The document discusses optimizing data lakes with Amazon S3. It describes how Epic Games uses Amazon S3 as a data lake to collect telemetry data from Fortnite players with Amazon Kinesis and performs real-time analytics with Spark on EMR and queries with DynamoDB. Game designers then use the data to inform decisions about improving gamer engagement.
Analyzing and processing streaming data with Amazon EMR - ADB204 - New York A...Amazon Web Services
Customers regularly use Apache Spark running on Amazon EMR to process large amounts of data. As time to insight and the ability to act quickly based on those insights become core differentiators for customers, there is a greater need to be able to analyze data in real time. In this session, we teach you several design patterns to process and analyze real-time streaming data using Amazon EMR and Amazon Kinesis data services.
Make your data move: Best practices for migrating data to AWS - STG201 - New ...Amazon Web Services
The prospect of moving data to the cloud can be daunting, and making sense of all of the services, tools, and protocols available to do it can be difficult. In this session, learn how to get started moving data into AWS efficiently and securely. We show you online and offline data transfer methods, including AWS DataSync, AWS Transfer for SFTP, and the AWS Snow family, and identify practical use cases to help you select the right service for your needs. This session also includes a live demo of AWS DataSync.
Performing serverless analytics in AWS Glue - ADB202 - Chicago AWS SummitAmazon Web Services
The document discusses serverless analytics using AWS Glue. It provides an overview of AWS Glue, describing how it uses Apache Spark and Python shells to enable serverless data science and analytics. It also discusses how AWS Glue supports data discovery, preparation, and orchestration of analytics workflows through its crawlers, data catalog, notebooks, and orchestration capabilities. Customer examples are given that demonstrate how AWS Glue allows cost-effective and scalable serverless analytics without operational overhead.
AWS CloudFormation macros: Coding best practices - MAD201 - New York AWS SummitAmazon Web Services
With AWS CloudFormation macros, infrastructure-as-code developers can use AWS Lambda functions to empower template authors with utilities to improve their productivity. In this session, we review example use cases to teach you best practices when writing macros. You also learn deployment strategies so your teams can make the most of this functionality.
Running Amazon EC2 workloads at scale - CMP301 - New York AWS SummitAmazon Web Services
Amazon EC2 Fleet makes it easy to optimize compute performance and cost by blending EC2 Spot, On-Demand, and RI purchasing models. In this session, learn how to use the power of EC2 Fleet with AWS services, such as AWS Auto Scaling, Amazon ECS, Amazon EKS, Amazon EMR, AWS Batch, AWS Thinkbox Deadline, and AWS OpsWorks, to programmatically optimize costs while maintaining high performance and availability. We also cover cost optimization patterns for workloads such as containers, web services, CI/CD, and big data.
Soluzioni per la migrazione e gestione dei dati in Amazon Web ServicesAmazon Web Services
AWS Summit Milano 2019 - Soluzioni per la migrazione e gestione dei dati in Amazon Web Services - Antonio Aga Rossi, Global Accounts Solutions Architect, AWS
Manage your database in the cloud like a pro with Cloud Volumes Service for A...Amazon Web Services
Cloud adoption among enterprises is rapidly growing, with many companies adopting a cloud-first strategy for new projects and migrating their existing systems to AWS. Oracle workloads are mission-critical for most enterprises and figure prominently in planning for cloud migration. If you're looking to offload many of the standard database and infrastructure management tasks, consider a fully managed service from NetApp as a one-stop storage solution that can handle Oracle databases. In this talk, learn about important considerations when running databases on the cloud, such as meeting fluctuating performance demands. Also learn how to control costs, get guaranteed SLAs, and continually keep your data protected. This presentation is brought to you by AWS partner, NetApp.
Migrate a relational database to Aurora - ADB302 - Atlanta AWS SummitAmazon Web Services
In this hands-on lab, you use AWS Schema Conversion Tool and AWS Database Migration Service to migrate a relational database to Amazon Aurora PostgreSQL. Bring a laptop that has the Firefox or Chrome browser installed and a working AWS account. We provide an AWS CloudFormation template to configure the lab environment and help you walk through the migration process. Please be sure to bring your laptop.
Analyzing and processing streaming data with Amazon EMR - ADB204 - New York A...Amazon Web Services
Customers regularly use Apache Spark running on Amazon EMR to process large amounts of data. As time to insight and the ability to act quickly based on those insights become core differentiators for customers, there is a greater need to be able to analyze data in real time. In this session, we teach you several design patterns to process and analyze real-time streaming data using Amazon EMR and Amazon Kinesis data services.
Make your data move: Best practices for migrating data to AWS - STG201 - New ...Amazon Web Services
The prospect of moving data to the cloud can be daunting, and making sense of all of the services, tools, and protocols available to do it can be difficult. In this session, learn how to get started moving data into AWS efficiently and securely. We show you online and offline data transfer methods, including AWS DataSync, AWS Transfer for SFTP, and the AWS Snow family, and identify practical use cases to help you select the right service for your needs. This session also includes a live demo of AWS DataSync.
