The vast amount of big data that today’s companies generate makes it difficult to separate the signal from the noise. Organizations need to derive meaningful insights into operations and business to take action. TrueCar needed a better way to manage, search, and analyze their hybrid environment. In this webinar, you’ll learn how TrueCar centralized all of their data in one place using Amazon Kinesis and Splunk Cloud, gaining deep visibility, scalability, and the ability to monitor and troubleshoot operational issues – all while migrating to AWS.
by Kwesi Edwards, Business Development Manager, AWS
Database migration doesn’t need to be difficult or time-consuming. Learn how AWS Database Migration Service provides an easy, secure migration from on-premises and Amazon EC2 environments to Amazon RDS, Amazon Redshift, Amazon DynamoDB and EC2 databases, with minimal-downtime. We’ll also see how the AWS Schema Conversion Tool automatically converts your schema and a majority of the custom code, so you can get up and running in the cloud quickly and inexpensively. We’ll discuss alternative data migration strategies for special use cases. Level 200
by Darin Briskman, Technical Evangelist, AWS
SQL is a powerful tool to query data, but it doesn't cover everything you might need. Sometimes, the precision of SQL is a limitation, that can be overcome by using the flexibility and inherent ranking of search. Learn how to use AWS servcies to create fully managed solutions using Amazon Aurora and Amazon Elasticsearch Service to combine the power of query and search. Level: 200
ABD206-Building Visualizations and Dashboards with Amazon QuickSightAmazon Web Services
Just as a picture is worth a thousand words, a visual is worth a thousand data points. A key aspect of our ability to gain insights from our data is to look for patterns, and these patterns are often not evident when we simply look at data in tables. The right visualization will help you gain a deeper understanding in a much quicker timeframe. In this session, we will show you how to quickly and easily visualize your data using Amazon QuickSight. We will show you how you can connect to data sources, generate custom metrics and calculations, create comprehensive business dashboards with various chart types, and setup filters and drill downs to slice and dice the data.
Deploying Business Analytics at Enterprise Scale - AWS Online Tech TalksAmazon Web Services
Learning Objectives:
- Deploy business analytics to thousands of users using Active Directory and Federated SSO
- Securely access data sources in Amazon VPCs or on-premises and build data marts with SPICE
- Control access to your data sources, implement row-level security, and audit access to your data
ABD324_Migrating Your Oracle Data Warehouse to Amazon Redshift Using AWS DMS ...Amazon Web Services
Customers that have Oracle Data warehouses find them complex and expensive to manage. Most are struggling with data load and performance issues. They are looking to migrate to something which is easy to manage, cost effective, and improves their query performance. Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse service that makes it simple and cost-effective to analyze all your data using your existing business intelligence tools. Migrating your Oracle data warehouse to Amazon Redshift can substantially improve query and data load performance, increase scalability, and save costs. This workshop leverages AWS Database Migration Service and AWS Schema Conversion Tool to migrate an existing Oracle data warehouse to Amazon Redshift. When migrating your database from one engine to another, you have two major things to consider: the conversion of the schema and code objects, and the migration and conversion of the data itself. You can convert schema and code with AWS SCT and migrate data with AWS DMS. AWS DMS helps you migrate your data easily and securely with minimal downtime. Prerequisites: Have an AWS account with IAM admin permissions and sufficient limits for AWS resources above, with a comfortable working knowledge of AWS console, relational databases (Oracle) and Amazon Redshift.
ABD207 building a banking utility leveraging aws to fight financial crime and...Amazon Web Services
"Banks aren’t known to share data and collaborate with one another. But that is exactly what the Mid-Sized Bank Coalition of America (MBCA) is doing to fight digital financial crime—and protect national security. Using the AWS Cloud, the MBCA developed a shared data analytics utility that processes terabytes of non-competitive customer account, transaction, and government risk data. The intelligence produced from the data helps banks increase the efficiency of their operations, cut labor and operating costs, and reduce false positive volumes. The collective intelligence also allows greater enforcement of Anti-Money Laundering (AML) regulations by helping members detect internal risks—and identify the challenges to detecting these risks in the first place. This session demonstrates how the AWS Cloud supports the MBCA to deliver advanced data analytics, provide consistent operating models across financial institutions, reduce costs, and strengthen national security.
