Aurora is the fastest growing Service in AWS history since September, 2016 & STILL IS TODAY 2/9/2019! I cover what makes Amazon Aurora so unique & perfect for analytics that must use a relational database. I describe how it came to be, its features, its business value, some comparisons between Amazon Aurora to Amazon RDS for MySQL (now supports PostgreSQL & there's also a Serverless version! I cover high performance & why/how it accomplishes that, a high-level view of Amazon Aurora's Architecture, its ability to scale both up & out, its high availability & durability & how that's achieved, how to secure it, & a few ways to take advantage of different pricing options. It also covers Database Storage & Input/Output (IO), backups, AWS' "Simple Monthly Calculator" (which has been updated since making this video), & how its pricing compares to SQL Server

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Compared to storing long-term datasets on-premises, archiving in the cloud is a smart alternative whether you’re looking for an active archive solution, tape replacement, or to fulfill a compliance requirement. Learn how AWS customers are simplifying their archiving strategy and meeting compliance needs using Amazon Glacier. Hear how customers have evolved their backup and disaster recovery architectures and replaced tape solutions by turning to AWS for a more cost efficient, durable and agile solution. We will showcase Sony DADC's active archive deployment on Glacier and demo how some of our financial service customers have set up compliant archives to meet their regulatory objectives.

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At Monsanto, we build and use technologies that support our data and also BI efforts that facilitate intelligent, data-driven decisions. In the past year, we've embarked on large-scale efforts to modernize our geospatial platform and improve our analytic processing capabilities by building out new cloud and open-source based services. We found using Amazon Elastic File System (Amazon EFS) gave us the flexibility and performance we were seeking while saving us significant time, effort, and cost. In this session, we discuss how Monsanto uses the Amazon EFS service to run our large scaling geospatial data sets such as raster, and to perform highly parallelized analytics for data scientists and business users. Topics include the technical architecture, how and why we chose EFS for handling data sets that are terabytes in size, our recommendations, and the lessons learned along the way.

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High performance computing in the cloud is enabling high scale compute- and graphics-intensive workloads across industries, ranging from aerospace, automotive, and manufacturing to life sciences, financial services, and energy. AWS provides application developers and end users with unprecedented computational power for massively parallel applications, in areas such as large-scale fluid and materials simulations, 3D content rendering, financial computing, and deep learning. This session provides an overview of HPC capabilities on AWS, describes the newest generations of accelerated computing instances (including P2), as well as highlighting customer and partner use-cases across industries. Attendees learn about best practices for running HPC workflows in the cloud, including graphical pre- and post-processing, workflow automation, and optimization. Attendees also learn about new and emerging HPC use cases: in particular, deep learning training and inference, large-scale simulations, and high performance data analytics.

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Amazon Web Services (AWS) can make hosting scalable, highly-available websites and web applications easier and less expensive for the Enterprise Education customers. Join us for an informative webinar on tools AWS provides to elastically scale your architecture to avoid underutilized resources while reducing complexity with templates, partners, and tools to do much of the heavy lifting of creating and running a website for you.

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Cost and Performance Optimisation in Amazon RDS This session is for database administrators and other technical users looking to learn the top techniques for optimising the performance and cost of operating Amazon RDS. You will leave with a toolkit of best-practices that can be applied to your deployments for achieving optimal performance, flexibility, and cost-savings. Brad Staszcuk, Solutions Architect, Amazon Web Services

Cost and Performance Optimisation in Amazon RDS - AWS Summit Sydney 2018

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Learn how to build a scalable, compliance-ready, and automated deployment of the Microsoft “backoffice” servers for 100K users running on AWS. In this session, we show a reference architecture deployment of Exchange, SharePoint, Skype for Business, SQL Server and Active Directory in a single VPC. We discuss the following: (1) how the solution is automated for 100K users, (2) how the solution is enabled for compliance (e.g., FedRAMP, HIPAA, PCI), and (3) how the solution is built from modular 10K user blocks. Attendees should have knowledge of AWS CloudFormation, PowerShell, instance bootstrapping, VPCs, and Amazon Route 53, as well as the relevant Microsoft technologies.

