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The AWS Online Tech Talks is a selection of live online presentations that cover a broad range of topics at varying technical levels. These tech talks feature technical sessions led by AWS solutions architects and engineers, live demonstrations, customer examples and Q&A with AWS experts.

The sessions below are categorized. You can click on the "learn more" drop down arrow to view the detailed description of each session.

Presenter:

David Pearson, Technical Business Development Mgr, AWS

Time: June 5, 2017 l 9:00 - 9:40 AM Pacific Time

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Amazon Lex is a service for building conversational interfaces into any application using voice and text. Amazon Lex is now generally available, making it easy for developers to access the same deep learning technologies that power Amazon Alexa. In this tech talk, we will introduce Lex and walk through use cases for retail, travel and hospitality, and internal help desks, where Amazon Lex's automation engine creates the potential to reduce costs, improve service quality, and create new ways to access corporate information.

Learning Objectives:
  • Learn about applying conversational interfaces in applications through Amazon Lex
  • Learn about popular use cases for Amazon Lex
  • Learn how specific AWS customers have implemented Amazon Lex in different workflows

Who Should Attend:

  • Technical Decision Makers, Solution Architects, Business Development Managers, Developers

Presenter:

Rafal Kuklinski, Senior Manager, Amazon Polly

Time: June 8, 2017 l 9:00 - 9:40 AM Pacific Time

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Amazon Polly is a service that turns text into lifelike speech, making it easy to develop applications that use high-quality speech to increase engagement and accessibility. In this tech talk, we will introduce Amazon Polly and walk through popular use cases in specific industries where Amazon Polly's natural sounding voices improve user experience and enables new ways to consume content: Education, Gaming, Content Creation and Telephony.

Learning Objectives:
  • Learn about applying conversational interfaces in applications through Amazon Polly
  • Learn about popular use cases for Amazon Polly
  • Learn how specific AWS customers have implemented Amazon Polly in different workflows

Who Should Attend:

  • Technical Decision Makers, IT Managers, Software Developers, Database Administrators, Data Analysts

Presenter:

Ranju Das, Director, Software Development, Rekognition

Time: June 8, 2017 l 10:30 - 11:10 AM Pacific Time

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Amazon Rekognition is a service that makes it easy to add image analysis to your applications.You can detect objects, scenes, faces; search and compare faces; and identify inappropriate content in images, In this tech talk, we will introduce Amazon Rekognition and walk through use cases for media and entertainment, hospitality and public safety, where Amazon Rekognition’s computer vision capabilities create the potential to streamline existing workflows to reduce time to production subsequently reduce costs and improve service quality and delivery for customers and citizens.

Learning Objectives:
  • Learn about using image analysis with Amazon Rekognition
  • Learn about popular use cases for Amazon Rekognition
  • Learn how specific AWS customers have implemented Amazon Rekognition in different workflows

Who Should Attend:

  • Technical Decision Makers, Solution Architects, Business Development Managers, Developers

Presenter:

Kumar Venkateswar, Sr. Product Manager

Time: June 12, 2017 l 9:00 - 9:40 AM Pacific Time

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Machine learning has been used to provide more accurate predictions than hardcoded business logic using available data. For our customers, Amazon Machine Learning is being used from helping restaurant owners, as with Upserve, to determine the right staffing level on a night; to providing more accurate cost estimates in the insurance industry, as with BuildFax. In this tech talk, we'll cover the basics of how to get started with Amazon Machine Learning, and go through an example of how to perform real-time classification of log data using Amazon Machine Learning.