Session sponsored by Accenture"
by Kwesi Edwards, Business Development Manager, AWS
Database migration doesn’t need to be difficult or time-consuming. Learn how AWS Database Migration Service provides an easy, secure migration from on-premises and Amazon EC2 environments to Amazon RDS, Amazon Redshift, Amazon DynamoDB and EC2 databases, with minimal-downtime. We’ll also see how the AWS Schema Conversion Tool automatically converts your schema and a majority of the custom code, so you can get up and running in the cloud quickly and inexpensively. We’ll discuss alternative data migration strategies for special use cases. Level 200
by Darin Briskman, Technical Evangelist, AWS
SQL is a powerful tool to query data, but it doesn't cover everything you might need. Sometimes, the precision of SQL is a limitation, that can be overcome by using the flexibility and inherent ranking of search. Learn how to use AWS servcies to create fully managed solutions using Amazon Aurora and Amazon Elasticsearch Service to combine the power of query and search. Level: 200
ABD206-Building Visualizations and Dashboards with Amazon QuickSightAmazon Web Services
Just as a picture is worth a thousand words, a visual is worth a thousand data points. A key aspect of our ability to gain insights from our data is to look for patterns, and these patterns are often not evident when we simply look at data in tables. The right visualization will help you gain a deeper understanding in a much quicker timeframe. In this session, we will show you how to quickly and easily visualize your data using Amazon QuickSight. We will show you how you can connect to data sources, generate custom metrics and calculations, create comprehensive business dashboards with various chart types, and setup filters and drill downs to slice and dice the data.
Deploying Business Analytics at Enterprise Scale - AWS Online Tech TalksAmazon Web Services
Learning Objectives:
- Deploy business analytics to thousands of users using Active Directory and Federated SSO
- Securely access data sources in Amazon VPCs or on-premises and build data marts with SPICE
- Control access to your data sources, implement row-level security, and audit access to your data
ABD324_Migrating Your Oracle Data Warehouse to Amazon Redshift Using AWS DMS ...Amazon Web Services
Customers that have Oracle Data warehouses find them complex and expensive to manage. Most are struggling with data load and performance issues. They are looking to migrate to something which is easy to manage, cost effective, and improves their query performance. Amazon Redshift is a fast, fully managed, petabyte-scale data warehouse service that makes it simple and cost-effective to analyze all your data using your existing business intelligence tools. Migrating your Oracle data warehouse to Amazon Redshift can substantially improve query and data load performance, increase scalability, and save costs. This workshop leverages AWS Database Migration Service and AWS Schema Conversion Tool to migrate an existing Oracle data warehouse to Amazon Redshift. When migrating your database from one engine to another, you have two major things to consider: the conversion of the schema and code objects, and the migration and conversion of the data itself. You can convert schema and code with AWS SCT and migrate data with AWS DMS. AWS DMS helps you migrate your data easily and securely with minimal downtime. Prerequisites: Have an AWS account with IAM admin permissions and sufficient limits for AWS resources above, with a comfortable working knowledge of AWS console, relational databases (Oracle) and Amazon Redshift.
ABD207 building a banking utility leveraging aws to fight financial crime and...Amazon Web Services
"Banks aren’t known to share data and collaborate with one another. But that is exactly what the Mid-Sized Bank Coalition of America (MBCA) is doing to fight digital financial crime—and protect national security. Using the AWS Cloud, the MBCA developed a shared data analytics utility that processes terabytes of non-competitive customer account, transaction, and government risk data. The intelligence produced from the data helps banks increase the efficiency of their operations, cut labor and operating costs, and reduce false positive volumes. The collective intelligence also allows greater enforcement of Anti-Money Laundering (AML) regulations by helping members detect internal risks—and identify the challenges to detecting these risks in the first place. This session demonstrates how the AWS Cloud supports the MBCA to deliver advanced data analytics, provide consistent operating models across financial institutions, reduce costs, and strengthen national security.
Session sponsored by Accenture"
ABD202_Best Practices for Building Serverless Big Data ApplicationsAmazon Web Services
Serverless technologies let you build and scale applications and services rapidly without the need to provision or manage servers. In this session, we show you how to incorporate serverless concepts into your big data architectures. We explore the concepts behind and benefits of serverless architectures for big data, looking at design patterns to ingest, store, process, and visualize your data. Along the way, we explain when and how you can use serverless technologies to streamline data processing, minimize infrastructure management, and improve agility and robustness and share a reference architecture using a combination of cloud and open source technologies to solve your big data problems. Topics include: use cases and best practices for serverless big data applications; leveraging AWS technologies such as Amazon DynamoDB, Amazon S3, Amazon Kinesis, AWS Lambda, Amazon Athena, and Amazon EMR; and serverless ETL, event processing, ad hoc analysis, and real-time analytics.
Companies, from startups to enterprises across the globe, are looking to migrate data warehousing to the cloud to increase performance and lower costs. Data engineers, data analysts, and developers also need to access and consume this important data. The landscape is constantly evolving and there are many solutions available for enterprises of all sizes. In this workshop, we dive deep into architectural patterns, use cases, and best practices when designing an enterprise data warehouse in the cloud. We also address key issues such as data governance and democratization. At the end of this workshop, you’ll be equipped to design and implement a cloud enterprise data warehouse platform that provides the most benefit for your enterprise, data consumers, and customers.
