Amazon Kinesis makes it easy to speed up the time it takes for you to get valuable, real-time insights from your streaming data. Apache Flink is an open source framework and engine for processing data streams. In this chalk talk, we provide an overview of streaming data, Amazon Kinesis, and Apache Flink. We then go deep into a specific example of when to use Apache Flink for building streaming application. Our customer, John Deere, then dives deep into their specific Amazon Kinesis and Apache Flink use case and discusses best practices for processing streaming data in real time.
Instrumenting Kubernetes for Observability Using AWS X-Ray and Amazon CloudWa...Amazon Web Services
In this hands-on workshop, we walk you through instrumenting container workloads running on the Amazon Elastic Container Service for Kubernetes (Amazon EKS). Learn how Amazon CloudWatch and the new AWS X-Ray capabilities enable you to quickly understand problem areas in your application and determine customer impact. To participate in this workshop, bring your laptop and have a nonproduction AWS account.
Managing Modern Infrastructure in Enterprises (ENT227-R1) - AWS re:Invent 2018Amazon Web Services
In this session, Verizon shares how it uses AWS Systems Manager for inventory, compliance, and patch management solutions. Learn about the challenges that large enterprises face when they attempt to retrofit legacy solutions for cloud environments, and discover best practices for using AWS Systems Manager for minimal access policies, custom Amazon Machine Images, tagging policies, encryption, and more.
Serverless Architectural Patterns and Best Practices (ARC305-R2) - AWS re:Inv...Amazon Web Services
As serverless architectures become more popular, customers need a framework of patterns to help them identify how to leverage AWS to deploy their workloads without managing servers or operating systems. This session describes reusable serverless patterns while considering costs. For each pattern, we provide operational and security best practices and discuss potential pitfalls and nuances. We also discuss the considerations for moving an existing server-based workload to a serverless architecture. This session can help you recognize candidates for serverless architectures in your own organizations and understand areas of potential savings and increased agility.
Serverless State Management & Orchestration for Modern Apps (API302) - AWS re...Amazon Web Services
Keeping track of state and orchestrating the components of a distributed application is complex. AWS Step Functions makes the job simpler, faster, and more intuitive. In this session, learn how to leverage AWS Step Functions to design and run workflows for your serverless, containerized, and instance-based architectures. We explore practical applications of orchestration spanning different industries and workloads. For each, we walk through the architecture, lessons learned, and business outcomes. Expect to leave this session with a practical understanding of how to use orchestration to express your application’s business logic more productively while improving its resilience.
Effective Cost Optimization for Business (ARC201) - AWS re:Invent 2018Amazon Web Services
Aimed at finance and management functions, this talk explains what cost optimization means in the cloud and how you can enable your organization to optimize costs. We break down what optimization actually means and how much you should invest in it. We then discuss the cultural aspects to address when promoting optimization and developing capability across your business. Finally, we explore some of the common areas in which to achieve optimization: governance, pricing models, financial processes, service selection, and cost controls. Please join us for a speaker meet-and-greet following this session at the Speaker Lounge (ARIA East, Level 1, Willow Lounge). The meet-and-greet starts 15 minutes after the session and runs for half an hour.
Streaming data ingestion and near real-time analysis gives you immediate insights into your data. By using AWS Lambda with Amazon Kinesis, you can obtain these insights without the need to manage servers. But are you doing this in the most optimal way? In this interactive session, we review the best practices for using Lambda with Kinesis, and how to avoid common pitfalls.
Supercell – Scaling Mobile Games (GAM301) - AWS re:Invent 2018Amazon Web Services
In this session, learn how Supercell architected its analytics pipeline on AWS. We dive deep into how Supercell leverages Amazon Elastic Compute Cloud (Amazon EC2), Amazon Kinesis, Amazon Simple Storage Service (Amazon S3), Amazon EMR, and Spark to ingest, process, store, and query petabytes of data. We also dive deep into how Supercell's games are architected to accommodate scaling and failure recovery. We explain how Supercell's teams are organized into small and independent cells and how this affects the technology choices they make to produce value and agility in the development process.
The Amazon.com Database Journey to AWS – Top 10 Lessons Learned (DAT326) - AW...Amazon Web Services
In this session, we share the top 10 lessons learned from migrating the online transaction processing (OLTP) and data warehouse (DW) databases used by Amazon.com to AWS services, such as Amazon Relational Database Service (Amazon RDS), Amazon Aurora, Amazon Redshift, and Amazon DynamoDB. We discuss the challenges associated with operating and managing legacy OLTP and DW databases at Amazon.com scale and how the Amazon.com team successfully executed the database freedom program across different organizations and geographies.
Instrumenting Kubernetes for Observability Using AWS X-Ray and Amazon CloudWa...Amazon Web Services
In this hands-on workshop, we walk you through instrumenting container workloads running on the Amazon Elastic Container Service for Kubernetes (Amazon EKS). Learn how Amazon CloudWatch and the new AWS X-Ray capabilities enable you to quickly understand problem areas in your application and determine customer impact. To participate in this workshop, bring your laptop and have a nonproduction AWS account.
