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.
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.
How TrueCar Gains Actionable Insights with Splunk Cloud PPTAmazon Web Services
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.
This session will highlight the most impactful announcements made at AWS re:Invent 2017 while giving you ideas on key use cases for new services and features. We’ll cover major themes of the conference, the new services and features within those themes and how they work together to make it faster and easier to build functionality into your app.
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.
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
Amazon Aurora is a relational database built for the cloud and is compatible with MySQL and PostgreSQL. It combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open-source databases. We'll cover some of the key innovations in the Aurora database engine and storage layers, explain recently announced features, such as Aurora Serverless, Aurora Multi-Master, and Aurora Parallel Query, and discuss best practices and optimal configurations. See why Aurora is a great fit for new application development and for migrations from overpriced, restrictive commercial databases.
AWS DeepLens Workshop_Build Computer Vision Applications Amazon Web Services
In this workshop, developers have the opportunity to learn how to build and deploy computer vision models using the AWS DeepLens deep-learning-enabled video camera. By working hands on, developers of all skill levels can explore and build their own deep-learning-powered computer vision applications using Amazon SageMaker and AWS DeepLens devices. Attendees can experiment with different sample projects for face detection, object detection, artistic style transfer, and other machine learning use cases using Apache MXNet. Attendees also learn about use cases that integrate other AWS services that extend the functionality of AWS DeepLens, such as AWS Lambda, Amazon Polly, and Amazon Rekognition.
Enabling a Digital Platform with Microservices Architecture (ARC218-S) - AWS ...Amazon Web Services
Bajaj Finserv Direct Limited (BFDL) serves millions of customers with its comprehensive portfolio and innovative offerings in financing, general insurance, life and health insurance and retirement and savings. BFDL envisioned building a cloud-native digital platform to offer an unmatched experience to its customers. In this session, hear from BDFL how they built a robust digital backbone on AWS with a scalable microservices architecture deployed using Docker containers. The session also focuses on how a scalable microservices-based architecture can be developed using various AWS services. This session is brought to you by AWS partner, Cognizant Technology Solutions US Corp.
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.
How TrueCar Gains Actionable Insights with Splunk Cloud PPTAmazon Web Services
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.
This session will highlight the most impactful announcements made at AWS re:Invent 2017 while giving you ideas on key use cases for new services and features. We’ll cover major themes of the conference, the new services and features within those themes and how they work together to make it faster and easier to build functionality into your app.
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.
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
Amazon Aurora is a relational database built for the cloud and is compatible with MySQL and PostgreSQL. It combines the speed and availability of high-end commercial databases with the simplicity and cost-effectiveness of open-source databases. We'll cover some of the key innovations in the Aurora database engine and storage layers, explain recently announced features, such as Aurora Serverless, Aurora Multi-Master, and Aurora Parallel Query, and discuss best practices and optimal configurations. See why Aurora is a great fit for new application development and for migrations from overpriced, restrictive commercial databases.
AWS DeepLens Workshop_Build Computer Vision Applications Amazon Web Services
In this workshop, developers have the opportunity to learn how to build and deploy computer vision models using the AWS DeepLens deep-learning-enabled video camera. By working hands on, developers of all skill levels can explore and build their own deep-learning-powered computer vision applications using Amazon SageMaker and AWS DeepLens devices. Attendees can experiment with different sample projects for face detection, object detection, artistic style transfer, and other machine learning use cases using Apache MXNet. Attendees also learn about use cases that integrate other AWS services that extend the functionality of AWS DeepLens, such as AWS Lambda, Amazon Polly, and Amazon Rekognition.
Enabling a Digital Platform with Microservices Architecture (ARC218-S) - AWS ...Amazon Web Services
Bajaj Finserv Direct Limited (BFDL) serves millions of customers with its comprehensive portfolio and innovative offerings in financing, general insurance, life and health insurance and retirement and savings. BFDL envisioned building a cloud-native digital platform to offer an unmatched experience to its customers. In this session, hear from BDFL how they built a robust digital backbone on AWS with a scalable microservices architecture deployed using Docker containers. The session also focuses on how a scalable microservices-based architecture can be developed using various AWS services. This session is brought to you by AWS partner, Cognizant Technology Solutions US Corp.