Automate the Provisioning of Secure Developer Environments on AWS PPTAmazon Web Services
Providing development and engineering teams with access to cloud resources introduces challenges around deploying the proper security policies. Organizations need automated security solutions that enable their engineers to spin up their own secure environments for application development with a push of a button. Join our upcoming webinar with Palo Alto Networks, REAN Cloud, and AWS, to learn how organizations are leveraging Palo Alto Networks VM-Series and REAN Cloud to build a simple, fast, and automated solution on AWS that helps provision secure environments for developers.
DynamoDB queries enable consistent low latency at any workload, using the partition key, sort key, local secondary indexes, and global secondary indexes. Amazon Elasticsearch Service enables flexible search, including ranking and aggregation. Adding Elasticsearch to DynamoDB opens new capabilities to combine the power of query and search. Learn how Amazon.com uses this combination and how you can use it, too
Come see first-hand how Amazon EC2 Systems Manager can help you manage your servers at scale with the agility and security you need in today's dynamic cloud-enabled world. To be truly agile, you need a way to define and track system configurations, prevent drift, and maintain software compliance. At the same time, you need to collect software inventory, apply OS patches, automate your system image maintenance, and configure anything in the OSs of your EC2 instances and on-premises servers. Amazon EC2 Systems Manager does all of that and more for both Linux and Windows systems. In this session, learn about the seven services that make up Amazon EC2 Systems Manager and see them in action. No matter if you are managing 10 or 10,000 instances, see how you can manage your systems, increasing your agility and security with EC2 Systems Manager.
Humans and Data Don't Mix- Best Practices to Secure Your CloudAmazon Web Services
When it comes to security, human error far outpaces other causes of failures. The risk of humans touching sensitive data is clear, so how do you get them away from your data while also speeding up time to detection and remediation? Stephen Schmidt, AWS CISO, will share hard-earned lessons around potential opportunities in your security program, along with practical steps to improve the agility of your organization.
DVC303-Technological Accelerants for Organizational TransformationAmazon Web Services
"Developers and management can seem at cross purposes when one group looks at technologies and the other looks at organizational issues. Both groups are looking for ways to deliver value faster, leaner, and at less cost. There are technological avenues for accomplishing these goals, including DevOps and serverless architectures. However, these approaches also have organizational implications, as they change the nature and content of communication between teams. In this session, we cover the technology benefits and organizational transformations involved in DevOps and serverless architectures.
This session is part of the re:Invent Developer Community Day, six community-led sessions where AWS enthusiasts share technical insights on trending topics based on first-hand experiences and knowledge shared within local AWS communities."
ENT324-Automating and Auditing Cloud Governance and Compliance in Multi-Accou...Amazon Web Services
In this session, we explore multi-account considerations for compliance and auditing. We include topics such as API call prefiltering, a repeatable approach to SCP and IAM policy creation, internal separation of duty and need to know, compliance scope ring-fencing, scope of impact limitation, and mandatory access control. We review approaches for log and event analytics and log record lifecycle management (including redaction where necessary) and alerting. We also discuss how you can deploy compliance assessment tools in multi-account environments and how you can interpret these tools' output so it makes sense. Finally, no set of detailed multi-account sessions is complete without discussing tools for visualization.
What’s New in Amazon RDS for Open-Source and Commercial Databases: Amazon Web Services
by Kwesi Edwards, Business Development Manager, AWS
In the past year, Amazon RDS has continued to expand functionality, scalability, availability and ease of use for all supported database engines: PostgreSQL, MySQL, MariaDB, Oracle and Microsoft SQL Server. We’ll take a close look at RDS use cases and new capabilities, splitting the time between open-source and commercial database engines. Level 300
Enabling Governance, Compliance, and Operational and Risk Auditing with AWS M...Amazon Web Services
In this session, learn how you can enable governance, compliance, and operational and risk auditing of your AWS account through a combination of continuous monitoring, auditing, and evaluation of your AWS resources. With AWS management tools, you can see a history of AWS API calls for your account, review changes in configurations and relationships among AWS resources, and dive into detailed resource configuration histories. You can determine your overall compliance with the configurations specified in your internal guidelines, and you can give developers and systems administrators a secure and compliant means to create and manage AWS resources.
