This session, we go deep into advanced design patterns for DynamoDB. This session is intended for those who already have some familiarity with DynamoDB and are interested in applying the design patterns covered in the DynamoDB deep dive session and hands-on labs for DynamoDB. The patterns and data models discussed in this presentation summarize a collection of implementations and best practices leveraged by the Amazon CDO to deliver highly scaleable solutions for a wide variety of business problems. In this session, we discuss strategies for GSI sharding and index overloading, scaleable graph processing with materialized queries, relational modeling with composite keys, executing transactional workflows on DynamoDB, and much, much more.
MongoDB World 2019: MongoDB Read Isolation: Making Your Reads Clean, Committe...MongoDB
Isolation, the I in ACID, determines how/when the changes made by one operation become visible to another. Relational databases provide four isolation levels (uncommitted, committed, repeatable reads, and serialiable) to enable the trade off of performance versus the level of cross operation change visibility. In contrast, MongoDB’s isolation levels are controlled by using readConcerns and transactions. This talk will describe how the relational isolation levels compare to MongoDB’s isolation guarantees, how you configure MongoDB to provide the desired isolation level, and the performance implications.
This talk will describe the changes which went into MongoDB 3.0 in order to allow storage engines to achieve their maximum concurrency potential. In MongoDB 3.0, concurrency control has been separated into two levels: top-level, which protects the database catalog, and storage engine-level, which allows each individual storage engine implementation to manage its own concurrency. We will start from the top and introduce the concept of multi-granularity locking and how it protects the database catalog. We will then explain how the MongoDB lock manager works and how it allows storage engines to manage their own concurrency control without imposing any additional overhead.
AWS January 2016 Webinar Series - Introduction to Docker on AWSAmazon Web Services
Using Docker on your local development machine is simple, but running Docker applications at scale in production can be difficult.
In this webinar, we will discuss the difficulties of running Docker in production and how Amazon EC2 Container Service (ECS) can be used to reduce the operational burdens, and we will give an overview of the architecture powering Amazon ECS. We will also demo how to define multi-container applications with Docker Compose and deploy and scale them seamlessly to a cluster with Amazon ECS.
Learning Objectives:
Understand the benefits and architecture of Amazon ECS
Learn how to deploy and scale Docker containers on Amazon ECS
Who Should Attend:
Developers
MongoDB World 2019: MongoDB Read Isolation: Making Your Reads Clean, Committe...MongoDB
Isolation, the I in ACID, determines how/when the changes made by one operation become visible to another. Relational databases provide four isolation levels (uncommitted, committed, repeatable reads, and serialiable) to enable the trade off of performance versus the level of cross operation change visibility. In contrast, MongoDB’s isolation levels are controlled by using readConcerns and transactions. This talk will describe how the relational isolation levels compare to MongoDB’s isolation guarantees, how you configure MongoDB to provide the desired isolation level, and the performance implications.
This talk will describe the changes which went into MongoDB 3.0 in order to allow storage engines to achieve their maximum concurrency potential. In MongoDB 3.0, concurrency control has been separated into two levels: top-level, which protects the database catalog, and storage engine-level, which allows each individual storage engine implementation to manage its own concurrency. We will start from the top and introduce the concept of multi-granularity locking and how it protects the database catalog. We will then explain how the MongoDB lock manager works and how it allows storage engines to manage their own concurrency control without imposing any additional overhead.
AWS January 2016 Webinar Series - Introduction to Docker on AWSAmazon Web Services
Using Docker on your local development machine is simple, but running Docker applications at scale in production can be difficult.
In this webinar, we will discuss the difficulties of running Docker in production and how Amazon EC2 Container Service (ECS) can be used to reduce the operational burdens, and we will give an overview of the architecture powering Amazon ECS. We will also demo how to define multi-container applications with Docker Compose and deploy and scale them seamlessly to a cluster with Amazon ECS.
Learning Objectives:
Understand the benefits and architecture of Amazon ECS
Learn how to deploy and scale Docker containers on Amazon ECS
Who Should Attend:
Developers
Building with AWS Databases: Match Your Workload to the Right Database (DAT30...Amazon Web Services
We have recently seen some convergence of different database technologies. Many customers are evaluating heterogeneous migrations as their database needs have evolved or changed. Evaluating the best database to use for a job isn't as clear as it was ten years ago. We'll discuss the ideal use cases for relational and nonrelational data services, including Amazon ElastiCache for Redis, Amazon DynamoDB, Amazon Aurora, Amazon Neptune, and Amazon Redshift. This session digs into how to evaluate a new workload for the best managed database option. Please join us for a speaker meet-and-greet following this session at the Speaker Lounge (ARIA East, Level 1, Willow Lounge). The meet-and-greet starts 15 minutes after the session and runs for half an hour.
The presentation explains how to setup rate limits, how to work with 429 code, how rate limits are implemented in kubernetes, cni, loadbalancer and so on
What is AWS?
Most Popular AWS Products
What is Serverless Architecture?