Learning Objectives:
  • Learn how to integrate Amazon Machine Learning with applications
  • Learn how to train a model using Amazon Machine Learning
  • Learn how to process semi-structured log data in real-time with Amazon Machine Learning

Who Should Attend:

  • Technical Decision Makers, IT Developers, Software Developers, Engineers

Presenter:

Dan Mbanga, Business Development Manager, AWS

Time: June 19, 2017 l 9:00 - 9:40 AM Pacific Time

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Deep Learning (DL) is a subset of Machine Learning (ML) that extends the concept of Artificial Neural Networks (ANN) to uncover hidden patterns in unstructured datasets. Due to the current ubiquity of data (Big Data), and availability of on-demand, inexpensive, and parallel hardware such as Graphics Processing Units (GPUs) on Amazon EC2, Deep Learning has revitalized the excitement in Artificial Intelligence. Breakthrough results can be seen in industry applications such, computer vision, robotics, healthcare, security, retail, and more. Apache MXNet is a fully-featured, flexibly-programmable and ultra-scalable deep learning framework supporting state-of-the-art deep models including convolutional neural networks (CNNs), and long short-term memory networks (LSTMs). MXNet enables Data Scientists familiar with the R programing language to train and deploy deep models at scale, using their favorite language, with the same fast performance observed by Python, Scala or C++ ML practitioners.

You will also hear from Jared P. Lander, adjunct professor of statistics at Columbia University and the organizer of the New York Open Statistical Programming Meetup—the world’s largest R meetup—and the New York R Conference.

Participants will learn how to spin up a pre-built, GPU enabled Data Science environment using the AWS Deep Learning Amazon Machine Image (AMI), in few minutes. We will write a deep learning program with MXNet in a few lines of codes using the R programming language. We will discuss training deep learning models on one or multiple GPUs via R. Finally, we will compare deep models to some traditional Machine Learning models such as Support Vector Machines or Random Forest.

Learning Objectives:
  • Deploy a Data science environment in minutes with the AWS Deep Learning AMI
  • Getting started with Apache MXNet on R
  • Train and deploy Deep Learning models at scale with R

Who Should Attend:

  • Data Scientists practitioners, R programmers, Machine Learning practitioners, Deep Learning practitioners, Data Science students, Managers and Executives interested in deploying deep learning environments, anyone in a related field willing to know more about deep learning.

Presenter:

Asif Khan, Solutions Architect, AWS

Time: June 20, 2017 l 10:30 - 11:10 AM Pacific Time

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AWS offers a family of intelligent services that provide cloud-native machine learning and deep learning technologies to address your different use cases and needs. For developers looking to add managed AI services to their applications, AWS brings natural language understanding (NLU) and automatic speech recognition (ASR) with Amazon Lex, visual search and image recognition with Amazon Rekognition, text-to-speech (TTS) with Amazon Polly, and developer-focused machine learning with Amazon Machine Learning. For more in-depth deep learning applications, the AWS Deep Learning AMI lets you run deep learning in the cloud, at any scale. Launch instances of the AMI, pre-installed with open source deep learning engines (Apache MXNet, TensorFlow, Caffe, Theano, Torch and Keras), to train sophisticated, custom AI models, experiment with new algorithms, and learn new deep learning skills and techniques; all backed by auto-scaling clusters of GPU-based instances. Whether you’re just getting started with AI or you’re a deep learning expert, this session will provide a meaningful overview of how to improve scale and efficiency with the AWS Cloud.

Learning Objectives:
  • Learn about the breadth of AI services available on the AWS Cloud
  • Gain insight into Amazon Lex, Amazon Polly, and Amazon Rekognition
  • Learn more about why Apache MXNet is the deep learning framework of choice for AWS

Who Should Attend:

  • Data Scientists practitioners, Machine Learning practitioners, Deep Learning practitioners, Data Science students, Managers and Executives interested in deploying deep learning environments, anyone in a related field willing to know more about deep learning.