Performing serverless analytics in AWS Glue - ADB202 - Chicago AWS SummitAmazon Web Services
The document discusses serverless analytics using AWS Glue. It provides an overview of AWS Glue, describing how it uses Apache Spark and Python shells to enable serverless data science and analytics. It also discusses how AWS Glue supports data discovery, preparation, and orchestration of analytics workflows through its crawlers, data catalog, notebooks, and orchestration capabilities. Customer examples are given that demonstrate how AWS Glue allows cost-effective and scalable serverless analytics without operational overhead.
AWS CloudFormation macros: Coding best practices - MAD201 - New York AWS SummitAmazon Web Services
With AWS CloudFormation macros, infrastructure-as-code developers can use AWS Lambda functions to empower template authors with utilities to improve their productivity. In this session, we review example use cases to teach you best practices when writing macros. You also learn deployment strategies so your teams can make the most of this functionality.
Running Amazon EC2 workloads at scale - CMP301 - New York AWS SummitAmazon Web Services
Amazon EC2 Fleet makes it easy to optimize compute performance and cost by blending EC2 Spot, On-Demand, and RI purchasing models. In this session, learn how to use the power of EC2 Fleet with AWS services, such as AWS Auto Scaling, Amazon ECS, Amazon EKS, Amazon EMR, AWS Batch, AWS Thinkbox Deadline, and AWS OpsWorks, to programmatically optimize costs while maintaining high performance and availability. We also cover cost optimization patterns for workloads such as containers, web services, CI/CD, and big data.
Soluzioni per la migrazione e gestione dei dati in Amazon Web ServicesAmazon Web Services
AWS Summit Milano 2019 - Soluzioni per la migrazione e gestione dei dati in Amazon Web Services - Antonio Aga Rossi, Global Accounts Solutions Architect, AWS
Manage your database in the cloud like a pro with Cloud Volumes Service for A...Amazon Web Services
Cloud adoption among enterprises is rapidly growing, with many companies adopting a cloud-first strategy for new projects and migrating their existing systems to AWS. Oracle workloads are mission-critical for most enterprises and figure prominently in planning for cloud migration. If you're looking to offload many of the standard database and infrastructure management tasks, consider a fully managed service from NetApp as a one-stop storage solution that can handle Oracle databases. In this talk, learn about important considerations when running databases on the cloud, such as meeting fluctuating performance demands. Also learn how to control costs, get guaranteed SLAs, and continually keep your data protected. This presentation is brought to you by AWS partner, NetApp.
Migrate a relational database to Aurora - ADB302 - Atlanta AWS SummitAmazon Web Services
In this hands-on lab, you use AWS Schema Conversion Tool and AWS Database Migration Service to migrate a relational database to Amazon Aurora PostgreSQL. Bring a laptop that has the Firefox or Chrome browser installed and a working AWS account. We provide an AWS CloudFormation template to configure the lab environment and help you walk through the migration process. Please be sure to bring your laptop.
Using automation to drive continuous-compliance best practices - SEC208 - New...Amazon Web Services
Northwestern Mutual’s technology teams maintain a complex compliance environment for a diverse set of developers working within more than 100 AWS accounts. To drive best practices and ensure continuous compliance, the teams designed an AWS-based architecture using services such as AWS Lambda, Amazon DynamoDB, Amazon Simple Queue Service (Amazon SQS), and Amazon CloudWatch to auto-remediate misconfigurations. In this session, learn how these services help Northwestern Mutual swiftly correct configurations and integrate with tools like Slack and PagerDuty to create logs, notify developers and account owners of changes, and track trends in remediation.
Modernize your data warehouse with Amazon Redshift - ADB305 - New York AWS Su...Amazon Web Services
Can you set up a data warehouse and create a dashboard in less than 60 minutes? You can with Amazon Redshift, a fully managed cloud data warehouse that provides first-rate performance at a low cost. In this workshop, you learn the steps and best practices to deploy your data warehouse in your organization. You also see how to query across petabytes of data in your data warehouse and exabytes of data in your Amazon S3 data lake. Finally, you learn how to easily migrate from traditional or on-premises data warehouses.
Deep dive on Amazon S3 Glacier Deep Archive - STG301 - Santa Clara AWS SummitAmazon Web Services
The document discusses Amazon S3 Glacier Deep Archive, a new storage class for long-term archive of data. It provides details on how to use Deep Archive including ingesting data via PUT, COPY, cross-region replication and lifecycles. It also discusses retrieval processes and costs. Deep Archive offers the lowest cost for storage, at $0.00099 per GB-month, but has minimum 180 day retrieval times versus hours for regular Glacier.
What's new in Amazon Aurora - ADB207 - New York AWS SummitAmazon Web Services
Amazon Aurora is a fully managed relational database that runs on Amazon RDS and offers versions compatible with MySQL and PostgreSQL. Aurora provides the speed, reliability, and availability of commercial databases at a fraction of the cost and is faster than standard MySQL and PostgreSQL databases. In this session, we provide an overview of Aurora, exploring recently announced features, such as serverless, multi-master, and performance insights. We also discuss what you need to get your organization started with Aurora.