ABD303_Developing an Insights Platform—the Sysco Journey from Disparate Syste...Amazon Web Services
Sysco has nearly 200 operating companies across its multiple lines of business throughout the United States, Canada, Central/South America, and Europe. As the global leader in food services, Sysco identified the need to streamline the collection, transformation, and presentation of data produced by the distributed units and systems, into a central data ecosystem. Sysco's Business Intelligence and Analytics team addressed these requirements by creating a data lake with scalable analytics and query engines leveraging AWS services. In this session, Sysco will outline their journey from a hindsight reporting focused company to an insights driven organization. They will cover solution architecture, challenges, and lessons learned from deploying a self-service insights platform. They will also walk through the design patterns they used and how they designed the solution to provide predictive analytics using Amazon Redshift Spectrum, Amazon S3, Amazon EMR, AWS Glue, Amazon Elasticsearch Service and other AWS services.
Over 90% of today’s data was generated in the last 2 years, and the rate of data growth isn’t slowing down. In this session, we’ll step through the challenges and best practices on how to capture all the data that is being generated, understand what data you have, and start driving insights and even predict the future using purpose built AWS Services. We’ll frame the session and demonstrations around common pitfalls of building Data Lakes and how to successful drive analytics and insights from the data. This session will focus on the architecture patterns bringing together key AWS Services and rather than a deep dive on any single service. We’ll show how services such as Amazon S3, Amazon Glue, AWS Glue, Amazon Redshift, Amazon Athena, Amazon EMR, and Amazon Kinesis, and Amazon Machine Learning services are put together to build a successful data lake for various role including both data scientists and business users.
Deploy and Enforce Compliance Controls When Archiving Large-Scale Data Stores...Amazon Web Services
Learning Objectives:
- Learn what storage regulations to be aware of when developing and deploying a cloud based storage solution
- Gain awareness of various strategies to address compliance
- Examine solutions available from AWS, including Amazon S3, Amazon Glacier and the Vault Lock feature, AWS Snowball and their data ingestion services.
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
GPSWKS408-GPS Migrate Your Databases with AWS Database Migration Service and ...Amazon Web Services
Database migration is one of the most commonly performed tasks in the journey to the AWS Cloud. In this workshop, we help migration solutions architects, engineers, and program staff gain in-depth knowledge, hands-on experience, and best practices in using the AWS Database Migration Service (AWS DMS) and its companion, the AWS Schema Conversion Tool (AWS SCT). First, we walk through database migration methodologies and provide field data about what customers are doing with AWS DMS and AWS SCT. Then, we take a closer look at AWS DMS and AWS SCT features, architecture, workflows, and Amazon Aurora as a destination database. Attendees work through a lab to gain firsthand experience in database migration. To get the most out of this session, bring a laptop for the lab and have a QwikLabs account.
AMF302-Alexa Wheres My Car A Test Drive of the AWS Connected Car Reference.pdfAmazon Web Services
Today's trends in auto technology are all about connecting cars and their occupants to the outside world in a seamless and safe manner. In this session, we discuss how automotive companies are leveraging AWS for a variety of connected vehicle use cases. You'll leave this session with source code, architecture diagrams, and an understanding of how to apply the AWS Connected Vehicle Reference Architecture to build your own prototypes. You'll also learn how car companies can leverage Amazon services such as Alexa and AWS services such as AWS IOT, AWS Greengrass, AWS Lambda and Amazon API Gateway to rapidly develop and deploy innovative connected vehicle services.
One of the biggest tradeoffs customers usually make when deploying BI solutions at scale is agility versus governance. Large-scale BI implementations with the right governance structure can take months to design and deploy. In this session, learn how you can avoid making this tradeoff using Amazon QuickSight. Learn how to easily deploy Amazon QuickSight to thousands of users using Active Directory and Federated SSO, while securely accessing your data sources in Amazon VPCs or on-premises. We also cover how to control access to your datasets, implement row-level security, create scheduled email reports, and audit access to your data.
Learning Objectives:
- Learn AWS architectural best practices
- Measure your architecture against pillars of security, reliability, cost, performance, and operations
- Build a plan to remediate and improve your architecture
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.
Join our webinar to learn:
- How to quickly and easily ingest data for a data lake on Amazon S3.
- How to use Attunity with Apache Kafka to provide critical business insights that drive customer satisfaction.
- How to replicate data to the cloud – with zero downtime.
ABD202_Best Practices for Building Serverless Big Data ApplicationsAmazon Web Services
Serverless technologies let you build and scale applications and services rapidly without the need to provision or manage servers. In this session, we show you how to incorporate serverless concepts into your big data architectures. We explore the concepts behind and benefits of serverless architectures for big data, looking at design patterns to ingest, store, process, and visualize your data. Along the way, we explain when and how you can use serverless technologies to streamline data processing, minimize infrastructure management, and improve agility and robustness and share a reference architecture using a combination of cloud and open source technologies to solve your big data problems. Topics include: use cases and best practices for serverless big data applications; leveraging AWS technologies such as Amazon DynamoDB, Amazon S3, Amazon Kinesis, AWS Lambda, Amazon Athena, and Amazon EMR; and serverless ETL, event processing, ad hoc analysis, and real-time analytics.