Presenter:

Tony Nguyen, Senior Consultant, AWS

Time: June 1, 2017 l 10:30 - 11:30 AM Pacific Time

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Businesses are migrating their analytics, data processing (ETL), and data science workloads running on Apache Hadoop, Spark, and data warehouse appliances from on-premise deployments to Amazon EMR in order to save costs, increase availability, and improve performance. Amazon EMR is a managed service that lets you process and analyze extremely large data sets using the latest versions of over 15 open-source frameworks in the Apache Hadoop and Spark ecosystems. This tech talk will focus on identifying the components and workflows in your current environment and providing the best practices to migrate these workloads to Amazon EMR. We will explain how to move from HDFS to Amazon S3 as a durable storage layer, and how to lower costs with Amazon EC2 Spot instances and Auto Scaling. Additionally, we will go over common security recommendations and tuning tips to accelerate the time to production.
 
Learning Objectives:
  • Identify best practices to migrate from on-premise deployments to Amazon EMR
  • Understand how to move data from HDFS to Amazon S3
  • Use Amazon EC2 Spot instances to save costs

Who Should Attend:

  • Hadoop Developers, Data Scientists, Database Administrators, IT Decision Makers

Presenter:

Vidhya Srinivasan, GM Amazon Redshift

Time: June 7, 2017 l 10:30 - 11:10 AM Pacific Time

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Amazon Redshift Spectrum is a new feature that extends Amazon Redshift’s analytics capabilities beyond the data stored in your data warehouse to also query your data in Amazon S3. You can use Amazon Redshift and your existing business intelligence tools to run SQL queries against exabytes of data.
 
In this session, we will show you how you can easily start querying your data stored in Amazon S3 with Redshift Spectrum. You can run Amazon Redshift queries on Amazon S3 data on its own, or you can run queries that join together data in S3 with data already in your Redshift data warehouse. We will highlight technical details of query execution and implementation of Redshift Spectrum. We will talk about supported queries, data formats, and strategies to save cost by compressing or transforming your data into a columnar format.
 
Learning Objectives:
  • Learn about Redshift Spectrum, a new feature that allows you to run Redshift queries directly against your data in Amazon S3
  • Understand common use cases for Redshift Spectrum
  • Identify strategies for improving performance and saving costs when querying your data in Amazon S3

Who Should Attend:

  • Database & data warehouse administrators, data scientists, data analysts, IT decision makers

Presenter:

Ryan Nienhuis, Senior Product Manager, AWS

Time: June 13, 2017 l 12:00 - 12:40 PM Pacific Time

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Log analytics is a common big data use case that allows you to analyze log data from websites, mobile devices, servers, sensors, and more for a wide variety of applications such as digital marketing, application monitoring, fraud detection, ad tech, gaming, and IoT. Moving your log analytics to real time can speed up your time to information allowing you to get insights in seconds or minutes instead of hours or days. In this session, you will learn how to ingest and deliver logs with no infrastructure using Amazon Kinesis Firehose. We will show how Amazon Kinesis Analytics can be used to process log data in real time to build responsive analytics. Finally, we will show how to use Amazon Elasticsearch Service to interactively query and visualize your log data.
 
Learning Objectives:
  • Understand how to easily build an end to end, real time log analytics solution
  • Get an overview of collecting and processing data in real-time using Amazon Kinesis
  • Learn how to Interactively query and visualize your log data using Amazon Elasticsearch Service

Who Should Attend:

  • Big data developers, data engineers, data analysts, data engineers, technical decision makers

Presenter:

Allan MacInnis, Senior Solutions Architect

Time: June 15, 2017 l 12:00 - 12:40 PM Pacific Time

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Building data processing applications is challenging and time-consuming, and often requires specialized expertise to deploy and operate. With serverless computing, you can perform real-time stream processing of multiple data types without needing to spin up servers or install software, allowing you to deploy big data applications quickly and more easily. Come learn how you can use AWS Lambda with Amazon Kinesis to analyze streaming data in real-time and then store the results in a managed NoSQL database such as Amazon DynamoDB. You’ll learn tips and tricks for doing in-line processing, data manipulation, and even distributed MapReduce on large data sets.