Asynchronous Serverless Model
Synchronous Serverless Model
Amazon Lambda
https://notebookbft.wordpress.com/
AWS Training For Beginners | AWS Certified Solutions Architect Tutorial | AWS...Simplilearn
This AWS training for beginners presentation will help you understand what is AWS (Amazon Web Services), how did AWS become so successful, the services that AWS provides (AWS EC2, Amazon Elastic Beanstalk, Amazon Lightsail, Amazon Lambda, Amazon S3, Amazon Glacier, Amazon EBS, Amazon Elastic File System, Amazon RDS, Amazon Redshift), the future of AWS and a demonstration on deploying a web application in AWS. Amazon Web services (AWS) provide a lot of benefits to a business organization. These benefits allow you to maximize your productivity and enhance efficiency. This AWS tutorial video is ideal for those who aspire to become AWS Certified Solution Architect. Now, let us deep dive into the video to understand what AWS actually is and what are the services that AWS provides to an organization.
The below topics are covered in this AWS presentation:
1. What is AWS?
2. How did AWS become so successful?
3. The services AWS provides
4. The future of AWS
5. Use case - Deploying a web application
This AWS certification training is designed to help you gain the in-depth understanding of Amazon Web Services (AWS) architectural principles and services. You will learn how cloud computing is redefining the rules of IT architecture and how to design, plan, and scale AWS Cloud implementations with best practices recommended by Amazon. The AWS Cloud platform powers hundreds of thousands of businesses in 190 countries, and AWS certified solution architects take home about $126,000 per year.
This AWS certification course will help you learn the key concepts, latest trends, and best practices for working with the AWS architecture – and become industry-ready AWS certified solutions architect to help you qualify for a position as a high-quality AWS professional.
The course begins with an overview of the AWS platform before diving into its individual elements: IAM, VPC, EC2, EBS, ELB, CDN, S3, EIP, KMS, Route 53, RDS, Glacier, Snowball, Cloudfront, Dynamo DB, Redshift, Auto Scaling, Cloudwatch, Elastic Cache, CloudTrail, and Security. Those who complete the course will be able to:
1. Formulate solution plans and provide guidance on AWS architectural best practices
2. Design and deploy scalable, highly available, and fault tolerant systems on AWS
3. Identify the lift and shift of an existing on-premises application to AWS
4. Decipher the ingress and egress of data to and from AWS
5. Select the appropriate AWS service based on data, compute, database, or security requirements
6. Estimate AWS costs and identify cost control mechanisms
This AWS course is recommended for professionals who want to pursue a career in Cloud computing or develop Cloud applications with AWS. You’ll become an asset to any organization, helping leverage best practices around advanced cloud-based solutions and migrate existing workloads to the cloud.
Learn more at: https://www.simplilearn.com
Cassandra concepts, patterns and anti-patternsDave Gardner
An introduction to the fundamental concepts behind Apache Cassandra. This talk explains the engineering principles that make Cassandra such an attractive choice for building highly resilient and available systems and then goes on to explain how to use it - covering basic data modelling patterns and anti-patterns.
Apache Kafka as Data Hub for Crypto, NFT, Metaverse (Beyond the Buzz!)Kai Wähner
Decentralized finance with crypto and NFTs is a huge topic these days. It becomes a powerful combination with the coming metaverse platforms across industries. This session explores the relationship between crypto technologies and modern enterprise architecture.
I discuss how data streaming and Apache Kafka help build innovation and scalable real-time applications of a future metaverse. Let's skip the buzz (and NFT bubble) and instead review existing real-world deployments in the crypto and blockchain world powered by Kafka and its ecosystem.
BRIEF HISTORY OF DATA PROCESSING
RELATIONAL (SQL) VS. NONRELATIONAL (NOSQL)
Why noSQL?
ACID VS CAP
DynamoDB- what is it?
DynamoDB ARCHITECTURE
Conditional Writes
Provisioned throughput
QUERY VS SCAN
Operations
Benefits
Limitations
DEMO
Benchmarking is hard. Benchmarking databases, harder. Benchmarking databases that follow different approaches (relational vs document) is even harder.
But the market demands these kinds of benchmarks. Despite the different data models that MongoDB and PostgreSQL expose, many organizations face the challenge of picking either technology. And performance is arguably the main deciding factor.
Join this talk to discover the numbers! After $30K spent on public cloud and months of testing, there are many different scenarios to analyze. Benchmarks on three distinct categories have been performed: OLTP, OLAP and comparing MongoDB 4.0 transaction performance with PostgreSQL's.
What would be faster, MongoDB or PostgreSQL?
Using AWS Batch and AWS Step Functions to Design and Run High-Throughput Work...Amazon Web Services
Learning Objectives:
- How to simply scale out your batch workflows on AWS
- How to think about container/job management within managed, high-throughput workflows
- How to build a scalable orchestration framework within AWS Step Functions
This session will begin with an introduction to non-relational (NoSQL) databases and compare them with relational (SQL) databases. Learn the fundamentals of Amazon DynamoDB, a fully managed NoSQL database service, and see the DynamoDB console first-hand. See a walk-through demo of building a serverless web application using this high-performance key-value and JSON document store.