Managing Modern Infrastructure in Enterprises (ENT227-R1) - AWS re:Invent 2018Amazon Web Services
In this session, Verizon shares how it uses AWS Systems Manager for inventory, compliance, and patch management solutions. Learn about the challenges that large enterprises face when they attempt to retrofit legacy solutions for cloud environments, and discover best practices for using AWS Systems Manager for minimal access policies, custom Amazon Machine Images, tagging policies, encryption, and more.
Serverless Architectural Patterns and Best Practices (ARC305-R2) - AWS re:Inv...Amazon Web Services
As serverless architectures become more popular, customers need a framework of patterns to help them identify how to leverage AWS to deploy their workloads without managing servers or operating systems. This session describes reusable serverless patterns while considering costs. For each pattern, we provide operational and security best practices and discuss potential pitfalls and nuances. We also discuss the considerations for moving an existing server-based workload to a serverless architecture. This session can help you recognize candidates for serverless architectures in your own organizations and understand areas of potential savings and increased agility.
Serverless State Management & Orchestration for Modern Apps (API302) - AWS re...Amazon Web Services
Keeping track of state and orchestrating the components of a distributed application is complex. AWS Step Functions makes the job simpler, faster, and more intuitive. In this session, learn how to leverage AWS Step Functions to design and run workflows for your serverless, containerized, and instance-based architectures. We explore practical applications of orchestration spanning different industries and workloads. For each, we walk through the architecture, lessons learned, and business outcomes. Expect to leave this session with a practical understanding of how to use orchestration to express your application’s business logic more productively while improving its resilience.
Effective Cost Optimization for Business (ARC201) - AWS re:Invent 2018Amazon Web Services
Aimed at finance and management functions, this talk explains what cost optimization means in the cloud and how you can enable your organization to optimize costs. We break down what optimization actually means and how much you should invest in it. We then discuss the cultural aspects to address when promoting optimization and developing capability across your business. Finally, we explore some of the common areas in which to achieve optimization: governance, pricing models, financial processes, service selection, and cost controls. Please join us for a speaker meet-and-greet following this session at the Speaker Lounge (ARIA East, Level 1, Willow Lounge). The meet-and-greet starts 15 minutes after the session and runs for half an hour.
Streaming data ingestion and near real-time analysis gives you immediate insights into your data. By using AWS Lambda with Amazon Kinesis, you can obtain these insights without the need to manage servers. But are you doing this in the most optimal way? In this interactive session, we review the best practices for using Lambda with Kinesis, and how to avoid common pitfalls.
Supercell – Scaling Mobile Games (GAM301) - AWS re:Invent 2018Amazon Web Services
In this session, learn how Supercell architected its analytics pipeline on AWS. We dive deep into how Supercell leverages Amazon Elastic Compute Cloud (Amazon EC2), Amazon Kinesis, Amazon Simple Storage Service (Amazon S3), Amazon EMR, and Spark to ingest, process, store, and query petabytes of data. We also dive deep into how Supercell's games are architected to accommodate scaling and failure recovery. We explain how Supercell's teams are organized into small and independent cells and how this affects the technology choices they make to produce value and agility in the development process.
The Amazon.com Database Journey to AWS – Top 10 Lessons Learned (DAT326) - AW...Amazon Web Services
In this session, we share the top 10 lessons learned from migrating the online transaction processing (OLTP) and data warehouse (DW) databases used by Amazon.com to AWS services, such as Amazon Relational Database Service (Amazon RDS), Amazon Aurora, Amazon Redshift, and Amazon DynamoDB. We discuss the challenges associated with operating and managing legacy OLTP and DW databases at Amazon.com scale and how the Amazon.com team successfully executed the database freedom program across different organizations and geographies.
Shift-Left SRE: Self-Healing with AWS Lambda Functions (DEV313-S) - AWS re:In...Amazon Web Services
Even the best continuous delivery and DevOps practices cannot guarantee that there will be no issues in production. The rise of Site Reliability Engineering (SRE) has promoted new ways to automate resilience into your system and applications to circumvent potential problems, but it’s time to “shift-left” this effort into engineering. In this session, learn to leverage AWS Lambda functions as “remediation as code.” We show how to make it part of your continuous delivery process and orchestrate the invocation of Self-Healing Lambda functions in case of unexpected situations impacting the reliability of your system. Gone are the days of traditional operation teams—it’s the rise of “shift-lefters”! This session is brought to you by AWS partner, Dynatrace.
Automate & Audit Cloud Governance & Compliance in Your Landing Zone (ENT315-R...Amazon Web Services
In this session, we explore landing zone considerations as they apply to compliance and auditing. We include such topics as a repeatable approach to SCP and IAM policy creation, internal separation of duty & "need to know", compliance scope ringfencing, Region scoping, 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 compliance assessment tools can be deployed in multi-account environments and their output sensibly interpreted. We encourage you to attend the full AWS Landing Zone track, including SEC303. Search for #awslandingzone in the session catalog.
In this session, learn about the latest features in our cost management tooling. The presentation is given by the Cost Insights service team and supported by cost optimization experts from across our business.
What's New with Amazon Redshift ft. McDonald's (ANT350-R1) - AWS re:Invent 2018Amazon Web Services
Learn about the latest and hottest features of Amazon Redshift. We’ll deep dive into the architecture and inner workings of Amazon Redshift and discuss how the recent availability, performance, and manageability improvements we’ve made can significantly enhance your user experience. We’ll also share glimpse of what we are working on and our plans for the future. McDonald's will join us to share how they leverage a data lake powered by Redshift, Redshift spectrum and Athena to get quick insights.