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.
Building Serverless Analytics Solutions with Amazon QuickSight (ANT391) - AWS...Amazon Web Services
Querying and analyzing big data can be complicated and expensive. It requires you to setup and manage databases, data warehouses, and business intelligence (BI) applications—all of which require time, effort, and resources. Using Amazon Athena and Amazon QuickSight, you can avoid the cost and complexity by creating a fast, scalable, and serverless cloud analytics solution without the need to invest in databases, data warehouses, complex ETL solutions, and BI applications. In this session, we demonstrate how you can build a serverless big data analytics solution using Amazon Athena and Amazon QuickSight.
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.
Visualize your data in Data Lake with AWS Athena and AWS Quicksight Hands-on ...Amazon Web Services
Level 200: Visualize Your Data in Data Lake with AWS Athena and AWS Quicksight
Nowadays, enterprises are building Data Lake which store lots of structured and unstructured data for data analysis. But it takes lots of time for building the data modeling and infrastructure that is required. How to make quick data queries without servers and databases is the next big question for every enterprises.
In this workshop, eCloudvalley, the first and only Premier Consulting Partner in GCR, will demonstrate how to use serverless architecture to visualize your data using Amazon Athena and Amazon Quicksight.
You can easily query and visualize the data in your S3, and get business insights with the combination of these two services. Also, you can also build business reports with other tools such as AWS IoT, Amazon Kinesis Firehose.
Reason to Attend:
Learn how to quickly search for thousands of data on S3 via serverless Amazon's Athena
Learn how to use AWS QuickSight to retrieve information from your database quickly and create detailed reports
Building Data Lakes and Analytics on AWS. IPExpo Manchester.javier ramirez
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 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, AWS Glue, Amazon Redshift, Amazon Athena, Amazon EMR, Amazon Kinesis, and even Amazon Machine Learning services are put together to build a successful data lake for various role including both data scientists and business users.
Effective Data Lakes: Challenges and Design Patterns (ANT316) - AWS re:Invent...Amazon Web Services
Data lakes are emerging as the most common architecture built in data-driven organizations today. A data lake enables you to store unstructured, semi-structured, or fully-structured raw data as well as processed data for different types of analytics—from dashboards and visualizations to big data processing, real-time analytics, and machine learning. Well-designed data lakes ensure that organizations get the most business value from their data assets. In this session, you learn about the common challenges and patterns for designing an effective data lake on the AWS Cloud, with wisdom distilled from various customer implementations. We walk through patterns to solve data lake challenges, like real-time ingestion, choosing a partitioning strategy, file compaction techniques, database replication to your data lake, handling mutable data, machine learning integration, security patterns, and more.
Analyze your Data Lake, Fast @ Any Scale - AWS Online Tech TalksAmazon Web Services
Learning Objectives:
-Learn how to automatically discover, catalog, and prepare your data for analytics
-Understand how to query data in your data lake without having to transform or load the data into your data warehouse
-See how to analyze data in both your data lake and data warehouse
Building Your First Serverless Data Lake (ANT356-R1) - AWS re:Invent 2018Amazon Web Services
In this session, you have the opportunity to learn the fundamental building blocks of a data lake on AWS. You design and build a serverless pipeline to ingest, process, optimize and query data in your very own data lake. We discuss different optimizations and best practices to tune your architecture for future growth.
The Future of Enterprise Applications is Serverless (ENT314-R1) - AWS re:Inve...Amazon Web Services
At re:Invent 2014, we announced AWS Lambda and ushered in a whole new world of application design, one without the need to manage or think about traditional server infrastructure. Since then, serverless has become one of the hottest topics in the industry. Customers like Capital One and Coca Cola talk about how serverless saved them time and money, helped them reduce their operational burden, and drove developer agility and innovation. What is serverless, and what are the key trends you should be aware of? Where does one start on the journey of building serverless applications? We cover all of this and more in this session.
Developing with .NET Core on AWS: What's New (DEV318-R1) - AWS re:Invent 2018Amazon Web Services
In this demonstration-heavy session, we illustrate our latest techniques, tools, and libraries for developing end-to-end applications with .NET Core. We focus on serverless applications, but the techniques are broadly relevant. We start by showing you some useful features and best practices for authoring your serverless application, including debugging locally from the IDE and in production. From there, we demonstrate some helpful tools that make it easy to set up your CI/CD workflow from the start. Finally, we deploy our application with AWS Lambda.