The document provides an overview of Amazon Web Services (AWS) and its core infrastructure and services. It describes AWS's global infrastructure including regions, availability zones, and edge locations. It also outlines AWS's core services such as compute, storage, database, and networking services. Finally, it summarizes AWS's approach to security including its shared responsibility model and built-in security features.
Resiliency-and-Availability-Design-Patterns-for-the-CloudAmazon Web Services
We have traditionally built robust software systems by trying to avoid mistakes and by dodging failures when they occur in production or by testing parts of the system in isolation from one another. Modern methods and techniques take a very different approach based on resiliency, which promotes embracing failure instead of trying to avoid it. Resilient architectures enhance observability, leverage well-known patterns such as graceful degradation, timeouts and circuit breakers. In this session, will review the most useful patterns for building resilient software systems and especially show the audience how they can benefit from the patterns.
“Lift and shift” storage for business-critical applications - STG203 - New Yo...Amazon Web Services
Among your company’s top priorities should be ensuring that its data is safely and securely persisted. But beyond data integrity, you also need to ensure availability. In this session, learn best practices for AWS block and file storage when supporting business-critical applications such as SAP HANA, Oracle RAC, Microsoft SQL Server, MySQL, Cassandra, and home directories. We discuss migrating mission-critical workload data, selecting volumes or file systems, maximizing performance, and designing for durability and availability. You also learn how to optimize for cost to make sure your “lift and shift” project is a complete success.
Need for Speed – Intro To Real-Time Data Streaming Analytics on AWS | AWS Sum...AWS Summits
AWS provides multiple ways to ingest and process real-time data generated from sources such as Edge device, logs, websites, mobile apps, IoT devices and more.
In this session we will compare the different tools and technologies and share best practices for when to use what.
The session will cover: Apache Kafka, Kinesis Data Streams/Firehose, MSK (Managed Kafka), Kinesis Data Analytics for SQL and Java (Flink), Apache Spark and more.
The document discusses how MobiX Corp, an e-commerce company in Taiwan, transitioned their infrastructure to use Amazon ECS and containers to address challenges from their rapid growth. As MobiX launched new brands and saw traffic fluctuations, managing servers became difficult. They moved applications into containers and used ECS for automated scaling and deployment. This simplified operations and allowed scaling without adding complexity. ECS task placement strategies helped optimize resource usage across the cluster. MobiX now has a flexible and low cost architecture that can easily expand.
Journey into the Cloud with VMware Cloud on AWS: Deep Dive - CMP303 - Anaheim...Amazon Web Services
Customers use VMware Cloud on AWS to accelerate cloud migrations, deploy hybrid architectures, and replace their DR environments. VMware Cloud on AWS offers the opportunity to augment and evolve existing and legacy applications. Learn how VMware Cloud on AWS can help build a lower-risk and iterative transformation approach to your traditional applications and data in a hybrid environment. Also learn best practices for protecting and scaling your workload by natively integrating AWS services, such as AWS Direct Connect, Amazon S3, Amazon RDS, and Elastic Load Balancing. Learn how to bring your entire IT landscape closer to your digital innovation goals.
Certificate management concepts in AWS - SEC205 - New York AWS SummitAmazon Web Services
In this session, learn about the encryption and certificate management services that AWS offers. You also get to see a few demonstrations of how you can leverage these services on AWS to protect data at rest and data in transit.
Introducing Open Distro for Elasticsearch - ADB201 - New York AWS SummitAmazon Web Services
Open Distro for Elasticsearch is a 100% open-source distribution of Elasticsearch, the popular search and analytics engine. In this session, we explore its many new advanced features—previously available only in commercial software—including encryption in transit, role-based access control (RBAC), event monitoring and alerting, SQL support, cluster diagnostics, and more. We also show you how you can join the Open Distro for Elasticsearch community to accelerate open innovation for Elasticsearch.
High-Performance-Computing-on-AWS-and-Industry-SimulationAmazon Web Services
High Performance Computing on AWS enables engineers, analysts, and researchers to think beyond the limitations of on-premises HPC infrastructure. AWS HPC solutions address the infrastructure capacity, secure global collaboration, technology obsolescence, and capital expenditure constraints associated with on-premises HPC clusters to give you the freedom to tackle the most challenging HPC workloads and get to your results faster. In this session. we will provide a quick overview of the services that make up the HPC on AWS solution, and share customer success stories across multiple industries, such as Financial Services and Life Sciences.
Accelerate database development and testing with Amazon Aurora - ADB208 - New...Amazon Web Services
Build faster, more scalable database applications with Amazon Aurora, a MySQL- and PostgreSQL-compatible relational database built for the cloud. We cover Aurora Serverless, which automatically scales your database up and down to meet demand; Fast Database Cloning, which makes data instantly available for application development; Backtrack, which rolls back your database between test runs; and Performance Insights, which helps assess the load on your database and optimize your SQL queries.