What Can Your Logs Tell You? (ANT215) - AWS re:Invent 2018Amazon Web Services
Everyone has logs. They’re not the most exciting data that your systems generate, but often, they are the most useful. Across the board, we see customers using Amazon Elasticsearch Service (Amazon ES) to ingest, analyze, and search their log data. In this chalk talk, we discuss how to get your data into Amazon ES, and how to use Kibana to best effect to pull the information you need from the logs you’re generating.
AI/ML with Data Lakes: Counterintuitive Consumer Insights in Retail (RET206) ...Amazon Web Services
In this session, learn how data scientists in the retail industry, from companies like Tapestry, Coach, and Kate Spade, are finding new, counterintuitive consumer insights using AWS artificial intelligence services in a data lake. By leveraging data from various retail systems, including CRM, marketing, e-commerce, point of sale, order management, merchandising, and customer care, we show you how these consumer insights might influence new and interesting retail use cases while establishing a data-driven culture within the organization. Services referenced include Amazon S3, Amazon Machine Learning, Amazon QuickSight, Amazon SageMaker, among others.
DevSecOps: Instituting Cultural Transformation for Public Sector Organization...Amazon Web Services
In this in-depth, interactive workshop, we examine how different public sector customers achieve this shift and analyze common success patterns. We address key points such as continuous compliance, integrating security, and removing people from the data to vastly improve the organization's security posture over traditional operating models. Takeaways include a blueprint for building a DevSecOps operating model in your organization; an understanding the security practitioners' point of view and embracing it to drive innovation; and ways to identify current operating characteristics in your organization and use them to drive a strategy for DevSecOps.
MassMutual Goes Cloud First with Hybrid Cloud on AWS (ENT210) - AWS re:Invent...Amazon Web Services
In this session, we discuss how MassMutual adopts a cloud-first strategy, and we outline their journey to hybrid cloud on AWS. Specifically, we cover four aspects of MassMutual's hybrid cloud on AWS architecture: First, we talk about the use of the AWS Well-Architected Framework to create MassMutual’s cloud minimal viable product (MVP) document. Next, we do a deep dive into MassMutual's multi-account, multi-region architecture. We discuss achieving cloud governance, risk, and compliance through tooling and automation. Finally, we demonstrate how MassMutual deploys fully compliant hybrid cloud environments in less than five minutes. We also showcase some of MassMutual's actual hybrid deployments and share the benefits of using AWS.
Architecting for Real-Time Insights with Amazon Kinesis (ANT310) - AWS re:Inv...Amazon Web Services
Amazon Kinesis makes it easy to speed up the time it takes for you to get valuable, real-time insights from your streaming data. In this session, we walk through the most popular applications that customers implement using Amazon Kinesis, including streaming extract-transform-load, continuous metric generation, and responsive analytics. Our customer Autodesk joins us to describe how they created real-time metrics generation and analytics using Amazon Kinesis and Amazon Elasticsearch Service. They walk us through their architecture and the best practices they learned in building and deploying their real-time analytics solution.
Analyze Amazon CloudFront and Lambda@Edge Logs to Improve Customer Experience...Amazon Web Services
Nowadays, web servers are often fronted by a global content delivery network, such as Amazon CloudFront, to accelerate delivery of websites, APIs, media content, and other web assets. In this hands-on-workshop, learn to improve website availability, optimize content based on devices, browser and user demographics, identify and analyze CDN usage patterns, and perform end-to-end debugging by correlating logs from various points in a request-response pipeline. Build an end-to-end serverless solution to analyze Amazon CloudFront logs using AWS Glue and Amazon Athena, generate visualization to derive deeper insights using Amazon QuickSight, and correlate with other logs such as CloudWatch logs to provide finer debugging experiences. Discuss how you can extend the pipeline you just built to generate deeper insights needed to improve the overall experience for your users.
Driving Machine Learning and Analytics Use Cases with AWS Storage (STG302) - ...Amazon Web Services
You’ve designed and built a well-architected data lake and ingested extreme amounts of structured and unstructured data. Now what? In this session, we explore real-world use cases where data scientists, developers, and researchers have discovered new and valuable ways to extract business insights using advanced analytics and machine learning. We review Amazon S3, Amazon Glacier, and Amazon EFS, the foundation for the analytics clusters and data engines. We also explore analytics tools and databases, including Amazon Redshift, Amazon Athena, Amazon EMR, Amazon QuickSight, Amazon Kinesis, Amazon RDS, and Amazon Aurora; and we review the AWS machine learning portfolio and AI services such as Amazon SageMaker, AWS Deep Learning AMIs, Amazon Rekognition, and Amazon Lex. We discuss how all of these pieces fit together to build intelligent applications.
Architecture Patterns of Serverless Microservices (ARC304-R1) - AWS re:Invent...Amazon Web Services
In this chalk talk, we describe the architecture patterns you can use to deploy serverless microservices, the design considerations, and best practices.