Analyzing your web and application logs with the Amazon Elasticsearch Service...javier ramirez
This presentation shows how you can use the Amazon Elasticsearch Service in general, and in particular I showcase how you can host a static website, use CloudFront as a global CDN, and process HTTP logs using serverless functions with Lambda to ingest into ElasticSearch. I finish by creating a Kibana dashboard. Live demo was done in Stockholm and Oslo, and screenshots are included. Also included the URL for you to build the demo by yourself
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.
Running Your SQL Server Database on Amazon RDS (DAT329) - AWS re:Invent 2018Amazon Web Services
In this session, learn how to run SQL Server on Amazon RDS, best practices for migration from on-premises or Amazon EC2 into Amazon RDS, and the pros and cons of running in Amazon RDS for SQL Server today. We also discuss workarounds for customer needs that are not supported today with Amazon RDS.
[REPEAT 1] Executing a Large-Scale Migration to AWS (ENT205-R1) - AWS re:Inve...Amazon Web Services
We have partnered with hundreds of customers in their large-scale migration to the AWS Cloud. In this session, we discuss some of the common challenges that our customers have faced during these migrations and how they overcame them. We also describe the patterns that make migrations successful and the mechanisms we created to help our customers migrate faster.
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
SRV307 Applying AWS Purpose-Built Database Strategy: Match Your Workload to ...Amazon Web Services
In this session, Tony Petrossian, director of engineering, AWS Database Services, dives deep into what databases to use for which components of your application. Learn how to evaluate a new workload for the best managed database option based on specific application needs related to data shape, data size at limit, computational requirements, programmability, throughput and latency needs, etc. This session explains the ideal use cases for relational and non-relational database services, including Amazon Aurora, Amazon DynamoDB, Amazon ElastiCache for Redis, Amazon Neptune, and Amazon Redshift.
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? In this talk, we’ll cover security in the CI/CD pipeline, and share hard-earned lessons around potential opportunities in your security program, along with practical steps to improve the agility of your organization.
Speaker: Bill Reid - Sr Mgr, Solutions Architecture AWS
AWS Security Week: Humans & Data Don’t Mix - Best Practices to Secure Your CloudAmazon Web Services
AWS Security Week at the San Francisco Loft: Humans & Data Don’t Mix - Best Practices to Secure Your Cloud
Presenter: William Reid, CISM, FIP
Head of Security and Compliance Solution Architecture, AWS
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.
Building Serverless Analytics Solutions with Amazon QuickSight (ANT391) - AWS...Amazon Web Services
Querying and analyzing big data can be complicated and expensive. It requires you to setup and manage databases, data warehouses, and business intelligence (BI) applications—all of which require time, effort, and resources. Using Amazon Athena and Amazon QuickSight, you can avoid the cost and complexity by creating a fast, scalable, and serverless cloud analytics solution without the need to invest in databases, data warehouses, complex ETL solutions, and BI applications. In this session, we demonstrate how you can build a serverless big data analytics solution using Amazon Athena and Amazon QuickSight.
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.
Visualize your data in Data Lake with AWS Athena and AWS Quicksight Hands-on ...Amazon Web Services
Level 200: Visualize Your Data in Data Lake with AWS Athena and AWS Quicksight
Nowadays, enterprises are building Data Lake which store lots of structured and unstructured data for data analysis. But it takes lots of time for building the data modeling and infrastructure that is required. How to make quick data queries without servers and databases is the next big question for every enterprises.
In this workshop, eCloudvalley, the first and only Premier Consulting Partner in GCR, will demonstrate how to use serverless architecture to visualize your data using Amazon Athena and Amazon Quicksight.
You can easily query and visualize the data in your S3, and get business insights with the combination of these two services. Also, you can also build business reports with other tools such as AWS IoT, Amazon Kinesis Firehose.