Drive innovation in Financial Services with Amazon EC2 - CMP204 - New York AW...Amazon Web Services
The landscape of the Financial Services industry is changing through new types of risks, an explosion of data, and evolving customer expectations. Join this session to learn how compute solutions powered by Amazon EC2 are helping financial services companies drive innovation and transform their businesses. We highlight how financial services companies are leveraging machine learning and grid computing to minimize risk, optimize investments, and meet customer demands. We also cover how AWS Outposts extends the AWS Cloud on-premises for a consistent hybrid cloud experience.
Connecting your devices at scale, ft. Discovery - SVC205 - New York AWS SummitAmazon Web Services
AWS IoT Core is a managed cloud service that lets connected devices easily and securely interact with cloud applications and other devices. In this session, we discuss how AWS IoT Core can help you securely connect and manage devices, process and act on device data, and read and set device state. We are also joined by Discovery, which has built a data pipeline—a special-purpose, highly scalable, performant, flexible publish-subscribe system designed to collect, store, stream, and query events—built entirely on AWS. A representative from Discovery discusses how the company used AWS IoT Core to substantially improve subscriber integrations.
Everything You Need to Know About Big Data: From Architectural Principles to ...Amazon Web Services
In this session, we discuss architectural principles that help simplify big data analytics. We'll apply principles to various stages of big data processing: collect, store, process, analyze, and visualize. We'll discuss how to choose the right technology in each stage based on criteria such as data structure, query latency, cost, request rate, item size, data volume, durability, and so on. Finally, we provide reference architectures, design patterns, and best practices for assembling these technologies to solve your big data problems at the right cost.
Solutions for Storage and Data Migrations | AWS Summit Tel Aviv 2019AWS Summits
Objects? File Systems? Block? Hybrid? Let's talk about AWS' storage solutions, starting from ways to migrate your data into AWS, through the different storage services AWS has to offer, alongside AWS's storage parterships.
Accelerating your Cloud Migration with VMware Cloud on AWS - SVC210 - Atlanta...Amazon Web Services
Customers are using VMware Cloud on AWS to accelerate cloud migrations, deploy hybrid architectures, and replace their disaster recovery environments. VMware Cloud on AWS brings a new dimension of hybrid cloud and mixed architecture to many customers, offering the opportunity for augmenting and evolving existing and legacy applications. Learn how VMware Cloud on AWS helps build a lower-risk and iterative transformation approach to your traditional applications and data in a hybrid environment. Also learn best practices to protect and scale your workload by natively integrating AWS services, such as AWS Direct Connect, Amazon S3, Amazon RDS, and Elastic Load Balancing.
Optimize data lakes with Amazon S3 - STG302 - Santa Clara AWS SummitAmazon Web Services
In this session, AWS experts dive into the benefits of Amazon S3 that customers are leveraging to build and manage their data lakes in the AWS Cloud. Learn about the Amazon S3 integrations with the AWS analytics suite and Amazon FSx for Lustre. Learn how to seamlessly run big data analytics, high performance computing applications, machine learning training models, and media data processing workloads across your Amazon S3 data lakes. We also cover the range of features that enable you to manage data with object-level granularity, configure and enforce finely tuned access policies, make changes to billions of objects with just a few clicks, enable cost efficiencies with the S3 storage classes, and audit and report on your data and Amazon S3 activities across your entire data lake.
AWS Portfolio: highlight delle categorie di prodotti AWS con esempiAmazon Web Services
The document discusses Amazon Web Services (AWS) and its various cloud computing products and services. It provides information on AWS' global infrastructure including 21 regions, 64 availability zones, and 158 edge locations. It also describes compute services such as EC2 instances, containers, and serverless functions. Additional sections cover database services, storage options, data transfer mechanisms, analytics and machine learning tools, and specific AI services for image and text recognition.
Using automation to drive continuous-compliance best practices - SEC208 - New...Amazon Web Services
Northwestern Mutual’s technology teams maintain a complex compliance environment for a diverse set of developers working within more than 100 AWS accounts. To drive best practices and ensure continuous compliance, the teams designed an AWS-based architecture using services such as AWS Lambda, Amazon DynamoDB, Amazon Simple Queue Service (Amazon SQS), and Amazon CloudWatch to auto-remediate misconfigurations. In this session, learn how these services help Northwestern Mutual swiftly correct configurations and integrate with tools like Slack and PagerDuty to create logs, notify developers and account owners of changes, and track trends in remediation.
Modernize your data warehouse with Amazon Redshift - ADB305 - New York AWS Su...Amazon Web Services
Can you set up a data warehouse and create a dashboard in less than 60 minutes? You can with Amazon Redshift, a fully managed cloud data warehouse that provides first-rate performance at a low cost. In this workshop, you learn the steps and best practices to deploy your data warehouse in your organization. You also see how to query across petabytes of data in your data warehouse and exabytes of data in your Amazon S3 data lake. Finally, you learn how to easily migrate from traditional or on-premises data warehouses.