An overview of the Amazon ElastiCache managed service, with examples of how it can be used to increase performance, lower costs and augment other database services and databases to make things faster, easier and less expensive.
SRV307 Applying AWS Purpose-Built Database Strategy: Match Your Workload to ...Amazon Web Services
In this session, Tony Petrossian, director of engineering, AWS Database Services, dives deep into what databases to use for which components of your application. Learn how to evaluate a new workload for the best managed database option based on specific application needs related to data shape, data size at limit, computational requirements, programmability, throughput and latency needs, etc. This session explains the ideal use cases for relational and non-relational database services, including Amazon Aurora, Amazon DynamoDB, Amazon ElastiCache for Redis, Amazon Neptune, and Amazon Redshift.
In this session, we dive deep into applying the AWS Purpose-Built Database Strategy to determine which databases to use for which components of your application. Learn how to evaluate a new workload for the best managed database option, based on specific application needs related to data shape, data size at limit, computational requirements, programmability, throughput and latency needs, and more. We explain the ideal use cases for relational and non-relational database services, including Amazon Aurora, Amazon DynamoDB, Amazon ElastiCache for Redis, Amazon Neptune, and Amazon Redshift.
Building with AWS Databases: Match Your Workload to the Right Database (DAT30...Amazon Web Services
We have recently seen some convergence of different database technologies. Many customers are evaluating heterogeneous migrations as their database needs have evolved or changed. Evaluating the best database to use for a job isn't as clear as it was ten years ago. We'll discuss the ideal use cases for relational and nonrelational data services, including Amazon ElastiCache for Redis, Amazon DynamoDB, Amazon Aurora, Amazon Neptune, and Amazon Redshift. This session digs into how to evaluate a new workload for the best managed database option. Please join us for a speaker meet-and-greet following this session at the Speaker Lounge (ARIA East, Level 1, Willow Lounge). The meet-and-greet starts 15 minutes after the session and runs for half an hour.
The presentation explains how to setup rate limits, how to work with 429 code, how rate limits are implemented in kubernetes, cni, loadbalancer and so on
What is AWS?
Most Popular AWS Products
What is Serverless Architecture?
Asynchronous Serverless Model
Synchronous Serverless Model
Amazon Lambda
https://notebookbft.wordpress.com/
AWS Training For Beginners | AWS Certified Solutions Architect Tutorial | AWS...Simplilearn
This AWS training for beginners presentation will help you understand what is AWS (Amazon Web Services), how did AWS become so successful, the services that AWS provides (AWS EC2, Amazon Elastic Beanstalk, Amazon Lightsail, Amazon Lambda, Amazon S3, Amazon Glacier, Amazon EBS, Amazon Elastic File System, Amazon RDS, Amazon Redshift), the future of AWS and a demonstration on deploying a web application in AWS. Amazon Web services (AWS) provide a lot of benefits to a business organization. These benefits allow you to maximize your productivity and enhance efficiency. This AWS tutorial video is ideal for those who aspire to become AWS Certified Solution Architect. Now, let us deep dive into the video to understand what AWS actually is and what are the services that AWS provides to an organization.
The below topics are covered in this AWS presentation:
1. What is AWS?
2. How did AWS become so successful?
3. The services AWS provides
4. The future of AWS
5. Use case - Deploying a web application
This AWS certification training is designed to help you gain the in-depth understanding of Amazon Web Services (AWS) architectural principles and services. You will learn how cloud computing is redefining the rules of IT architecture and how to design, plan, and scale AWS Cloud implementations with best practices recommended by Amazon. The AWS Cloud platform powers hundreds of thousands of businesses in 190 countries, and AWS certified solution architects take home about $126,000 per year.
This AWS certification course will help you learn the key concepts, latest trends, and best practices for working with the AWS architecture – and become industry-ready AWS certified solutions architect to help you qualify for a position as a high-quality AWS professional.
The course begins with an overview of the AWS platform before diving into its individual elements: IAM, VPC, EC2, EBS, ELB, CDN, S3, EIP, KMS, Route 53, RDS, Glacier, Snowball, Cloudfront, Dynamo DB, Redshift, Auto Scaling, Cloudwatch, Elastic Cache, CloudTrail, and Security. Those who complete the course will be able to:
1. Formulate solution plans and provide guidance on AWS architectural best practices
2. Design and deploy scalable, highly available, and fault tolerant systems on AWS
3. Identify the lift and shift of an existing on-premises application to AWS
4. Decipher the ingress and egress of data to and from AWS
5. Select the appropriate AWS service based on data, compute, database, or security requirements
6. Estimate AWS costs and identify cost control mechanisms
This AWS course is recommended for professionals who want to pursue a career in Cloud computing or develop Cloud applications with AWS. You’ll become an asset to any organization, helping leverage best practices around advanced cloud-based solutions and migrate existing workloads to the cloud.