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Enterprises rely on messaging to integrate services and applications and to exchange information critical to running their business. However, managing and operating dedicated message-oriented middleware and underlying infrastructure creates costly overhead and can compromise reliability. In this session, enterprise architects and developers learn how to improve scalability, availability, and operational efficiency by migrating on-premises messaging middleware to a managed cloud service using Amazon SQS. Hear how Capital One is using SQS to migrate several core banking applications to the cloud to ensure high availability and cost efficiency. We also share some exciting new SQS features that allow even more workloads to take advantage of the cloud.

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If you’re running a MySQL database at scale, there’s a good chance you’re sharding your database deployment. Sharding is a useful way to increase the scale of your deployment, but it has drawbacks like higher costs, high administration overheard and lower elasticity. It’s harder to grow or shrink a sharded database deployment to match your traffic patterns. In this session, we will discuss and demonstrate how to use AWS Database Migration Service to consolidate multiple MySQL shards into an Amazon Aurora cluster to reduce cost, improve elasticity and make it easier to manage your database. Learning Objectives: Learn how to scale your MySQL database at reduced cost and higher elasticity, by consolidating multiple shards into one Amazon Aurora cluster.

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Amazon ElastiCache makes it easy to deploy, operate, and scale an in-memory cache for web applications running in the AWS cloud. Customers can now take advantage of the managed caching service to operate Redis in the cloud where Amazon ElastiCache handles the complexity of creating, scaling and managing an in-memory store enabling developers to focus on differentiated workloads. This presentation will provide an overview of the new Amazon ElastiCache for Redis service, discuss popular use cases for Redis, and share best practices that will help you fully leverage ElastiCache for Redis in your high performance architecture.

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Organizations need to perform increasingly complex analysis on data — streaming analytics, ad-hoc querying, and predictive analytics — in order to get better customer insights and actionable business intelligence. Apache Spark has recently emerged as the framework of choice to address many of these challenges. In this session, we show you how to use Apache Spark on AWS to implement and scale common big data use cases such as real-time data processing, interactive data science, predictive analytics, and more. We will talk about common architectures, best practices to quickly create Spark clusters using Amazon EMR, and ways to integrate Spark with other big data services in AWS. Learning Objectives: • Learn why Spark is great for ad-hoc interactive analysis and real-time stream processing. • How to deploy and tune scalable clusters running Spark on Amazon EMR. • How to use EMR File System (EMRFS) with Spark to query data directly in Amazon S3. • Common architectures to leverage Spark with Amazon DynamoDB, Amazon Redshift, Amazon Kinesis, and more.

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AWS offers customers a range of different database options. These include Amazon DynamoDB, a fully-managed NoSQL database service that makes it simple and cost-effective to store and retrieve any amount of data as well as Amazon Relational Database Service (RDS), a service that makes it easy to set up, operate, and scale a relational database in the cloud with support for MySQL, Microsoft SQL Server, PostgreSQL, and Oracle Database. In this session you’ll get an overview of AWS database options and how they might help support your application and see how to get started.

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by Joyjeet Banerjee, Enterprise Solutions Architect, AWS Amazon Aurora is a MySQL- and PostgreSQL-compatible database engine that combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open source databases. In this deep dive session, we’ll discuss best practices and explore new features in areas like high availability, security, performance management and database cloning. Level 300

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During the “Architecting for the Cloud” breakfast seminar where we discussed the requirements of modern cloud-based applications and how to overcome the confinement of traditional on-premises infrastructure. We heard from data management practitioners and cloud strategists from Amazon Web Services and NuoDB about how organizations are meeting the challenges associated with building new or migrating existing applications to the cloud. Finally, we discussed how the right cloud-based architecture can: - Handle rapid user growth by adding new servers on demand - Provide high performance even in the face of heavy application usage - Offer around-the-clock resiliency and uptime - Provide easy and fast access across multiple geographies - Deliver cloud-enabled apps in public, private, or hybrid cloud environments

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