Deep dive on Amazon S3 Glacier Deep Archive - STG301 - Santa Clara AWS SummitAmazon Web Services
The document discusses Amazon S3 Glacier Deep Archive, a new storage class for long-term archive of data. It provides details on how to use Deep Archive including ingesting data via PUT, COPY, cross-region replication and lifecycles. It also discusses retrieval processes and costs. Deep Archive offers the lowest cost for storage, at $0.00099 per GB-month, but has minimum 180 day retrieval times versus hours for regular Glacier.
What's new in Amazon Aurora - ADB207 - New York AWS SummitAmazon Web Services
Amazon Aurora is a fully managed relational database that runs on Amazon RDS and offers versions compatible with MySQL and PostgreSQL. Aurora provides the speed, reliability, and availability of commercial databases at a fraction of the cost and is faster than standard MySQL and PostgreSQL databases. In this session, we provide an overview of Aurora, exploring recently announced features, such as serverless, multi-master, and performance insights. We also discuss what you need to get your organization started with Aurora.
The document provides an overview of Amazon Web Services (AWS) and its core infrastructure and services. It describes AWS's global infrastructure including regions, availability zones, and edge locations. It also outlines AWS's core services such as compute, storage, database, and networking services. Finally, it summarizes AWS's approach to security including its shared responsibility model and built-in security features.
Resiliency-and-Availability-Design-Patterns-for-the-CloudAmazon Web Services
We have traditionally built robust software systems by trying to avoid mistakes and by dodging failures when they occur in production or by testing parts of the system in isolation from one another. Modern methods and techniques take a very different approach based on resiliency, which promotes embracing failure instead of trying to avoid it. Resilient architectures enhance observability, leverage well-known patterns such as graceful degradation, timeouts and circuit breakers. In this session, will review the most useful patterns for building resilient software systems and especially show the audience how they can benefit from the patterns.
“Lift and shift” storage for business-critical applications - STG203 - New Yo...Amazon Web Services
Among your company’s top priorities should be ensuring that its data is safely and securely persisted. But beyond data integrity, you also need to ensure availability. In this session, learn best practices for AWS block and file storage when supporting business-critical applications such as SAP HANA, Oracle RAC, Microsoft SQL Server, MySQL, Cassandra, and home directories. We discuss migrating mission-critical workload data, selecting volumes or file systems, maximizing performance, and designing for durability and availability. You also learn how to optimize for cost to make sure your “lift and shift” project is a complete success.
Need for Speed – Intro To Real-Time Data Streaming Analytics on AWS | AWS Sum...AWS Summits
AWS provides multiple ways to ingest and process real-time data generated from sources such as Edge device, logs, websites, mobile apps, IoT devices and more.
In this session we will compare the different tools and technologies and share best practices for when to use what.
The session will cover: Apache Kafka, Kinesis Data Streams/Firehose, MSK (Managed Kafka), Kinesis Data Analytics for SQL and Java (Flink), Apache Spark and more.
The document discusses how MobiX Corp, an e-commerce company in Taiwan, transitioned their infrastructure to use Amazon ECS and containers to address challenges from their rapid growth. As MobiX launched new brands and saw traffic fluctuations, managing servers became difficult. They moved applications into containers and used ECS for automated scaling and deployment. This simplified operations and allowed scaling without adding complexity. ECS task placement strategies helped optimize resource usage across the cluster. MobiX now has a flexible and low cost architecture that can easily expand.
Journey into the Cloud with VMware Cloud on AWS: Deep Dive - CMP303 - Anaheim...Amazon Web Services
Customers use VMware Cloud on AWS to accelerate cloud migrations, deploy hybrid architectures, and replace their DR environments. VMware Cloud on AWS offers the opportunity to augment and evolve existing and legacy applications. Learn how VMware Cloud on AWS can help build a lower-risk and iterative transformation approach to your traditional applications and data in a hybrid environment. Also learn best practices for protecting and scaling your workload by natively integrating AWS services, such as AWS Direct Connect, Amazon S3, Amazon RDS, and Elastic Load Balancing. Learn how to bring your entire IT landscape closer to your digital innovation goals.
Certificate management concepts in AWS - SEC205 - New York AWS SummitAmazon Web Services
In this session, learn about the encryption and certificate management services that AWS offers. You also get to see a few demonstrations of how you can leverage these services on AWS to protect data at rest and data in transit.
Introducing Open Distro for Elasticsearch - ADB201 - New York AWS SummitAmazon Web Services
Open Distro for Elasticsearch is a 100% open-source distribution of Elasticsearch, the popular search and analytics engine. In this session, we explore its many new advanced features—previously available only in commercial software—including encryption in transit, role-based access control (RBAC), event monitoring and alerting, SQL support, cluster diagnostics, and more. We also show you how you can join the Open Distro for Elasticsearch community to accelerate open innovation for Elasticsearch.