Reason to Attend:
Learn how to quickly search for thousands of data on S3 via serverless Amazon's Athena
Learn how to use AWS QuickSight to retrieve information from your database quickly and create detailed reports
Building Data Lakes and Analytics on AWS. IPExpo Manchester.javier ramirez
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 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, AWS Glue, Amazon Redshift, Amazon Athena, Amazon EMR, Amazon Kinesis, and even Amazon Machine Learning services are put together to build a successful data lake for various role including both data scientists and business users.
Effective Data Lakes: Challenges and Design Patterns (ANT316) - AWS re:Invent...Amazon Web Services
Data lakes are emerging as the most common architecture built in data-driven organizations today. A data lake enables you to store unstructured, semi-structured, or fully-structured raw data as well as processed data for different types of analytics—from dashboards and visualizations to big data processing, real-time analytics, and machine learning. Well-designed data lakes ensure that organizations get the most business value from their data assets. In this session, you learn about the common challenges and patterns for designing an effective data lake on the AWS Cloud, with wisdom distilled from various customer implementations. We walk through patterns to solve data lake challenges, like real-time ingestion, choosing a partitioning strategy, file compaction techniques, database replication to your data lake, handling mutable data, machine learning integration, security patterns, and more.
Analyze your Data Lake, Fast @ Any Scale - AWS Online Tech TalksAmazon Web Services
Learning Objectives:
-Learn how to automatically discover, catalog, and prepare your data for analytics
-Understand how to query data in your data lake without having to transform or load the data into your data warehouse
-See how to analyze data in both your data lake and data warehouse
Building Your First Serverless Data Lake (ANT356-R1) - AWS re:Invent 2018Amazon Web Services
In this session, you have the opportunity to learn the fundamental building blocks of a data lake on AWS. You design and build a serverless pipeline to ingest, process, optimize and query data in your very own data lake. We discuss different optimizations and best practices to tune your architecture for future growth.
The Future of Enterprise Applications is Serverless (ENT314-R1) - AWS re:Inve...Amazon Web Services
At re:Invent 2014, we announced AWS Lambda and ushered in a whole new world of application design, one without the need to manage or think about traditional server infrastructure. Since then, serverless has become one of the hottest topics in the industry. Customers like Capital One and Coca Cola talk about how serverless saved them time and money, helped them reduce their operational burden, and drove developer agility and innovation. What is serverless, and what are the key trends you should be aware of? Where does one start on the journey of building serverless applications? We cover all of this and more in this session.
Developing with .NET Core on AWS: What's New (DEV318-R1) - AWS re:Invent 2018Amazon Web Services
In this demonstration-heavy session, we illustrate our latest techniques, tools, and libraries for developing end-to-end applications with .NET Core. We focus on serverless applications, but the techniques are broadly relevant. We start by showing you some useful features and best practices for authoring your serverless application, including debugging locally from the IDE and in production. From there, we demonstrate some helpful tools that make it easy to set up your CI/CD workflow from the start. Finally, we deploy our application with AWS Lambda.
Analyzing your web and application logs with the Amazon Elasticsearch Service...javier ramirez
This presentation shows how you can use the Amazon Elasticsearch Service in general, and in particular I showcase how you can host a static website, use CloudFront as a global CDN, and process HTTP logs using serverless functions with Lambda to ingest into ElasticSearch. I finish by creating a Kibana dashboard. Live demo was done in Stockholm and Oslo, and screenshots are included. Also included the URL for you to build the demo by yourself
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.
Running Your SQL Server Database on Amazon RDS (DAT329) - AWS re:Invent 2018Amazon Web Services
In this session, learn how to run SQL Server on Amazon RDS, best practices for migration from on-premises or Amazon EC2 into Amazon RDS, and the pros and cons of running in Amazon RDS for SQL Server today. We also discuss workarounds for customer needs that are not supported today with Amazon RDS.
[REPEAT 1] Executing a Large-Scale Migration to AWS (ENT205-R1) - AWS re:Inve...Amazon Web Services
We have partnered with hundreds of customers in their large-scale migration to the AWS Cloud. In this session, we discuss some of the common challenges that our customers have faced during these migrations and how they overcame them. We also describe the patterns that make migrations successful and the mechanisms we created to help our customers migrate faster.