Companies, from startups to enterprises across the globe, are looking to migrate data warehousing to the cloud to increase performance and lower costs. Data engineers, data analysts, and developers also need to access and consume this important data. The landscape is constantly evolving and there are many solutions available for enterprises of all sizes. In this workshop, we dive deep into architectural patterns, use cases, and best practices when designing an enterprise data warehouse in the cloud. We also address key issues such as data governance and democratization. At the end of this workshop, you’ll be equipped to design and implement a cloud enterprise data warehouse platform that provides the most benefit for your enterprise, data consumers, and customers.
Automate the Provisioning of Secure Developer Environments on AWS PPTAmazon Web Services
Providing development and engineering teams with access to cloud resources introduces challenges around deploying the proper security policies. Organizations need automated security solutions that enable their engineers to spin up their own secure environments for application development with a push of a button. Join our upcoming webinar with Palo Alto Networks, REAN Cloud, and AWS, to learn how organizations are leveraging Palo Alto Networks VM-Series and REAN Cloud to build a simple, fast, and automated solution on AWS that helps provision secure environments for developers.
DynamoDB queries enable consistent low latency at any workload, using the partition key, sort key, local secondary indexes, and global secondary indexes. Amazon Elasticsearch Service enables flexible search, including ranking and aggregation. Adding Elasticsearch to DynamoDB opens new capabilities to combine the power of query and search. Learn how Amazon.com uses this combination and how you can use it, too
Come see first-hand how Amazon EC2 Systems Manager can help you manage your servers at scale with the agility and security you need in today's dynamic cloud-enabled world. To be truly agile, you need a way to define and track system configurations, prevent drift, and maintain software compliance. At the same time, you need to collect software inventory, apply OS patches, automate your system image maintenance, and configure anything in the OSs of your EC2 instances and on-premises servers. Amazon EC2 Systems Manager does all of that and more for both Linux and Windows systems. In this session, learn about the seven services that make up Amazon EC2 Systems Manager and see them in action. No matter if you are managing 10 or 10,000 instances, see how you can manage your systems, increasing your agility and security with EC2 Systems Manager.
Humans and Data Don't Mix- Best Practices to Secure Your CloudAmazon Web Services
When it comes to security, human error far outpaces other causes of failures. The risk of humans touching sensitive data is clear, so how do you get them away from your data while also speeding up time to detection and remediation? Stephen Schmidt, AWS CISO, will share hard-earned lessons around potential opportunities in your security program, along with practical steps to improve the agility of your organization.
DVC303-Technological Accelerants for Organizational TransformationAmazon Web Services
"Developers and management can seem at cross purposes when one group looks at technologies and the other looks at organizational issues. Both groups are looking for ways to deliver value faster, leaner, and at less cost. There are technological avenues for accomplishing these goals, including DevOps and serverless architectures. However, these approaches also have organizational implications, as they change the nature and content of communication between teams. In this session, we cover the technology benefits and organizational transformations involved in DevOps and serverless architectures.
This session is part of the re:Invent Developer Community Day, six community-led sessions where AWS enthusiasts share technical insights on trending topics based on first-hand experiences and knowledge shared within local AWS communities."
ENT324-Automating and Auditing Cloud Governance and Compliance in Multi-Accou...Amazon Web Services
In this session, we explore multi-account considerations for compliance and auditing. We include topics such as API call prefiltering, a repeatable approach to SCP and IAM policy creation, internal separation of duty and need to know, compliance scope ring-fencing, scope of impact limitation, and mandatory access control. We review approaches for log and event analytics and log record lifecycle management (including redaction where necessary) and alerting. We also discuss how you can deploy compliance assessment tools in multi-account environments and how you can interpret these tools' output so it makes sense. Finally, no set of detailed multi-account sessions is complete without discussing tools for visualization.
What’s New in Amazon RDS for Open-Source and Commercial Databases: Amazon Web Services
by Kwesi Edwards, Business Development Manager, AWS
In the past year, Amazon RDS has continued to expand functionality, scalability, availability and ease of use for all supported database engines: PostgreSQL, MySQL, MariaDB, Oracle and Microsoft SQL Server. We’ll take a close look at RDS use cases and new capabilities, splitting the time between open-source and commercial database engines. Level 300
Enabling Governance, Compliance, and Operational and Risk Auditing with AWS M...Amazon Web Services
In this session, learn how you can enable governance, compliance, and operational and risk auditing of your AWS account through a combination of continuous monitoring, auditing, and evaluation of your AWS resources. With AWS management tools, you can see a history of AWS API calls for your account, review changes in configurations and relationships among AWS resources, and dive into detailed resource configuration histories. You can determine your overall compliance with the configurations specified in your internal guidelines, and you can give developers and systems administrators a secure and compliant means to create and manage AWS resources.