High-Performance-Computing-on-AWS-and-Industry-SimulationAmazon Web Services
High Performance Computing on AWS enables engineers, analysts, and researchers to think beyond the limitations of on-premises HPC infrastructure. AWS HPC solutions address the infrastructure capacity, secure global collaboration, technology obsolescence, and capital expenditure constraints associated with on-premises HPC clusters to give you the freedom to tackle the most challenging HPC workloads and get to your results faster. In this session. we will provide a quick overview of the services that make up the HPC on AWS solution, and share customer success stories across multiple industries, such as Financial Services and Life Sciences.
Accelerate database development and testing with Amazon Aurora - ADB208 - New...Amazon Web Services
Build faster, more scalable database applications with Amazon Aurora, a MySQL- and PostgreSQL-compatible relational database built for the cloud. We cover Aurora Serverless, which automatically scales your database up and down to meet demand; Fast Database Cloning, which makes data instantly available for application development; Backtrack, which rolls back your database between test runs; and Performance Insights, which helps assess the load on your database and optimize your SQL queries.
Drive innovation in Financial Services with Amazon EC2 - CMP204 - New York AW...Amazon Web Services
The landscape of the Financial Services industry is changing through new types of risks, an explosion of data, and evolving customer expectations. Join this session to learn how compute solutions powered by Amazon EC2 are helping financial services companies drive innovation and transform their businesses. We highlight how financial services companies are leveraging machine learning and grid computing to minimize risk, optimize investments, and meet customer demands. We also cover how AWS Outposts extends the AWS Cloud on-premises for a consistent hybrid cloud experience.
Connecting your devices at scale, ft. Discovery - SVC205 - New York AWS SummitAmazon Web Services
AWS IoT Core is a managed cloud service that lets connected devices easily and securely interact with cloud applications and other devices. In this session, we discuss how AWS IoT Core can help you securely connect and manage devices, process and act on device data, and read and set device state. We are also joined by Discovery, which has built a data pipeline—a special-purpose, highly scalable, performant, flexible publish-subscribe system designed to collect, store, stream, and query events—built entirely on AWS. A representative from Discovery discusses how the company used AWS IoT Core to substantially improve subscriber integrations.
Everything You Need to Know About Big Data: From Architectural Principles to ...Amazon Web Services
In this session, we discuss architectural principles that help simplify big data analytics. We'll apply principles to various stages of big data processing: collect, store, process, analyze, and visualize. We'll discuss how to choose the right technology in each stage based on criteria such as data structure, query latency, cost, request rate, item size, data volume, durability, and so on. Finally, we provide reference architectures, design patterns, and best practices for assembling these technologies to solve your big data problems at the right cost.
Solutions for Storage and Data Migrations | AWS Summit Tel Aviv 2019AWS Summits
Objects? File Systems? Block? Hybrid? Let's talk about AWS' storage solutions, starting from ways to migrate your data into AWS, through the different storage services AWS has to offer, alongside AWS's storage parterships.
Accelerating your Cloud Migration with VMware Cloud on AWS - SVC210 - Atlanta...Amazon Web Services
Customers are using VMware Cloud on AWS to accelerate cloud migrations, deploy hybrid architectures, and replace their disaster recovery environments. VMware Cloud on AWS brings a new dimension of hybrid cloud and mixed architecture to many customers, offering the opportunity for augmenting and evolving existing and legacy applications. Learn how VMware Cloud on AWS helps build a lower-risk and iterative transformation approach to your traditional applications and data in a hybrid environment. Also learn best practices to protect and scale your workload by natively integrating AWS services, such as AWS Direct Connect, Amazon S3, Amazon RDS, and Elastic Load Balancing.
Optimize data lakes with Amazon S3 - STG302 - Santa Clara AWS SummitAmazon Web Services
In this session, AWS experts dive into the benefits of Amazon S3 that customers are leveraging to build and manage their data lakes in the AWS Cloud. Learn about the Amazon S3 integrations with the AWS analytics suite and Amazon FSx for Lustre. Learn how to seamlessly run big data analytics, high performance computing applications, machine learning training models, and media data processing workloads across your Amazon S3 data lakes. We also cover the range of features that enable you to manage data with object-level granularity, configure and enforce finely tuned access policies, make changes to billions of objects with just a few clicks, enable cost efficiencies with the S3 storage classes, and audit and report on your data and Amazon S3 activities across your entire data lake.
AWS Portfolio: highlight delle categorie di prodotti AWS con esempiAmazon Web Services
The document discusses Amazon Web Services (AWS) and its various cloud computing products and services. It provides information on AWS' global infrastructure including 21 regions, 64 availability zones, and 158 edge locations. It also describes compute services such as EC2 instances, containers, and serverless functions. Additional sections cover database services, storage options, data transfer mechanisms, analytics and machine learning tools, and specific AI services for image and text recognition.
The document discusses building data lakes and analytics on AWS. It provides an overview of challenges posed by big data including volume, velocity, variety and veracity of data. It then describes how AWS services like S3, Glue and Athena can help address these challenges by allowing quick ingestion and storage of raw data in its original format. The document also discusses best practices for preparing and analyzing data in the lake using services like EMR, Redshift and SageMaker to derive insights and drive machine learning models.