Learning Objectives:
  • Use cases and best practices for serverless big data applications
  • Leverage AWS technologies such as AWS Lambda and Amazon Kinesis
  • Learn to perform ETL, event processing, ad-hoc analysis, real-time processing, and MapReduce with serverless

Who Should Attend:

  • Developers, Software Development Engineers, Architects, Data Analysts, Data Scientists, IT Decision Makers

Presenter:

David Pellerin, Business Development Manager, AWS

Time: May 30, 2017 l 10:30 - 11:30 AM Pacific Time

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Amazon EC2 Elastic GPUs allow you to easily attach low-cost graphics acceleration to current generation EC2 instances. With Elastic GPUs, you choose the GPU resources that are sized for your workload, so you can accelerate the graphics performance of your applications for a fraction of the cost of stand-alone graphics instances. In this tech talk, we will provide a deep dive on the capabilities of Elastic GPUs and its use case.
 
Learning Objectives:
  • Get an overview of Elastic GPUs
  • Dive deep on the technical capabilities of Elastic GPUs
  • Learn best practices when using Elastic GPUs

Who Should Attend:

  • IT Administrators, 3D Application ISVs, Users interested in running 3D applications in the cloud

Presenter:

Julien Lepine, Sr. Solutions Architect, AWS

Time: June 13, 2017 l 9:00 - 9:40 AM Pacific Time

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Enterprise developers are pushing hard to adopt devops methodologies, but want to keep using the familiar IDE they know and love. AWS makes this a reality with deeply integrated services for .NET like AWS Opsworks, AWS Elastic Beanstalk, and AWS Lambda.  In this session you will discover how to integrate the AWS tools for developers in your development process. We will demonstrate hands-on how to leverage the AWS services, .NET SDK and Visual Studio toolkits to simplify and streamline your development processes.
 
Learning Objectives:
  • Learn how to leverage AWS services to rapidly build and deploy .NET code
  • Learn best practices for developing .NET applications on AWS
  • Learn how to take advantage of the latest innovations such as support of .NET Core on AWS Lambda

Who Should Attend:

  • IT Developers, Software Developers, Engineers

Presenter:

Asif Khan, Solutions Architect, AWS

Time: June 14, 2017 l 9:00 - 9:40 AM Pacific Time

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Batch processing is useful when you need to periodically analyze large amounts of data, but configuring and scaling a cluster of virtual machines to process complex batch jobs can be difficult. Containers provide a great solution for running batch jobs by providing easily managed, scalable, and portable code environments.
 
In this tech talk, we’ll show you how to use containers on AWS for batch processing jobs that can scale quickly and cost-effectively. We’ll discuss AWS Batch, our fully managed batch-processing service, and show you how to architect your own batch processing service using the Amazon EC2 Container Service. We’ll also discuss best practices for ensuring efficient and opportunistic scheduling, fine-grained monitoring, compute resource auto-scaling, and security for your batch jobs.
 
Learning Objectives:
  • Learn about the options for running batch workloads on AWS
  • Learn how to architect a containerized batch processing service on Amazon ECS
  • Learn best practices for optimizing and scaling complex batch workload requirements

Who Should Attend:

  • Software Developers, DevOps

Presenter:

Joseph Idziorek, Sr. Product Manager, Amazon DynamoDB

Time: May 30, 2017 l 9:00 - 10:00 AM Pacific Time

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Developers who build applications for ad tech, finance, gaming, IoT, and other performance sensitive use cases require response times in the range of 1-2 milliseconds. They are also constantly pushing to further reduce this latency to achieve a competitive advantage. Amazon DynamoDB Accelerator (DAX) is a fully-managed, highly-available, in-memory cache for DynamoDB that delivers up to a 10x performance improvement – from milliseconds to microseconds – even at millions of requests per second. In this tech talk, we go over best practices for multiple use cases, including gaming, Ad Tech, IoT, and we’ll explore new features to help you get the most out of your DynamoDB database, including DynamoDB Accelerator (DAX), TTL, Tagging, VPC Endpoints for DynamoDB. Learn how customers have successfully used these features to deploy their applications.