Learn more at: https://www.simplilearn.com
Cassandra concepts, patterns and anti-patternsDave Gardner
An introduction to the fundamental concepts behind Apache Cassandra. This talk explains the engineering principles that make Cassandra such an attractive choice for building highly resilient and available systems and then goes on to explain how to use it - covering basic data modelling patterns and anti-patterns.
Apache Kafka as Data Hub for Crypto, NFT, Metaverse (Beyond the Buzz!)Kai Wähner
Decentralized finance with crypto and NFTs is a huge topic these days. It becomes a powerful combination with the coming metaverse platforms across industries. This session explores the relationship between crypto technologies and modern enterprise architecture.
I discuss how data streaming and Apache Kafka help build innovation and scalable real-time applications of a future metaverse. Let's skip the buzz (and NFT bubble) and instead review existing real-world deployments in the crypto and blockchain world powered by Kafka and its ecosystem.
BRIEF HISTORY OF DATA PROCESSING
RELATIONAL (SQL) VS. NONRELATIONAL (NOSQL)
Why noSQL?
ACID VS CAP
DynamoDB- what is it?
DynamoDB ARCHITECTURE
Conditional Writes
Provisioned throughput
QUERY VS SCAN
Operations
Benefits
Limitations
DEMO
Benchmarking is hard. Benchmarking databases, harder. Benchmarking databases that follow different approaches (relational vs document) is even harder.
But the market demands these kinds of benchmarks. Despite the different data models that MongoDB and PostgreSQL expose, many organizations face the challenge of picking either technology. And performance is arguably the main deciding factor.
Join this talk to discover the numbers! After $30K spent on public cloud and months of testing, there are many different scenarios to analyze. Benchmarks on three distinct categories have been performed: OLTP, OLAP and comparing MongoDB 4.0 transaction performance with PostgreSQL's.
What would be faster, MongoDB or PostgreSQL?
Using AWS Batch and AWS Step Functions to Design and Run High-Throughput Work...Amazon Web Services
Learning Objectives:
- How to simply scale out your batch workflows on AWS
- How to think about container/job management within managed, high-throughput workflows
- How to build a scalable orchestration framework within AWS Step Functions
This session will begin with an introduction to non-relational (NoSQL) databases and compare them with relational (SQL) databases. Learn the fundamentals of Amazon DynamoDB, a fully managed NoSQL database service, and see the DynamoDB console first-hand. See a walk-through demo of building a serverless web application using this high-performance key-value and JSON document store.
An overview of the Amazon ElastiCache managed service, with examples of how it can be used to increase performance, lower costs and augment other database services and databases to make things faster, easier and less expensive.
SRV307 Applying AWS Purpose-Built Database Strategy: Match Your Workload to ...Amazon Web Services
In this session, Tony Petrossian, director of engineering, AWS Database Services, dives deep into what databases to use for which components of your application. Learn how to evaluate a new workload for the best managed database option based on specific application needs related to data shape, data size at limit, computational requirements, programmability, throughput and latency needs, etc. This session explains the ideal use cases for relational and non-relational database services, including Amazon Aurora, Amazon DynamoDB, Amazon ElastiCache for Redis, Amazon Neptune, and Amazon Redshift.
In this session, we dive deep into applying the AWS Purpose-Built Database Strategy to determine which databases to use for which components of your application. Learn how to evaluate a new workload for the best managed database option, based on specific application needs related to data shape, data size at limit, computational requirements, programmability, throughput and latency needs, and more. We explain the ideal use cases for relational and non-relational database services, including Amazon Aurora, Amazon DynamoDB, Amazon ElastiCache for Redis, Amazon Neptune, and Amazon Redshift.
Applying AWS Purpose-Built Database Strategy - SRV307 - Toronto AWS SummitAmazon Web Services
In this session, we dive deep into applying the "AWS Purpose-Built Database Strategy" to determine which databases to use for which components of your application. Learn how to evaluate a new workload for the best managed database option based on specific application needs related to data shape, data size at limit, computational requirements, programmability, throughput and latency needs, etc. This session explains the ideal use cases for relational and non-relational database services, including Amazon Aurora, Amazon DynamoDB, Amazon ElastiCache for Redis, Amazon Neptune, and Amazon Redshift.
Tinder and DynamoDB: It's a Match! Massive Data Migration, Zero Down Time - D...Amazon Web Services
Are you considering a massive data migration? Do you worry about downtime during a migration? Dr. JunYoung Kwak, Tinder’s Lead Engineering Manager, will share his insights on how Tinder successfully migrated critical user data to DynamoDB with zero downtime. Join us to learn how Tinder leverages DynamoDB performance and scalability to meet the needs of their growing global user base.
Journey Towards Scaling Your API to 10 Million UsersAdrian Hornsby
The slides from my talk at the NordicAPI summit 2017:
https://nordicapis.com/sessions/journey-towards-scaling-application-10-million-users/
A collection of thoughts and ideas that I experienced during my 10 years working with AWS Cloud.