The document discusses building data lakes and analytics on AWS. It provides an overview of challenges posed by big data including volume, velocity, variety and veracity of data. It then describes how AWS services like S3, Glue and Athena can help address these challenges by allowing quick ingestion and storage of raw data in its original format. The document also discusses best practices for preparing and analyzing data in the lake using services like EMR, Redshift and SageMaker to derive insights and drive machine learning models.
The document discusses building data lakes and analytics on AWS. It provides an overview of challenges with big data like increasing data variety and growth. It then describes how AWS services like S3, Glue, Athena, EMR, and Redshift can be used to address these challenges by enabling quick ingestion of diverse data types, metadata management, and running analytics tools on curated datasets. The document emphasizes storing raw data immutable and using tiered storage for cost optimization. It outlines using the right AWS service based on user roles and discusses how data lakes and data warehouses are complementary.
The document discusses big data analytics and machine learning on AWS. It describes what big data is and the 3Vs of big data - variety, velocity, and volume. It provides examples of AWS services that can be used for big data analytics like S3, Redshift, EMR, Athena, and Kinesis. It also provides examples of customers like Sysco, FINRA, and Nasdaq that are using AWS services to build data lakes and leverage big data analytics.
The document discusses building data lakes and analytics on AWS. It describes how data lakes extend the traditional approach of data warehousing by allowing storage and analysis of structured, semi-structured, and unstructured data at massive scales cost effectively. It provides an overview of various AWS services that can be used for data ingestion, storage, processing, analysis and machine learning with data lakes.
In this session, we show you how to understand what data you have, how to drive insights, and how to make predictions using purpose-built AWS services. Learn about the common pitfalls of building data lakes and discover how to successfully drive analytics and insights from your data. Also learn how services such as Amazon S3, AWS Glue, Amazon Redshift, Amazon Athena, Amazon EMR, Amazon Kinesis, and Amazon ML services work together to build a successful data lake for various roles, including data scientists and business users.
The document discusses data lake architectures on AWS. It defines a data lake as a centralized storage platform capable of storing heterogeneous data sets at virtually limitless scale. It describes how AWS services like S3, Glue, Athena, EMR, Redshift, and Kinesis can be used to build data lakes for storing, cataloging, processing, analyzing and gaining insights from large volumes of diverse data. Examples of using these services for clickstream analytics, real-time analytics, machine learning, and reducing total cost of ownership are also provided.
ABD201-Big Data Architectural Patterns and Best Practices on AWSAmazon Web Services
In this session, we simplify big data processing as a data bus comprising various stages: collect, store, process, analyze, and visualize. Next, we discuss how to choose the right technology in each stage based on criteria such as data structure, query latency, cost, request rate, item size, data volume, durability, and so on. Finally, we provide reference architectures, design patterns, and best practices for assembling these technologies to solve your big data problems at the right cost.
Build Data Lakes and Analytics on AWS: Patterns & Best PracticesAmazon Web Services
With over 90% of today’s data generated in the last two years, the rate of data growth is showing no sign of slowing down. In this session, we step through the challenges and best practices for capturing data, understanding what data you own, driving insights, and predicting the future using AWS services. We frame the session and demonstrations around common pitfalls of building data lakes and how to successfully drive analytics and insights from data. We also discuss the architecture patterns brought together key AWS services, including Amazon S3, AWS Glue, Amazon Athena, Amazon Kinesis, and Amazon Machine Learning. Discover the real-world application of data lakes for roles including data scientists and business users.
Stephen Moon, Sr. Solutions Architect, Amazon Web Services
James Juniper, Solution Architect for the Geo-Community Cloud, Natural Resources Canada
Build Data Lakes & Analytics on AWS: Patterns & Best PracticesAmazon Web Services
This document discusses building data lakes and analytics on AWS. It covers challenges with big data like volume, velocity, and variety. An AWS data lake can quickly ingest and store any type of data. The data lake includes analytics, machine learning, real-time data movement, and traditional data movement. Metadata management is important for data lakes. AWS Glue crawlers can discover data in various formats and populate the data catalog. Different tools like Amazon Athena, Amazon EMR, and Amazon Redshift can be used for analytics depending on the user and use case. Machine learning benefits from big data, and a data lake supports agility in machine learning.
The document discusses AWS Glue Data Catalog and Amazon Athena. It provides an overview of AWS Glue Data Catalog as a unified metadata repository across data sources. It then describes Amazon Athena as an interactive query service that allows users to analyze data stored in Amazon S3 using standard SQL. Various use cases are presented that demonstrate how customers can use AWS Glue Data Catalog and Amazon Athena together to build data lakes on AWS.
The document discusses AWS Glue Data Catalog and Amazon Athena. It provides an overview of AWS Glue Data Catalog as a unified metadata repository across data sources. It then describes Amazon Athena as an interactive query service that allows users to analyze data stored in Amazon S3 using standard SQL. Various use cases are presented that demonstrate how customers can use AWS Glue Data Catalog and Amazon Athena together to build data lakes and perform analytics on data stored in S3.