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
SRV307 Applying AWS Purpose-Built Database Strategy: Match Your Workload to ...Amazon Web Services
In this session, Tony Petrossian, director of engineering, AWS Database Services, dives deep into what databases to use for which components of your application. Learn how to evaluate a new workload for the best managed database option based on specific application needs related to data shape, data size at limit, computational requirements, programmability, throughput and latency needs, etc. This session explains the ideal use cases for relational and non-relational database services, including Amazon Aurora, Amazon DynamoDB, Amazon ElastiCache for Redis, Amazon Neptune, and Amazon Redshift.
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? In this talk, we’ll cover security in the CI/CD pipeline, and share hard-earned lessons around potential opportunities in your security program, along with practical steps to improve the agility of your organization.
Speaker: Bill Reid - Sr Mgr, Solutions Architecture AWS
AWS Security Week: Humans & Data Don’t Mix - Best Practices to Secure Your CloudAmazon Web Services
AWS Security Week at the San Francisco Loft: Humans & Data Don’t Mix - Best Practices to Secure Your Cloud
Presenter: William Reid, CISM, FIP
Head of Security and Compliance Solution Architecture, AWS
This session is designed to introduce you to fundamental cloud computing and AWS security concepts that will help you prepare for the Security Week sessions, demos, and workshops. We will also provide an overview of the Security pillar of the AWS Cloud Adoption Framework (CAF) and talk about how AWS keeps humans away from data—and how you can, too.
Level: 100
Speaker: Don Edwards - Sr. Technical Delivery Manager, AWS
This session is designed to introduce you to fundamental cloud computing and AWS security concepts that will help you prepare for the Security Week sessions, demos, and workshops. We will also provide an overview of the Security pillar of the AWS Cloud Adoption Framework (CAF) and talk about how AWS keeps humans away from data—and how you can, too.
Iolaire Mckinnon, Senior Consultant, Security, Risk & Compliance, AWS
A Deep Dive into the best practice guidelines for securing your workloads in AWS cloud.
Introduction to AWS Security: Security Week at the SF LoftAmazon Web Services
Introduction to AWS Security: Security Week at the San Francisco Loft
This session is designed to introduce you to fundamental cloud computing and AWS security concepts that will help you prepare for the Security Week sessions, demos, and workshops. We will also provide an overview of the Security pillar of the AWS Cloud Adoption Framework (CAF) and talk about how AWS keeps humans away from data—and how you can, too.
Level: 100
Speaker: Bill Reid - Sr. Manager, Solutions Architecture, AWS
Lock it Down: How to Secure your AWS Account and your Organization's AccountsAmazon Web Services
The cloud enables users to run workloads in a more secure fashion than what typically can be done in a traditional data-center. However, customers are still not sure how to actually harden their AWS accounts and resources and make sure compliance is being enforced. When large customers have multiple accounts, ensuring consistency around governance can also be of concern. In this session, we will review how to use automation, tools, and techniques to harden and audit your AWS account and also how to leverage AWS Organizations to ensure compliance in your enterprise.
What if security became the reason to move an application to the cloud? Historically, security has been a necessary afterthought. Today, with AWS, security is moving from obligation to advantage. Here, you'll get a glimpse of tools and techniques that enterprise customers are using today to secure their AWS environments at scale.
Lock It Down: How to Secure Your Organization's AWS AccountAmazon Web Services
The cloud enables users to run workloads in a more secure fashion than what typically can be done in a traditional datacenter. However, many customers are still not sure how to actually harden their AWS accounts and resources and make sure compliance is being enforced. When large customers have multiple accounts, ensuring consistency around governance can also be of concern. In this session we will review how to use automation, tools and techniques to harden and audit your AWS accounts and also how to leverage AWS Organizations to ensure compliance in your enterprise.
Geordie Anderson, Security Specialist Solutions Architect, Amazon Web Services
Sean Donaghy, Senior Cyber Security Advisor, Canadian Centre for Cyber Security, Communications Security Establishment, Government of Canada
Michael Davie, Security Engineer, Canadian Centre for Cyber Security, Communications Security Establishment, Government of Canada
In this talk, we will introduce several methods of threat detection and remediation on AWS, including GuardDuty, Macie, WAF, Shield, Lambda, AWS Config, Systems Manager and Inspector. We will do a brief overview of each of these services, and then talk about how to put them all together, to have a comprehensive thread detection and remediation solution. We will also discuss how to use these services across multiple AWS accounts and regions, to cover the governance needs of enterprise AWS deployments.