[NEW LAUNCH!] Building modern applications using Amazon DynamoDB transactions...Amazon Web Services
DynamoDB transactions enables developers to maintain correctness of their data at scale by adding atomicity and isolation guarantees for multi-item conditional updates. With transactions, you can perform a batch of conditional operations including, PutItem, UpdateItem, and DeleteItem with guarantees. Come to this session to learn about how DynamoDB transactions works, the primary use cases in enables, and how to build modern applications that require transactions.
Policy Verification and Enforcement at Scale with AWS (SEC320) - AWS re:Inven...Amazon Web Services
In an ever-growing cloud environment, scaling to a number of accounts can range in the thousands— where edge cases dominate your firm’s spectrum and changes in your environment happen quickly. The Goldman Sachs cloud engineering team finds enforcement of best security practice as a growing concern. With developers managing infrastructure as code (IaC), learn how Goldman Sachs uses distributed serverless logging pipelines and leverages AWS formal verification tools to help enforce access policy in the process. In this session, we cover AWS Config, AWS Lambda, Amazon DynamoDB, and Amazon Simple Notification Service (Amazon SNS) as distributed infrastructure that can help catch security issues early and remediate those that happen unexpectedly.
Don’t Wait Until Tomorrow: From Batch to Streaming (ANT360) - AWS re:Invent 2018Amazon Web Services
In recent years, there has been explosive growth in the number of connected devices and real-time data sources. Data is being produced continuously and its production rate is accelerating. Businesses can no longer wait for hours or days to use this data. To gain the most valuable insights, they must use this data immediately so they can react quickly to new information. In this chalk talk, we discuss how to take advantage of streaming data sources to analyze and react in near-real time. In addition, we present different options for how to solve a real-world scenario and walk through those solutions.
How GumGum Migrated from Cassandra to Amazon DynamoDB (DAT345) - AWS re:Inven...Amazon Web Services
GumGum recently moved to Amazon DynamoDB from Apache Cassandra. In this session, we discuss the architecture and design decisions made in the process, including comparisons of different NoSQL database options. We also share the justifications and steps taken in order to plan and complete the migration process. Finally, we cover the benefits and outcome of the migration, including performance boost, cost savings, and maintenance reductions.
Dissecting Media Asset Management Architecture and Media Archive TCO (MAE301)...Amazon Web Services
Every M&E migration strategy to AWS requires the customer and partners to design and implement a content ingest workflow. These services vary from simple file transfer to fairly complex workflows that do quality control, proxy creation, and metadata augmentation. In this session, we present a baseline process for moving content into a Media Asset Management system in AWS, leveraging common open-source tools for asset registry and using AWS ML services to augment the metadata associated with assets. We also talk about common considerations that M&E organizations should consider when moving their assets and workflows to the cloud. Topics include metadata input, modeling, storage services and policies, security considerations, and managing increased content demands. We also visit the different storage tiers for different archive use cases and offer a TCO model.
Implementing Multi-Region AWS IoT, ft. Analog Devices (IOT401) - AWS re:Inven...Amazon Web Services
Your devices are being shipped across the globe. You have consumers who use their hardware across different countries. How can you build an IoT application that reflects the geographic reach of your devices? In this session, we walk you through the stages of going multi-region with AWS IoT. We first tackle common challenges around setting up your accounts and permissions for AWS IoT. We then dive into different modes of multi-region deployments using multiple AWS services. We also cover the nuances of moving devices across locations and how you can plan, monitor, and execute on your IoT application. Throughout this session, we dive into code and architectures that show the good, the bad, and the ugly of multi-region deployments in IoT, and we share how best to tackle them on day 1 as you take your applications global. We also highlight a customer example from Analog Devices.
Serverless Video Ingestion & Analytics with Amazon Kinesis Video Streams (ANT...Amazon Web Services
Amazon Kinesis Video Streams makes it easy to capture live video, play it back, and store it for real-time and batch-oriented ML-driven analytics. In this session, we first dive deep on the top five best practices for getting started and scaling with Amazon Kinesis Video Streams. Next, we demonstrate a streaming video from a standard USB camera connected to a laptop, and we perform a live playback on a standard browser within minutes. We also have on stage members of Amazon Go, who are building the next generation of physical retail store experiences powered by their "just walk out" technology. They walk through the technical details of their integration with Kinesis Video Streams and highlight their successes and difficulties along the way.
Real-Time Web Analytics with Amazon Kinesis Data Analytics (ADT401) - AWS re:...Amazon Web Services
Knowing what users are doing on your websites in real time provides insights you can act on without waiting for delayed batch processing of clickstream data. Watching the immediate impact on user behavior after new releases, detecting and responding to anomalies, situational awareness, and evaluating trends are all benefits of real-time website analytics. In this workshop, we build a cost-optimized platform to capture web beacon traffic, analyze it for interesting metrics, and display it on a customized dashboard. We start by deploying the Web Analytics Solution Accelerator, then once the core is complete, we extend their solution to capture new and interesting metrics, process those with Amazon Kinesis Analytics, and display new graphs on their custom dashboard. Participants come away with a fully functional system for capturing, analyzing, and displaying valuable website metrics in real time.