The document discusses data lakes on AWS. It describes how data lakes allow organizations to capture and analyze large amounts of structured and unstructured data at low costs. Key services for building data lakes on AWS include Amazon S3 for storage, AWS Glue for data cataloging and ETL, Amazon Athena for interactive querying, and Amazon QuickSight for visualization and analytics. The document outlines how these services provide scalable, secure, cost-effective solutions for data lakes that help organizations drive business value from their data.
This document discusses implementing a data lake on AWS to securely store, categorize, and analyze all types of data in a centralized repository. It describes key attributes of a data lake like decoupled storage and compute, rapid ingestion and transformation, and schema on read. It then outlines various AWS services that can be used to build a data lake like S3, Athena, EMR, Redshift, Glue, and Kinesis. It provides examples of streaming IoT data into a data lake and running queries and analytics on the data.
Value of Data Beyond Analytics by Darin BriskmanSameer Kenkare
The document discusses analytics capabilities provided by Amazon Web Services (AWS). It describes how AWS offers a variety of services for building data lakes, loading and querying data, and performing analytics. These services include Amazon S3, Amazon Redshift, Amazon Athena, Amazon EMR, and Amazon QuickSight. It also provides examples of how customers like Epic Games and a large media company use these AWS analytics services.
What's New with Amazon S3, Amazon EFS, and Other AWS Storage Services - STG20...Amazon Web Services
AWS provides storage services that fit any workload or application. In this session, we discuss each of the latest developments in Amazon S3, Amazon S3 Glacier, Amazon EBS, Amazon EFS, Amazon FSx for Windows File Server, Amazon FSx for Lustre, AWS Storage Gateway, the AWS Snow family, AWS Transfer for SFTP, and AWS DataSync. We also examine which workloads and applications are best suited to each storage service.
Discuss data migration with AWS experts - STG304 - Santa Clara AWS SummitAmazon Web Services
AWS offers a variety of data migration services and tools to help you move everything from gigabytes to petabytes of data using your networks, our networks, the mail, or even a tractor-trailer. We briefly cover a few key data migration services, including the AWS Snow family and AWS DataSync. We then engage in an interactive discussion about specific customer use cases to help you understand which technology is best for your needs. Come and join the discussion.
Modern data is massive, quickly evolving, unstructured, and increasingly hard to catalog and understand from multiple consumers and applications. This presentation will guide you though the best practices for designing a robust data architecture, highlightning the benefits and typical challenges of data lakes and data warehouses. We will build a scalable solution based on managed services such as Amazon Athena, AWS Glue, and AWS Lake Formation.
Similar to Optimizing data lakes with Amazon S3 - STG302 - New York AWS Summit (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.
1) The document discusses building a minimum viable product (MVP) using Amazon Web Services (AWS).
2) It provides an example of an MVP for an omni-channel messenger platform that was built from 2017 to connect ecommerce stores to customers via web chat, Facebook Messenger, WhatsApp, and other channels.
3) The founder discusses how they started with an MVP in 2017 with 200 ecommerce stores in Hong Kong and Taiwan, and have since expanded to over 5000 clients across Southeast Asia using AWS for scaling.
This document discusses pitch decks and fundraising materials. It explains that venture capitalists will typically spend only 3 minutes and 44 seconds reviewing a pitch deck. Therefore, the deck needs to tell a compelling story to grab their attention. It also provides tips on tailoring different types of decks for different purposes, such as creating a concise 1-2 page teaser, a presentation deck for pitching in-person, and a more detailed read-only or fundraising deck. The document stresses the importance of including key information like the problem, solution, product, traction, market size, plans, team, and ask.
This document discusses building serverless web applications using AWS services like API Gateway, Lambda, DynamoDB, S3 and Amplify. It provides an overview of each service and how they can work together to create a scalable, secure and cost-effective serverless application stack without having to manage servers or infrastructure. Key services covered include API Gateway for hosting APIs, Lambda for backend logic, DynamoDB for database needs, S3 for static content, and Amplify for frontend hosting and continuous deployment.
This document provides tips for fundraising from startup founders Roland Yau and Sze Lok Chan. It discusses generating competition to create urgency for investors, fundraising in parallel rather than sequentially, having a clear fundraising narrative focused on what you do and why it's compelling, and prioritizing relationships with people over firms. It also notes how the pandemic has changed fundraising, with examples of deals done virtually during this time. The tips emphasize being fully prepared before fundraising and cultivating connections with investors in advance.
AWS_HK_StartupDay_Building Interactive websites while automating for efficien...Amazon Web Services
This document discusses Amazon's machine learning services for building conversational interfaces and extracting insights from unstructured text and audio. It describes Amazon Lex for creating chatbots, Amazon Comprehend for natural language processing tasks like entity extraction and sentiment analysis, and how they can be used together for applications like intelligent call centers and content analysis. Pre-trained APIs simplify adding machine learning to apps without requiring ML expertise.
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.