ABD303_Developing an Insights Platform—the Sysco Journey from Disparate Syste...Amazon Web Services
Sysco has nearly 200 operating companies across its multiple lines of business throughout the United States, Canada, Central/South America, and Europe. As the global leader in food services, Sysco identified the need to streamline the collection, transformation, and presentation of data produced by the distributed units and systems, into a central data ecosystem. Sysco's Business Intelligence and Analytics team addressed these requirements by creating a data lake with scalable analytics and query engines leveraging AWS services. In this session, Sysco will outline their journey from a hindsight reporting focused company to an insights driven organization. They will cover solution architecture, challenges, and lessons learned from deploying a self-service insights platform. They will also walk through the design patterns they used and how they designed the solution to provide predictive analytics using Amazon Redshift Spectrum, Amazon S3, Amazon EMR, AWS Glue, Amazon Elasticsearch Service and other AWS services.
Over 90% of today’s data was generated in the last 2 years, and the rate of data growth isn’t slowing down. In this session, we’ll step through the challenges and best practices on how to capture all the data that is being generated, understand what data you have, and start driving insights and even predict the future using purpose built AWS Services. We’ll frame the session and demonstrations around common pitfalls of building Data Lakes and how to successful drive analytics and insights from the data. This session will focus on the architecture patterns bringing together key AWS Services and rather than a deep dive on any single service. We’ll show how services such as Amazon S3, Amazon Glue, AWS Glue, Amazon Redshift, Amazon Athena, Amazon EMR, and Amazon Kinesis, and Amazon Machine Learning services are put together to build a successful data lake for various role including both data scientists and business users.
Deploy and Enforce Compliance Controls When Archiving Large-Scale Data Stores...Amazon Web Services
Learning Objectives:
- Learn what storage regulations to be aware of when developing and deploying a cloud based storage solution
- Gain awareness of various strategies to address compliance
- Examine solutions available from AWS, including Amazon S3, Amazon Glacier and the Vault Lock feature, AWS Snowball and their data ingestion services.
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
GPSWKS408-GPS Migrate Your Databases with AWS Database Migration Service and ...Amazon Web Services
Database migration is one of the most commonly performed tasks in the journey to the AWS Cloud. In this workshop, we help migration solutions architects, engineers, and program staff gain in-depth knowledge, hands-on experience, and best practices in using the AWS Database Migration Service (AWS DMS) and its companion, the AWS Schema Conversion Tool (AWS SCT). First, we walk through database migration methodologies and provide field data about what customers are doing with AWS DMS and AWS SCT. Then, we take a closer look at AWS DMS and AWS SCT features, architecture, workflows, and Amazon Aurora as a destination database. Attendees work through a lab to gain firsthand experience in database migration. To get the most out of this session, bring a laptop for the lab and have a QwikLabs account.
AMF302-Alexa Wheres My Car A Test Drive of the AWS Connected Car Reference.pdfAmazon Web Services
Today's trends in auto technology are all about connecting cars and their occupants to the outside world in a seamless and safe manner. In this session, we discuss how automotive companies are leveraging AWS for a variety of connected vehicle use cases. You'll leave this session with source code, architecture diagrams, and an understanding of how to apply the AWS Connected Vehicle Reference Architecture to build your own prototypes. You'll also learn how car companies can leverage Amazon services such as Alexa and AWS services such as AWS IOT, AWS Greengrass, AWS Lambda and Amazon API Gateway to rapidly develop and deploy innovative connected vehicle services.
One of the biggest tradeoffs customers usually make when deploying BI solutions at scale is agility versus governance. Large-scale BI implementations with the right governance structure can take months to design and deploy. In this session, learn how you can avoid making this tradeoff using Amazon QuickSight. Learn how to easily deploy Amazon QuickSight to thousands of users using Active Directory and Federated SSO, while securely accessing your data sources in Amazon VPCs or on-premises. We also cover how to control access to your datasets, implement row-level security, create scheduled email reports, and audit access to your data.
Learning Objectives:
- Learn AWS architectural best practices
- Measure your architecture against pillars of security, reliability, cost, performance, and operations
- Build a plan to remediate and improve your architecture
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.
Join our webinar to learn:
- How to quickly and easily ingest data for a data lake on Amazon S3.
- How to use Attunity with Apache Kafka to provide critical business insights that drive customer satisfaction.
- How to replicate data to the cloud – with zero downtime.