Amazon Kinesis makes it easy to collect, process, and analyze real-time, streaming data so you can get timely insights and react quickly to new information. With Amazon Kinesis, you can ingest real-time data such as video, audio, application logs, website clickstreams, and IoT telemetry data for machine learning, analytics, and other applications. In this session, we’ll present an end-to-end streaming data solution including data ingestion, real-time processing, and persistence.
Amazon Kinesis Data Analytics gives us to tools to run SQL queries against active data streams. We'll look at how we can performance real-time log analytics and q build entire streaming applications using SQL, so that you can gain actionable insights promptly.
Level: Intermediate
Speaker: Bill Baldwin - Database Technical Evangelist, AWS
Shift-Left SRE: Self-Healing with AWS Lambda Functions (DEV313-S) - AWS re:In...Amazon Web Services
Even the best continuous delivery and DevOps practices cannot guarantee that there will be no issues in production. The rise of Site Reliability Engineering (SRE) has promoted new ways to automate resilience into your system and applications to circumvent potential problems, but it’s time to “shift-left” this effort into engineering. In this session, learn to leverage AWS Lambda functions as “remediation as code.” We show how to make it part of your continuous delivery process and orchestrate the invocation of Self-Healing Lambda functions in case of unexpected situations impacting the reliability of your system. Gone are the days of traditional operation teams—it’s the rise of “shift-lefters”! This session is brought to you by AWS partner, Dynatrace.
Automate & Audit Cloud Governance & Compliance in Your Landing Zone (ENT315-R...Amazon Web Services
In this session, we explore landing zone considerations as they apply to compliance and auditing. We include such topics as a repeatable approach to SCP and IAM policy creation, internal separation of duty & "need to know", compliance scope ringfencing, Region scoping, 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 compliance assessment tools can be deployed in multi-account environments and their output sensibly interpreted. We encourage you to attend the full AWS Landing Zone track, including SEC303. Search for #awslandingzone in the session catalog.
In this session, learn about the latest features in our cost management tooling. The presentation is given by the Cost Insights service team and supported by cost optimization experts from across our business.
What's New with Amazon Redshift ft. McDonald's (ANT350-R1) - AWS re:Invent 2018Amazon Web Services
Learn about the latest and hottest features of Amazon Redshift. We’ll deep dive into the architecture and inner workings of Amazon Redshift and discuss how the recent availability, performance, and manageability improvements we’ve made can significantly enhance your user experience. We’ll also share glimpse of what we are working on and our plans for the future. McDonald's will join us to share how they leverage a data lake powered by Redshift, Redshift spectrum and Athena to get quick insights.
What Can Your Logs Tell You? (ANT215) - AWS re:Invent 2018Amazon Web Services
Everyone has logs. They’re not the most exciting data that your systems generate, but often, they are the most useful. Across the board, we see customers using Amazon Elasticsearch Service (Amazon ES) to ingest, analyze, and search their log data. In this chalk talk, we discuss how to get your data into Amazon ES, and how to use Kibana to best effect to pull the information you need from the logs you’re generating.
AI/ML with Data Lakes: Counterintuitive Consumer Insights in Retail (RET206) ...Amazon Web Services
In this session, learn how data scientists in the retail industry, from companies like Tapestry, Coach, and Kate Spade, are finding new, counterintuitive consumer insights using AWS artificial intelligence services in a data lake. By leveraging data from various retail systems, including CRM, marketing, e-commerce, point of sale, order management, merchandising, and customer care, we show you how these consumer insights might influence new and interesting retail use cases while establishing a data-driven culture within the organization. Services referenced include Amazon S3, Amazon Machine Learning, Amazon QuickSight, Amazon SageMaker, among others.
DevSecOps: Instituting Cultural Transformation for Public Sector Organization...Amazon Web Services
In this in-depth, interactive workshop, we examine how different public sector customers achieve this shift and analyze common success patterns. We address key points such as continuous compliance, integrating security, and removing people from the data to vastly improve the organization's security posture over traditional operating models. Takeaways include a blueprint for building a DevSecOps operating model in your organization; an understanding the security practitioners' point of view and embracing it to drive innovation; and ways to identify current operating characteristics in your organization and use them to drive a strategy for DevSecOps.
MassMutual Goes Cloud First with Hybrid Cloud on AWS (ENT210) - AWS re:Invent...Amazon Web Services
In this session, we discuss how MassMutual adopts a cloud-first strategy, and we outline their journey to hybrid cloud on AWS. Specifically, we cover four aspects of MassMutual's hybrid cloud on AWS architecture: First, we talk about the use of the AWS Well-Architected Framework to create MassMutual’s cloud minimal viable product (MVP) document. Next, we do a deep dive into MassMutual's multi-account, multi-region architecture. We discuss achieving cloud governance, risk, and compliance through tooling and automation. Finally, we demonstrate how MassMutual deploys fully compliant hybrid cloud environments in less than five minutes. We also showcase some of MassMutual's actual hybrid deployments and share the benefits of using AWS.
Architecting for Real-Time Insights with Amazon Kinesis (ANT310) - AWS re:Inv...Amazon Web Services
Amazon Kinesis makes it easy to speed up the time it takes for you to get valuable, real-time insights from your streaming data. In this session, we walk through the most popular applications that customers implement using Amazon Kinesis, including streaming extract-transform-load, continuous metric generation, and responsive analytics. Our customer Autodesk joins us to describe how they created real-time metrics generation and analytics using Amazon Kinesis and Amazon Elasticsearch Service. They walk us through their architecture and the best practices they learned in building and deploying their real-time analytics solution.