Amazon.com - Replacing 100s of Oracle DBs with Just One: DynamoDB - ARC406 - ...Amazon Web Services
When customers across the globe place orders on Amazon.com, those orders are processed through many different backend systems, including Herd, a workflow-orchestration engine developed by the Amazon eCommerce Foundation team. A mission-critical system used by more than 300 Amazon engineering teams, Herd executes over four billion workflows every day. Beginning in 2013, Herd’s workflow traffic was doubling year-over-year, and scaling its then dozens of horizontally-partitioned Oracle databases was becoming a nightmare, and this number kept increasing. To support Herd’s increasing scaling needs, and to provide a better customer experience, the Herd team had to re-architect its storage system and move its primary data storage from Oracle to Amazon DynamoDB. In this session, we discuss how we moved from Oracle to Amazon DynamoDB, walk through the biggest challenges we faced and how we overcame them, and share the lessons we learned along the way.
RET305-Turbo Charge Your E-Commerce Site wAmazon Cache and Search Solutions.pdfAmazon Web Services
In this retail-focused workshop, we review and solve some of the common technical challenges that retailers face. These include scaling their backend databases to accommodate fluctuating demand and enabling full-text product search to achieve more relevant product search results. Bring your laptops, because after reviewing the proposed solutions, you can get hands-on with Amazon ElastiCache for Redis and see how easy it is to reduce the cost and pressure to your backend database, while dramatically improving the performance. We also show how you can leverage the Amazon Elasticsearch Service for building a full-text search solution.
DynamoDB adaptive capacity: smooth performance for chaotic workloads - DAT327...Amazon Web Services
Database capacity planning is critical to running your business, but it’s also hard. In this session we’ll compare how scaling is usually performed for relational databases and NoSQL databases. We’ll look behind the scenes at how DynamoDB shards your data across multiple partitions and servers. Finally, we’ll talk about some of the recent enhancements to DynamoDB that make scaling even simpler, particularly a new feature called adaptive throughput that eliminates much of the throttling issues that you may have experienced.
How to build a data lake with aws glue data catalog (ABD213-R) re:Invent 2017Amazon Web Services
As data volumes grow and customers store more data on AWS, they often have valuable data that is not easily discoverable and available for analytics. The AWS Glue Data Catalog provides a central view of your data lake, making data readily available for analytics. We introduce key features of the AWS Glue Data Catalog and its use cases. Learn how crawlers can automatically discover your data, extract relevant metadata, and add it as table definitions to the AWS Glue Data Catalog. We will also explore the integration between AWS Glue Data Catalog and Amazon Athena, Amazon EMR, and Amazon Redshift Spectrum.
Massively Parallel Data Processing with PyWren and AWS Lambda - SRV424 - re:I...Amazon Web Services
Have you ever wanted a "process in the cloud" button on your laptop for your data scientists? In this workshop we will explore how to achieve fast processing speeds by making use of an open-source project called PyWren to massively parallelize data analytics jobs across hundreds or thousands of AWS Lambda functions. We will learn how to use PyWren's wrapper to execute your Python function in parallel, potentially achieving tenths of TFLOPS at peak with Amazon S3 as event coordinator. Lastly we will make use of PyWren to process large amount of data from the Amazon Public datasets, achieving high throughput on Amazon S3, triggered straight from your laptop.
Amazon DynamoDB Deep Dive Advanced Design Patterns for DynamoDB (DAT401) - AW...Amazon Web Services
This session is for those who already have some familiarity with DynamoDB. The patterns and data models discussed in this session summarize a collection of implementations and best practices leveraged by Amazon.com to deliver highly scalable solutions for a wide variety of business problems. The session also covers strategies for global secondary index sharding and index overloading, scalable graph processing with materialized queries, relational modeling with composite keys, and executing transactional workflows on DynamoDB.
Streaming data ingestion and near real-time analysis gives you immediate insights into your data. By using AWS Lambda with Amazon Kinesis, you can obtain these insights without the need to manage servers. But are you doing this in the most optimal way? In this interactive session, we review the best practices for using Lambda with Kinesis, and how to avoid common pitfalls.
In this presentation, Leo Dirac, Principal Engineer inspires you to think big. He starts by explaining some deep learning concepts and sharing some results that we achieved at Amazon.This was a Tech Talk delivered in July 2017.
Data Warehousing and Data Lake Analytics, Together - AWS Online Tech TalksAmazon Web Services
Learning Objectives:
- Learn how to discover and prepare your data lake for analytics
- See how you can query across your data warehouse and data lake without moving data
- Understand use cases that give you freedom to store data where you want and analyze it when you need it
ABD307_Deep Analytics for Global AWS Marketing OrganizationAmazon Web Services
To meet the needs of the global marketing organization, the AWS marketing analytics team built a scalable platform that allows the data science team to deliver custom econometric and machine learning models for end user self-service. To meet data security standards, we use end-to-end data encryption and different AWS services such as Amazon Redshift, Amazon RDS, Amazon S3, Amazon EMR with Apache Spark and Auto Scaling. In this session, you see real examples of how we have scaled and automated critical analysis, such as calculating the impact of marketing programs like re:Invent and prioritizing leads for our sales teams.