Amazon Kinesis - Building Serverless real-time solution - Tel Aviv Summit 2018Amazon Web Services
Amazon Kinesis Streams was born of necessity, to enable Amazon Web Services to capture millions of individual metering records per second from AWS services and EC2 instances and aggregate these records by account identifier to produce a customer billing record in real time. Today, Kinesis is a foundational service which over a dozen AWS and Amazon retail services use to capture and process streaming data.
Since the launch of Kinesis Streams, Amazon has worked with customers as their stream processing needs have evolved, subsequently launching Kinesis Firehose—which enables customers to capture streaming data, perform in-line processing to clean, format, and deliver this data to service destinations, such as S3, Redshift, Elasticsearch, and Lambda, in minutes—and Kinesis Analytics—which enables customers to process streaming data in real time using ANSI SQL..
Today, Kinesis data streaming services are foundational for business critical workflows, providing customers with a new way to process big data and extract actionable insights. In this session, we offer an overview of Kinesis, Amazon’s data streaming platform—highlighting key architectural features—and explains how customers have architected their applications using Kinesis services for low-latency and extreme scale. We will also demonstrate how to build an end-to-end solution using the latest and greatest AWS Data and analytics services like Athena, Glue, Lambda and more.
GPS: Industry 4.0: AI and the Future of Manufacturing - GPSTEC326 - re:Invent...Amazon Web Services
Advances in artificial intelligence, machine learning, and deep learning, along with the rapid deployment of Internet of Things (IoT) devices, are changing how physical products are designed and built. In this session, learn how AWS partners Siemens and Autodesk use AWS to enhance the design process and how they're incorporating AWS services into their products and smart factories. We explore how these trends impact the future of design and manufacturing.
GPSTEC326-GPS Industry 4.0 AI and the Future of ManufacturingAmazon Web Services
Advances in artificial intelligence, machine learning, and deep learning, along with the rapid deployment of Internet of Things (IoT) devices, are changing how physical products are designed and built. In this session, learn how AWS partners Siemens and Autodesk use AWS to enhance the design process and how they're incorporating AWS services into their products and smart factories. We explore how these trends impact the future of design and manufacturing.
Analyzing Streaming Data in Real-time with Amazon KinesisAmazon Web Services
As more and more organizations strive to gain real-time insights into their business, streaming data has become ubiquitous. Typical streaming data analytics solutions require specific skills and complex infrastructure. However, with Amazon Kinesis Analytics, you can analyze streaming data in real-time with standard SQL—there is no need to learn new programming languages or processing frameworks.
In this session, we dive deep into the capabilities of Amazon Kinesis Analytics using real-world examples. We’ll present an end-to-end streaming data solution using Amazon Kinesis Streams for data ingestion, Amazon Kinesis Analytics for real-time processing, and Amazon Kinesis Firehose for persistence. We review in detail how to write SQL queries using streaming data and discuss best practices to optimize and monitor your Amazon Kinesis Analytics applications. Lastly, we discuss how to estimate the cost of the entire system.
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
Big Data Meets AI - Driving Insights and Adding Intelligence to Your SolutionsAmazon Web Services
Over 90% of today’s data has been generated in the last two years, and growth rates continue to climb. In this session, we’ll step through challenges and best practices with data capturing, how to derive meaningful insights to help predict the future, and common pitfalls in data analysis.
Come discover how integrated solutions involving Amazon S3, AWS Glue, Amazon Redshift, Amazon Athena, Amazon EMR, Amazon Kinesis, and Amazon Machine Learning, and Deep Learning on AWS result in effective data systems for data scientists and business users, alike.
Ben Snively, Principal Solutions Architect, AWS; Kate Werling, Solutions Architect, AWS
Building a Data Lake in Amazon S3 & Amazon Glacier (STG401-R1) - AWS re:Inven...Amazon Web Services
Whether you are part of a startup or a global enterprise, using a data lake to store and analyze data can help your business glean insights to evolve service offerings and capitalize on emerging market opportunities. In this workshop, AWS engineers and experts provide hands-on guidance for IT professionals looking to build a data lake for their organization. We provide overviews of Amazon S3, Amazon Glacier, and AWS query-in-place features and services, such as Amazon S3 Select, Amazon Glacier Select, Amazon Athena, and Amazon Redshift Spectrum. Attendees also learn how to use these services with third-party tools to build data lakes and other analytics solutions. Familiarity of with AWS object storage and analytics services is helpful but not required.
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 Machine Learning (Amazon ML) services work together to build a successful data lake for various roles, including data scientists and business users.