Analyze Amazon CloudFront and Lambda@Edge Logs to Improve Customer Experience...Amazon Web Services
Nowadays, web servers are often fronted by a global content delivery network, such as Amazon CloudFront, to accelerate delivery of websites, APIs, media content, and other web assets. In this hands-on-workshop, learn to improve website availability, optimize content based on devices, browser and user demographics, identify and analyze CDN usage patterns, and perform end-to-end debugging by correlating logs from various points in a request-response pipeline. Build an end-to-end serverless solution to analyze Amazon CloudFront logs using AWS Glue and Amazon Athena, generate visualization to derive deeper insights using Amazon QuickSight, and correlate with other logs such as CloudWatch logs to provide finer debugging experiences. Discuss how you can extend the pipeline you just built to generate deeper insights needed to improve the overall experience for your users.
Driving Machine Learning and Analytics Use Cases with AWS Storage (STG302) - ...Amazon Web Services
You’ve designed and built a well-architected data lake and ingested extreme amounts of structured and unstructured data. Now what? In this session, we explore real-world use cases where data scientists, developers, and researchers have discovered new and valuable ways to extract business insights using advanced analytics and machine learning. We review Amazon S3, Amazon Glacier, and Amazon EFS, the foundation for the analytics clusters and data engines. We also explore analytics tools and databases, including Amazon Redshift, Amazon Athena, Amazon EMR, Amazon QuickSight, Amazon Kinesis, Amazon RDS, and Amazon Aurora; and we review the AWS machine learning portfolio and AI services such as Amazon SageMaker, AWS Deep Learning AMIs, Amazon Rekognition, and Amazon Lex. We discuss how all of these pieces fit together to build intelligent applications.
Architecture Patterns of Serverless Microservices (ARC304-R1) - AWS re:Invent...Amazon Web Services
In this chalk talk, we describe the architecture patterns you can use to deploy serverless microservices, the design considerations, and best practices.
[NEW LAUNCH!] Building modern applications using Amazon DynamoDB transactions...Amazon Web Services
DynamoDB transactions enables developers to maintain correctness of their data at scale by adding atomicity and isolation guarantees for multi-item conditional updates. With transactions, you can perform a batch of conditional operations including, PutItem, UpdateItem, and DeleteItem with guarantees. Come to this session to learn about how DynamoDB transactions works, the primary use cases in enables, and how to build modern applications that require transactions.
Policy Verification and Enforcement at Scale with AWS (SEC320) - AWS re:Inven...Amazon Web Services
In an ever-growing cloud environment, scaling to a number of accounts can range in the thousands— where edge cases dominate your firm’s spectrum and changes in your environment happen quickly. The Goldman Sachs cloud engineering team finds enforcement of best security practice as a growing concern. With developers managing infrastructure as code (IaC), learn how Goldman Sachs uses distributed serverless logging pipelines and leverages AWS formal verification tools to help enforce access policy in the process. In this session, we cover AWS Config, AWS Lambda, Amazon DynamoDB, and Amazon Simple Notification Service (Amazon SNS) as distributed infrastructure that can help catch security issues early and remediate those that happen unexpectedly.
Don’t Wait Until Tomorrow: From Batch to Streaming (ANT360) - AWS re:Invent 2018Amazon Web Services
In recent years, there has been explosive growth in the number of connected devices and real-time data sources. Data is being produced continuously and its production rate is accelerating. Businesses can no longer wait for hours or days to use this data. To gain the most valuable insights, they must use this data immediately so they can react quickly to new information. In this chalk talk, we discuss how to take advantage of streaming data sources to analyze and react in near-real time. In addition, we present different options for how to solve a real-world scenario and walk through those solutions.
How GumGum Migrated from Cassandra to Amazon DynamoDB (DAT345) - AWS re:Inven...Amazon Web Services
GumGum recently moved to Amazon DynamoDB from Apache Cassandra. In this session, we discuss the architecture and design decisions made in the process, including comparisons of different NoSQL database options. We also share the justifications and steps taken in order to plan and complete the migration process. Finally, we cover the benefits and outcome of the migration, including performance boost, cost savings, and maintenance reductions.
Dissecting Media Asset Management Architecture and Media Archive TCO (MAE301)...Amazon Web Services
Every M&E migration strategy to AWS requires the customer and partners to design and implement a content ingest workflow. These services vary from simple file transfer to fairly complex workflows that do quality control, proxy creation, and metadata augmentation. In this session, we present a baseline process for moving content into a Media Asset Management system in AWS, leveraging common open-source tools for asset registry and using AWS ML services to augment the metadata associated with assets. We also talk about common considerations that M&E organizations should consider when moving their assets and workflows to the cloud. Topics include metadata input, modeling, storage services and policies, security considerations, and managing increased content demands. We also visit the different storage tiers for different archive use cases and offer a TCO model.