Real-time Analytics using Data from IoT Devices - AWS Online Tech TalksAmazon Web Services
Learning Objectives:
- Learn the different options available to stream data from IoT sensors to AWS
- Understand how to architect an analytics solution using AWS services to ingest and process IoT data
- Take away best practices for building IoT applications with scalability, cost-effectiveness, and security
GAM310_Build a Telemetry and Analytics Pipeline for Game BalancingAmazon Web Services
In this workshop, we will together build telemetry/analytics data processing pipelines to assist game developers/architects, designers and producers. We will use a fictitious RPG and ingest data from in-game events. We will then analyze the data to help with game balancing, troubleshooting and other relevant recommendations for game developers and designers. As a participant, you will use Amazon Kinesis, Amazon Kinesis Firehose, Amazon Analytics, Amazon EMR, Amazon Redshift, Amazon S3, Amazon Athena and Amazon QuickSight. Prerequisites include having your own laptop and an interest in big data services, game data processing & analytics.
In order to make your time in the workshop as productive as possible, please make sure to check out the additional information below.
AWS account: Fully functional AWS Account with administrative access. Participant should have the ability to create & destroy resources in the us-west-2 and eu-west-1 regions via API, CLI & AWS Console.
Device/OS: A laptop computer – running Mac OS X, a Linux flavor or Windows. The computer will need a functional ssh/Remote Desktop client.
AWS service familiarity/experience:Familiarity/Experience with EC2, S3 & the AWS Console will be good. For the rest of the services, we will introduce each during the workshop.
Audience: Game Developers (server programmers), Architects, Game Producers/Designers, Game Marketing/Analytics team – hands-on members
How Nextdoor Built a Scalable, Serverless Data Pipeline for Billions of Event...Amazon Web Services
In this session, learn how Nextdoor replaced their home-grown data pipeline based on a topology of Flume nodes with a completely serverless architecture based on Kinesis and Lambda. By making these changes, they improved both the reliability of their data and the delivery times of billions of records of data to their Amazon S3–based data lake and Amazon Redshift cluster. Nextdoor is a private social networking service for neighborhoods.
FSV305-Optimizing Payments Collections with Containers and Machine LearningAmazon Web Services
The Bank of Nova Scotia is using deep learning to improve the way it manages payments collections for its millions of credit card customers. In this session, we will show how the Bank of Nova Scotia leveraged Amazon EC2 Container Service and EC2 Container Registry and Docker to streamline their deployment pipeline. We will also cover how the bank used AWS IAM and Amazon S3 for asset management and security, as well as AWS GPU accelerated instances and TensorFlow to develop a retail risk model. We will conclude the session by examining how the Bank of Nova Scotia was able to dramatically cut costs in comparison to on-premise development.
Building mobile apps that can automatically scale globally to millions of use...AWS Germany
AWS provides purpose-built tools with purpose-built database solutions for builders. In this session, we looked at the the scalable key-value storage of DynamoDB, the submilli second speed of ElastiCache for Redis, the relationship graph transversals of Neptune, and the search power of Elasticsearch and build mobile applications that use them. https://aws.amazon.com/products/databases/
Similar to Advanced Design Patterns for Amazon DynamoDB - DAT403 - re:Invent 2017 (20)
Come costruire servizi di Forecasting sfruttando algoritmi di ML e deep learn...Amazon Web Services
Il Forecasting è un processo importante per tantissime aziende e viene utilizzato in vari ambiti per cercare di prevedere in modo accurato la crescita e distribuzione di un prodotto, l’utilizzo delle risorse necessarie nelle linee produttive, presentazioni finanziarie e tanto altro. Amazon utilizza delle tecniche avanzate di forecasting, in parte questi servizi sono stati messi a disposizione di tutti i clienti AWS.
In questa sessione illustreremo come pre-processare i dati che contengono una componente temporale e successivamente utilizzare un algoritmo che a partire dal tipo di dato analizzato produce un forecasting accurato.
Big Data per le Startup: come creare applicazioni Big Data in modalità Server...Amazon Web Services
La varietà e la quantità di dati che si crea ogni giorno accelera sempre più velocemente e rappresenta una opportunità irripetibile per innovare e creare nuove startup.
Tuttavia gestire grandi quantità di dati può apparire complesso: creare cluster Big Data su larga scala sembra essere un investimento accessibile solo ad aziende consolidate. Ma l’elasticità del Cloud e, in particolare, i servizi Serverless ci permettono di rompere questi limiti.
Vediamo quindi come è possibile sviluppare applicazioni Big Data rapidamente, senza preoccuparci dell’infrastruttura, ma dedicando tutte le risorse allo sviluppo delle nostre le nostre idee per creare prodotti innovativi.