This session will review how to secure your enterprise adoption of AWS at scale. At AWS security is job zero and at the heart of everything we build. This session will review the patterns of usage for AWS Identity and Access Management, AWS Key Management Service, AWS CloudTrail, AWS Config, Amazon GuardDuty AWS Systems Manager Parameter Store, Amazon EC2 Run Command, AWS Single Sign-On, AWS WAF, AWS Shield, and AWS Service Catalog to an create end-to-end security approach for your AWS cloud adoption. You will gain insight how these AWS services come together to increase your security posture in ways that are unique to AWS workloads.
Building the Technical Foundation for Your Security Practice (GPSCT205) - AWS...Amazon Web Services
Security is job zero at AWS. Come and learn how to build a modern security practice on AWS and supercharge it with AWS partners and serverless automation. Learn about the Security Perspectives found the AWS Well-Architected Framework, which equip your security program to not only keep your environment secure but also move fast. Learn advanced techniques to empower your teams with Amazon GuardDuty so you can elevate your team's ability to identify, protect, detect, respond, and recover from security events.
Module 3: Security, Identity and Access Management
This module will cover:
Data Center Security
AWS Identity and Access Management (IAM) concepts including users, groups, roles and policies
Security best practices the well-architected way - SDD318 - AWS re:Inforce 2019 Amazon Web Services
As you continually evolve your use of the AWS platform, it’s important to consider ways to improve your security posture and take advantage of new security services and features. In this advanced session, we share architectural patterns for meeting common challenges, service limits and tips, tricks, and ways to continually evaluate your architecture against best practices. Automation and tools are featured throughout, and there will be code giveaways! Be prepared for a technically deep session on AWS security.
At AWS, security is job zero and we have architected our infrastructure for the most data-sensitive organizations in the world. In this session, we will cover our Shared Responsibility Model in relation to Security and our Compliance Program, and what that means for our customers when using our suite of storage services.
Discover what the PROTECTED certification means for your organisation and how the status can help you build applications on Amazon Web Services (AWS) that meet the Australian government’s security requirements for highly sensitive workloads.
by Bill Reid, Sr. Manager of Solutions Architecture, AWS
This session is designed to introduce you to fundamental cloud computing and AWS security concepts that will help you prepare for the Security Week sessions, demos, and labs.
Similar to Humans and Data Don't Mix- Best Practices to Secure Your Cloud (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.
25. Automate Answering the Tough Questions
• What data do I have in the cloud?
• Where is it located?
• Where does my sensitive data exist?
• What’s sensitive about the data?
• What PII/PHI is possibly exposed?
• How is data being shared and stored?
• How and where is my data accessed?
• How can I classify data in near-real time?
• How do I build workflow remediation for my security and compliance
needs?
26. AWS CloudTrail
Track user
activity and API
usage
Automation: Log Data Inputs
VPC Flow Logs
IP traffic to/from
network
interfaces in your
VPC
CloudWatch Logs
Monitor apps using
log data, store &
access log files
DNS Logs
Log of DNS
queries in a VPC
when using the
VPC DNS resolver
27. Amazon
GuardDuty
Intelligent threat detection
and continuous monitoring
to protect your AWS
accounts and workloads
Automation: Machine Learning
Amazon Macie
Machine learning-powered
security service to discover,
classify, & protect sensitive
data
32. Automation: Triggers
Amazon CloudWatch
Events
Delivers a near real-time stream
of system events that describe
changes in AWS resources
AWS Config Rules
Continuously tracks your
resource configuration changes
and if they violate any of the
conditions in your rules
33. Automating Remediation
AWS Systems
Manager
Automate patching and
proactively mitigate threats
at the instance level
AWS Lambda
Capture info about the IP
traffic going to and from
network interfaces in your
VPC
34. • Asynchronously
execute commands
• No need to SSH/RDP
• Commands and output
logged
Remediating Threats on Amazon EC2 Instances
Amazon EC2 Systems Manager -
Run Command
EC2 Instances
Lambda
function
AWS Systems
Manager
Amazon
EC2