Migrating to 21st Century Analytics: Zopa Story
Speakers:
Shafreen Sayyed, Solution Architect, AWS
Varun Gangoor, Senior Big Data Engineer, Zopa
Data makes the world go around these days, and 21st Century Data Analytics means you can store, process and analyze massive amounts of data, often in real time, whilst making that data consumable across diverse groups in your organization. Many traditional tools lock data away in inflexible silos, making this impossible. This session will look at what is needed in a Financial Services organization to achieve a flexible and scalable data architecture, and we will also hear from Zopa, UK's first peer-to-peer lending company, about how they migrated their data analytics estate to AWS and look at what new insight that has given them.
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.
Speaker: John Yeung, Solutions Architect, AWS
Data collection and storage is a primary challenge for any big data architecture. In this webinar, gain a thorough understanding of AWS solutions for data collection and storage, and learn architectural best practices for applying those solutions to your projects. This session will also include a discussion of popular use cases and reference architectures. In this webinar, you will learn:
• Overview of the different types of data that customers are handling to drive high-scale workloads on AWS, and how to choose the best approach for your workload • Optimization techniques that improve performance and reduce the cost of data ingestion • Leveraging Amazon S3, Amazon DynamoDB, and Amazon Kinesis for storage and data collection
MSC203_How Citrix Uses AWS Marketplace Solutions To Accelerate Analytic Workl...Amazon Web Services
Find out how Citrix built a solution using Matillion ETL for Amazon Redshift from AWS Marketplace to load all data into an Amazon Redshift cluster, allowing them to do their analytics on the entire environment at a single time. We’ll discuss the transition made to consolidate multiple disparate databases in order to run analytic workloads, get a holistic view of all their data sources, and prevent inconsistent data from being captured.
How Citrix Uses AWS Marketplace Solutions to Accelerate Analytic Workloads on...Amazon Web Services
Find out how Citrix built a solution using Matillion ETL for Amazon Redshift from AWS Marketplace to load all data into an Amazon Redshift cluster, allowing them to do their analytics on the entire environment at a single time. We’ll discuss the transition made to consolidate multiple disparate databases in order to run analytic workloads, get a holistic view of all their data sources, and prevent inconsistent data from being captured.
Leadership Session: AWS Database and Analytics (DAT206-L) - AWS re:Invent 2018Amazon Web Services
We’re witnessing an unprecedented growth in the amount of data collected and stored in the cloud. Getting insights from this data requires database and analytics services that scale and perform in ways not possible before. AWS offers the broadest set of database and analytics services to process, store, manage, and analyze all your data. In this session, we provide an overview of the database and analytics services at AWS, new services and features we launched this year, how customers are using these services, and our vision for continued innovation in this space.
Citrix Moves Data to Amazon Redshift Fast with Matillion ETLAmazon Web Services
Matillion ETL, easily deployable from Amazon Web Services (AWS) Marketplace, helps Citrix collate and summarize data and augment it with more traditional business data from Microsoft SQL Server for additional context. Join our webinar to learn how organizations of any size can move data to the cloud quickly, accurately, and affordably with Matillion ETL.
Join our webinar to learn:
How Citrix moved data to Amazon Redshift with speed and accuracy.
How to make informed, business-critical decisions by analyzing data with Amazon Redshift.
How to speed time-to-value for your analytics initiatives using Matillion’s push-down ELT architecture.
FINRA's Managed Data Lake: Next-Gen Analytics in the Cloud - ENT328 - re:Inve...Amazon Web Services
Financial Impact Regulatory Authority (FINRA)'s Technology Group has changed its customers' relationship with data by creating a managed data lake that enables discovery on petabytes of capital markets' data, while saving time and money over traditional analytics solutions. FINRA's managed data lake unlocks the value in its data to accelerate analytics and machine learning at scale. The data lake includes a centralized data catalog and separates storage from compute, allowing users to query from petabytes of data in seconds. Learn how FINRA uses Spot Instances and services such as Amazon S3, Amazon EMR, Amazon Redshift, and AWS Lambda to provide the right tool for the right job at each step in the data processing pipeline. All of this is done while meeting FINRA's security and compliance responsibilities as a financial regulator.
Amazon Redshift Update and How Equinox Fitness Clubs Migrated to a Modern Dat...Amazon Web Services
In this session, we provide an update on Amazon Redshift, and look at a case study from Equinox Fitness Clubs. We show you how Amazon Redshift queries data across your data warehouse and data lake, without the need or delay of loading data, to deliver insights you cannot obtain by querying independent data silos. Discover how Equinox Fitness Clubs transitioned from on-premises data warehouses and data marts to a cloud-based, integrated data platform, built on AWS and Amazon Redshift. Learn about their journey from static reports, redundant data, and inefficient data integration to a modern and flexible data lake and data warehouse architecture that delivers dynamic reports based on trusted data.
Similar to How TrueCar Gains Actionable Insights with Splunk Cloud PPT (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.