Ora puoi utilizzare Amazon Elastic Kubernetes Service (EKS) per eseguire pod Kubernetes su AWS Fargate, il motore di elaborazione serverless creato per container su AWS. Questo rende più semplice che mai costruire ed eseguire le tue applicazioni Kubernetes nel cloud AWS.In questa sessione presenteremo le caratteristiche principali del servizio e come distribuire la tua applicazione in pochi passaggi
Vent'anni fa Amazon ha attraversato una trasformazione radicale con l'obiettivo di aumentare il ritmo dell'innovazione. In questo periodo abbiamo imparato come cambiare il nostro approccio allo sviluppo delle applicazioni ci ha permesso di aumentare notevolmente l'agilità, la velocità di rilascio e, in definitiva, ci ha consentito di creare applicazioni più affidabili e scalabili. In questa sessione illustreremo come definiamo le applicazioni moderne e come la creazione di app moderne influisce non solo sull'architettura dell'applicazione, ma sulla struttura organizzativa, sulle pipeline di rilascio dello sviluppo e persino sul modello operativo. Descriveremo anche approcci comuni alla modernizzazione, compreso l'approccio utilizzato dalla stessa Amazon.com.
Come spendere fino al 90% in meno con i container e le istanze spot Amazon Web Services
L’utilizzo dei container è in continua crescita.
Se correttamente disegnate, le applicazioni basate su Container sono molto spesso stateless e flessibili.
I servizi AWS ECS, EKS e Kubernetes su EC2 possono sfruttare le istanze Spot, portando ad un risparmio medio del 70% rispetto alle istanze On Demand. In questa sessione scopriremo insieme quali sono le caratteristiche delle istanze Spot e come possono essere utilizzate facilmente su AWS. Impareremo inoltre come Spreaker sfrutta le istanze spot per eseguire applicazioni di diverso tipo, in produzione, ad una frazione del costo on-demand!
In recent months, many customers have been asking us the question – how to monetise Open APIs, simplify Fintech integrations and accelerate adoption of various Open Banking business models. Therefore, AWS and FinConecta would like to invite you to Open Finance marketplace presentation on October 20th.
Event Agenda :
Open banking so far (short recap)
• PSD2, OB UK, OB Australia, OB LATAM, OB Israel
Intro to Open Finance marketplace
• Scope
• Features
• Tech overview and Demo
The role of the Cloud
The Future of APIs
• Complying with regulation
• Monetizing data / APIs
• Business models
• Time to market
One platform for all: a Strategic approach
Q&A
Rendi unica l’offerta della tua startup sul mercato con i servizi Machine Lea...Amazon Web Services
Per creare valore e costruire una propria offerta differenziante e riconoscibile, le startup di successo sanno come combinare tecnologie consolidate con componenti innovativi creati ad hoc.
AWS fornisce servizi pronti all'utilizzo e, allo stesso tempo, permette di personalizzare e creare gli elementi differenzianti della propria offerta.
Concentrandoci sulle tecnologie di Machine Learning, vedremo come selezionare i servizi di intelligenza artificiale offerti da AWS e, anche attraverso una demo, come costruire modelli di Machine Learning personalizzati utilizzando SageMaker Studio.
OpsWorks Configuration Management: automatizza la gestione e i deployment del...Amazon Web Services
Con l'approccio tradizionale al mondo IT per molti anni è stato difficile implementare tecniche di DevOps, che finora spesso hanno previsto attività manuali portando di tanto in tanto a dei downtime degli applicativi interrompendo l'operatività dell'utente. Con l'avvento del cloud, le tecniche di DevOps sono ormai a portata di tutti a basso costo per qualsiasi genere di workload, garantendo maggiore affidabilità del sistema e risultando in dei significativi miglioramenti della business continuity.
AWS mette a disposizione AWS OpsWork come strumento di Configuration Management che mira ad automatizzare e semplificare la gestione e i deployment delle istanze EC2 per mezzo di workload Chef e Puppet.
Scopri come sfruttare AWS OpsWork a garanzia e affidabilità del tuo applicativo installato su Instanze EC2.
Microsoft Active Directory su AWS per supportare i tuoi Windows WorkloadsAmazon Web Services
Vuoi conoscere le opzioni per eseguire Microsoft Active Directory su AWS? Quando si spostano carichi di lavoro Microsoft in AWS, è importante considerare come distribuire Microsoft Active Directory per supportare la gestione, l'autenticazione e l'autorizzazione dei criteri di gruppo. In questa sessione, discuteremo le opzioni per la distribuzione di Microsoft Active Directory su AWS, incluso AWS Directory Service per Microsoft Active Directory e la distribuzione di Active Directory su Windows su Amazon Elastic Compute Cloud (Amazon EC2). Trattiamo argomenti quali l'integrazione del tuo ambiente Microsoft Active Directory locale nel cloud e l'utilizzo di applicazioni SaaS, come Office 365, con AWS Single Sign-On.
Dal riconoscimento facciale al riconoscimento di frodi o difetti di fabbricazione, l'analisi di immagini e video che sfruttano tecniche di intelligenza artificiale, si stanno evolvendo e raffinando a ritmi elevati. In questo webinar esploreremo le possibilità messe a disposizione dai servizi AWS per applicare lo stato dell'arte delle tecniche di computer vision a scenari reali.