Implementing Multi-Region AWS IoT, ft. Analog Devices (IOT401) - AWS re:Inven...Amazon Web Services
Your devices are being shipped across the globe. You have consumers who use their hardware across different countries. How can you build an IoT application that reflects the geographic reach of your devices? In this session, we walk you through the stages of going multi-region with AWS IoT. We first tackle common challenges around setting up your accounts and permissions for AWS IoT. We then dive into different modes of multi-region deployments using multiple AWS services. We also cover the nuances of moving devices across locations and how you can plan, monitor, and execute on your IoT application. Throughout this session, we dive into code and architectures that show the good, the bad, and the ugly of multi-region deployments in IoT, and we share how best to tackle them on day 1 as you take your applications global. We also highlight a customer example from Analog Devices.
Serverless Video Ingestion & Analytics with Amazon Kinesis Video Streams (ANT...Amazon Web Services
Amazon Kinesis Video Streams makes it easy to capture live video, play it back, and store it for real-time and batch-oriented ML-driven analytics. In this session, we first dive deep on the top five best practices for getting started and scaling with Amazon Kinesis Video Streams. Next, we demonstrate a streaming video from a standard USB camera connected to a laptop, and we perform a live playback on a standard browser within minutes. We also have on stage members of Amazon Go, who are building the next generation of physical retail store experiences powered by their "just walk out" technology. They walk through the technical details of their integration with Kinesis Video Streams and highlight their successes and difficulties along the way.
Real-Time Web Analytics with Amazon Kinesis Data Analytics (ADT401) - AWS re:...Amazon Web Services
Knowing what users are doing on your websites in real time provides insights you can act on without waiting for delayed batch processing of clickstream data. Watching the immediate impact on user behavior after new releases, detecting and responding to anomalies, situational awareness, and evaluating trends are all benefits of real-time website analytics. In this workshop, we build a cost-optimized platform to capture web beacon traffic, analyze it for interesting metrics, and display it on a customized dashboard. We start by deploying the Web Analytics Solution Accelerator, then once the core is complete, we extend their solution to capture new and interesting metrics, process those with Amazon Kinesis Analytics, and display new graphs on their custom dashboard. Participants come away with a fully functional system for capturing, analyzing, and displaying valuable website metrics in real time.
Amazon Kinesis makes it easy to collect, process, and analyze real-time, streaming data so you can get timely insights and react quickly to new information. With Amazon Kinesis, you can ingest real-time data such as video, audio, application logs, website clickstreams, and IoT telemetry data for machine learning, analytics, and other applications. In this session, we’ll present an end-to-end streaming data solution including data ingestion, real-time processing, and persistence.
Amazon Kinesis Data Analytics gives us to tools to run SQL queries against active data streams. We'll look at how we can performance real-time log analytics and q build entire streaming applications using SQL, so that you can gain actionable insights promptly.
Level: Intermediate
Speaker: Bill Baldwin - Database Technical Evangelist, AWS
Amazon Kinesis Data Analytics gives us to tools to run SQL queries against active data streams. We'll look at how we can performance real-time log analytics and q build entire streaming applications using SQL, so that you can gain actionable insights promptly.
by Ben Willett, Solutions Architect AWS
AWS Data & Analytics Week is an opportunity to learn about Amazon’s family of managed analytics services. These services provide easy, scalable, reliable, and cost-effective ways to manage your data in the cloud. We explain the fundamentals and take a technical deep dive into Amazon Redshift data warehouse; Data Lake services including Amazon EMR, Amazon Athena, & Amazon Redshift Spectrum; Log Analytics with Amazon Elasticsearch Service; and data preparation and placement services with AWS Glue and Amazon Kinesis. You'll will learn how to get started, how to support applications, and how to scale.
by Darin Briskman, Technical Evangelist, AWS
Amazon Kinesis Data Analytics gives us to tools to run SQL queries against active data streams. We'll look at how we can performance real-time log analytics and q build entire streaming applications using SQL, so that you can gain actionable insights promptly.
Data Analytics Week at the San Francisco Loft
Analyzing Streams
Amazon Kinesis Data Analytics gives us to tools to run SQL queries against active data streams. We'll look at how we can performance real-time log analytics and q build entire streaming applications using SQL, so that you can gain actionable insights promptly.
Speakers:
Saurabh Shrivastava - Partner Solutions Architect, AWS
Tayo Olajide - Cloud Architect, AWS
Analyzing Streams: Data Analytics Week at the San Francisco Loft
Amazon Kinesis Data Analytics gives us to tools to run SQL queries against active data streams. We'll look at how we can performance real-time log analytics and q build entire streaming applications using SQL, so that you can gain actionable insights promptly.
Level: Intermediate
Speakers:
Ben Willett - Solutions Architect, AWS
Ahmed Gaafar - Technical Account Manager, AWS
by Rajeev Srinivasan, Sr. Solutions Architect and Gautam Srinivasan, Solutions Architect, AWS
Amazon Kinesis Data Analytics gives us to tools to run SQL queries against active data streams. We'll look at how we can performance real-time log analytics and q build entire streaming applications using SQL, so that you can gain actionable insights promptly.