Amazon Web Services e VMware organizzano un evento virtuale gratuito il prossimo mercoledì 14 Ottobre dalle 12:00 alle 13:00 dedicato a VMware Cloud ™ on AWS, il servizio on demand che consente di eseguire applicazioni in ambienti cloud basati su VMware vSphere® e di accedere ad una vasta gamma di servizi AWS, sfruttando a pieno le potenzialità del cloud AWS e tutelando gli investimenti VMware esistenti.
Molte organizzazioni sfruttano i vantaggi del cloud migrando i propri carichi di lavoro Oracle e assicurandosi notevoli vantaggi in termini di agilità ed efficienza dei costi.
La migrazione di questi carichi di lavoro, può creare complessità durante la modernizzazione e il refactoring delle applicazioni e a questo si possono aggiungere rischi di prestazione che possono essere introdotti quando si spostano le applicazioni dai data center locali.
Crea la tua prima serverless ledger-based app con QLDB e NodeJSAmazon Web Services
Molte aziende oggi, costruiscono applicazioni con funzionalità di tipo ledger ad esempio per verificare lo storico di accrediti o addebiti nelle transazioni bancarie o ancora per tenere traccia del flusso supply chain dei propri prodotti.
Alla base di queste soluzioni ci sono i database ledger che permettono di avere un log delle transazioni trasparente, immutabile e crittograficamente verificabile, ma sono strumenti complessi e onerosi da gestire.
Amazon QLDB elimina la necessità di costruire sistemi personalizzati e complessi fornendo un database ledger serverless completamente gestito.
In questa sessione scopriremo come realizzare un'applicazione serverless completa che utilizzi le funzionalità di QLDB.
Con l’ascesa delle architetture di microservizi e delle ricche applicazioni mobili e Web, le API sono più importanti che mai per offrire agli utenti finali una user experience eccezionale. In questa sessione impareremo come affrontare le moderne sfide di progettazione delle API con GraphQL, un linguaggio di query API open source utilizzato da Facebook, Amazon e altro e come utilizzare AWS AppSync, un servizio GraphQL serverless gestito su AWS. Approfondiremo diversi scenari, comprendendo come AppSync può aiutare a risolvere questi casi d’uso creando API moderne con funzionalità di aggiornamento dati in tempo reale e offline.
Inoltre, impareremo come Sky Italia utilizza AWS AppSync per fornire aggiornamenti sportivi in tempo reale agli utenti del proprio portale web.
Database Oracle e VMware Cloud™ on AWS: i miti da sfatareAmazon Web Services
Molte organizzazioni sfruttano i vantaggi del cloud migrando i propri carichi di lavoro Oracle e assicurandosi notevoli vantaggi in termini di agilità ed efficienza dei costi.
La migrazione di questi carichi di lavoro, può creare complessità durante la modernizzazione e il refactoring delle applicazioni e a questo si possono aggiungere rischi di prestazione che possono essere introdotti quando si spostano le applicazioni dai data center locali.
In queste slide, gli esperti AWS e VMware presentano semplici e pratici accorgimenti per facilitare e semplificare la migrazione dei carichi di lavoro Oracle accelerando la trasformazione verso il cloud, approfondiranno l’architettura e dimostreranno come sfruttare a pieno le potenzialità di VMware Cloud ™ on AWS.
Amazon Elastic Container Service (Amazon ECS) è un servizio di gestione dei container altamente scalabile, che semplifica la gestione dei contenitori Docker attraverso un layer di orchestrazione per il controllo del deployment e del relativo lifecycle. In questa sessione presenteremo le principali caratteristiche del servizio, le architetture di riferimento per i differenti carichi di lavoro e i semplici passi necessari per poter velocemente migrare uno o più dei tuo container.
60. • Partition table on node ID, add
edges to define adjacency list
• Define a default edge for every
node type to describe the node
itself
• Use partitioned GSIs to query large
nodes (dates, places, etc.)
• Use Dynamo DB
Streams/Lambda/EMR for graph
query projections
• Neighbor entity state
• Subtree aggregations
• Breadth first search
• Node ranking
Adjacency lists and materialized graphs
GSI Primary Key Attributes
GSIkey Data Target Type Node Projection
0-N
Jason Bourne 1
Person
1 …
James John Doe 4 4 …
20170418 2
Birthdate
1 …
4 …
Date 2 …
Finland 3
Birthplace
1 …
4 …
Place 3 …
GSI Primary Key Attributes
GSIkey Type Target Data Node Projection
0-N
Person
1 Jason Bourne 1 …
4 John Doe 4 …
Birthdate 2 20170418
1 …
4 …
Birthplace 3 Finland
1 …
4 …
Date 2 20170418 2 …
Place 3 Finland 3 …
Table Primary Key Attributes
Node Type Target Data GSIkey Projection
1
Person 1 Jason Bourne
HASH(Person.Data)
Edge/spanning
tree rollups
Birthdate 2 20170418
Birthplace 3 Finland
2 Date 2 20170418
HASH(Data) (Summary Stats)
3 Place 3 Finland
4
Person 4 John Doe
HASH(Person.Data
Edge/spanning
tree rollups
Birthdate 2 20170418
Birthplace 3 Finland