BDA307 Analyzing Data Streams in Real Time with Amazon KinesisAmazon Web Services
Amazon Kinesis makes it easy to collect, process, and analyze real-time, streaming data so you can get timely insights and react quickly to new information. In this session, we first present an end-to-end streaming data solution using Kinesis Data Streams for data ingestion, Kinesis Data Analytics for real-time processing, and Kinesis Data Firehose for persistence. Then, Zynga talks about how they analyze real-time game events that are triggered by player actions, and shares best practices for processing streaming data at scale.
Build an AWS Analytics Solution to Monitor the Video Streaming Experience (MA...Amazon Web Services
In this workshop, we build and deploy an end-to-end analytics solution for monitoring the video streaming experience. We integrate an open source video player with Amazon Kinesis Data Streams to capture events in real time. We explore the data available for capture and a variety of use cases: from generating alerts on poor experience to content recommendations based on user behavior. We also show you how this real-time data can be archived in a data lake and further used to generate reports of aggregate performance and experience across a number of dimensions.
In this workshop you'll explore approaches for processing data using serverless architectures. You'll build processing infrastructure to enable operations personnel in Wild Rydes headquarters to monitor the health of the unicorn fleet. Each unicorn is equipped with a sensor that reports its location and vitals and you'll explore approaches for processing this data in batches and real-time.
To build this infrastructure, you will use AWS Lambda, Amazon S3, Amazon Kinesis, Amazon DynamoDB, and Amazon Athena. You'll create functions in Lambda to process files and streams, use DynamoDB to persist unicorn vitals, create a serverless application to aggregate these data points using Kinesis Analytics, archive the raw data using Kinesis Firehose and Amazon S3, and you'll use Amazon Athena to run ad-hoc queries against the raw data.
Serverless Stream Processing Tips & Tricks - BDA311 - Chicago AWS SummitAmazon Web Services
In this interactive session, we review how AWS Lambda can be used to process your streaming data with Amazon Kinesis. We explain in detail the integration between Lambda and Kinesis and discuss how to avoid the most common issues that customers face today.
Real Time Data Ingestion & Analysis - AWS Summit Sydney 2018Amazon Web Services
Real Time Data Ingestion and Analysis
In this session you will learn how to perform real time data analytics on streaming data using Amazon Kinesis Streams and run prediction algorithms. Learn how to stream your Cloud Trail logs to Amazon Kinesis Streams and identify anomalies using Spark Stream analytics and Amazon Kinesis Data Analytics.
Ganesh Raja, Big Data Solutions Architect, Amazon Web Services
ABD301-Analyzing Streaming Data in Real Time with Amazon KinesisAmazon Web Services
Amazon Kinesis makes it easy to collect, process, and analyze real-time, streaming data so you can get timely insights and react quickly to new information. In this session, we present an end-to-end streaming data solution using Kinesis Streams for data ingestion, Kinesis Analytics for real-time processing, and 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 Kinesis Analytics applications. Lastly, we discuss how to estimate the cost of the entire system.
Serverless Stream Processing Pipeline Best Practices (SRV316-R1) - AWS re:Inv...Amazon Web Services
Real-time analytics has traditionally been analyzed using batch processing in DWH/Hadoop environments. Common use cases use data lakes, data science, and machine learning (ML). Creating serverless data-driven architecture and serverless streaming solutions with services like Amazon Kinesis, AWS Lambda, and Amazon Athena can solve real-time ingestion, storage, and analytics challenges, and help you focus on application logic without managing infrastructure. In this session, we introduce design patterns, best practices, and share customer journeys from batch to real-time insights in building modern serverless data-driven architecture applications. Hear how Intel built the Intel Pharma Analytics Platform using a serverless architecture. This AI cloud-based offering enables remote monitoring of patients using an array of sensors, wearable devices, and ML algorithms to objectively quantify the impact of interventions and power clinical studies in various therapeutics conditions.
Introduction to Real-Time Streaming Analytics - Amazon Kinesis State Of Union...Amazon Web Services
Serverless streaming applications Lambda+Kinesis Data Analytics/Kinesis Data Firehose - how to solve common streaming problems using serverless architecture and learn how customers like GE, Comcast, Lyft and more are using Amazon Kinesis.
Analyzing Streaming Data in Real-time - AWS Summit Cape Town 2018Amazon Web Services
Speaker: Tara Walker, AWS
Customer Speaker: Digitata
Level: 200
Amazon Kinesis is a platform for streaming data on AWS, offering powerful services to make it easy to load and analyze streaming data. With Amazon Kinesis, you can ingest real-time data such as video, audio, application logs, website clickstreams, and IoT telemetry data for machine learning, analytics, and other applications. In this session, we will provide an overview of streaming data applications with the Amazon Kinesis platform and present an end-to-end streaming data solution including data ingestion, real-time processing, and persistence.
Keeping the Pace with Data Ingestion (GPSCT402) - AWS re:Invent 2018Amazon Web Services
Data is eating the world. Don't let it consume your organization! In this talk, we take a deep dive into the various methods of ingesting the ever-increasing amount of data that your organization is generating, and we discuss how to effectively leverage that data as part of your data analytics pipeline. We cover topics such as batch and real-time ingestion with AWS services and open source tools. We also dive into some reference architecture implementations of common ingestion patterns. Finally, we discuss how you can make this data useful through catalogs and governance.
Similar to Using Apache Flink with Amazon Kinesis (ANT395) - AWS re:Invent 2018 (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.