Learning Objectives:
  • Learn about the benefits and features to help you get the most out of your DynamoDB database
  • Learn how customers have successfully used these features to deploy their applications

Who Should Attend:

  • Developers, Database Administrators, and Business Leaders considering in-memory acceleration solutions for new or existing applications

Presenter:

Ed Murray, Software Development Manager, AWS

Time: May 31, 2017 l 12:00 - 1:00 PM Pacific Time

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Moving or replicating your databases to the cloud should be simple and inexpensive. AWS has recently enhanced the AWS Database Migration Service and the AWS Schema Conversion Tool with new data sources to increase your migration options. You can now export from MongoDB databases and Greenplum, IBM Netezza, HPE Vertica, Teradata, Oracle DW and Microsoft SQL Server data warehouses to AWS. Learn how to export and migrate your data and procedural code with minimal downtime to the cloud database of your choice, including cloud-native offerings such as Amazon Aurora, Amazon DynamoDB and Amazon Redshift.

Learning Objectives:
  • Understand the use cases for migrating or replicating databases to the cloud
  • Learn about the benefits of cloud-native databases for performance and costs reduction
  • See how AWS Database Migration Service helps with your migration
  • See how AWS Schema Conversion Tool makes conversions simple and quick

Who Should Attend:

  • Technical Decision Makers, IT Managers, Software Developers, Database Administrators, Data Analysts

Presenter:

Henry Hahn, Senior Product Manager, Amazon Web Services

Stephen Henderson, Developer Advocate, Atlassian

Time: June 7, 2017 l 12:00 - 12:40 PM Pacific Time

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Software release cycles are now measured in days instead of months. Cutting edge companies are continuously delivering high-quality software at a fast pace. In this tech talk, we’d like to introduce a major new addition to our Developer Tools suite, AWS CodeStar, which enables you to quickly develop, build, and deploy applications on AWS. We will provide a hands-on demonstration of how you can use AWS CodeStar to set up an end-to-end software development and continuous delivery toolchain within minutes. We will also share Amazon’s best practices for DevOps and how you can accelerate your software development agility. Additionally, we will have experts from Atlassian, who will showcase how AWS CodeStar integrates with Atlassian JIRA and provides a unified experience to track and manage your JIRA issues within CodeStar dashboard.

Learning Objectives:
  • Learn how to automatically configure and end-to-end Continuous delivery toolchain in minutes
  • Learn how to accelerate your application release process by adopting agile software development tools from AWS
  • Learn how to better manage and track JIRA issues for AWS applications

Who Should Attend:

  • Developers

Presenter:

Nirav Kothari, Principal Consultant, AWS

Time: May 31, 2017 l 10:30 - 11:30 AM Pacific Time

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Many businesses have a large portfolio of existing applications running on-premises today and are interested in moving those workloads to AWS in order to achieve cost savings and enable business agility. Planning a large-scale migration to the cloud takes time and effort, as well as expertise and tools to ensure success along the way. AWS has developed a framework to help customers plan and execute large-scale migration programs, consisting of a comprehensive methodology, a set of tools, and partners with deep subject expertise. In this tech talk, you will learn about foundational milestones to achieve in your migration journey, how to analyze your application portfolio, plan and execute your migration project, and enable your organization to operate on the cloud. This framework leverages our experiences and best practices in assisting organization around the world with their migration programs.

Learning Objectives:
  • Understand what encompasses a large-scale migration and the key business drivers for this change
  • Learn the stages of adopting the AWS Cloud and key activities to complete before considering a large-scale migration
  • Learn how to analyze your application portfolio and classify it against common migration patterns
  • Discover the tools and techniques to help streamline your migration activities
  • Learn program management and governance techniques to ensure success

Who Should Attend:

  • Technology Leaders, Cloud Architects, Application Owners

Presenter:

Akhtar Hossain, Solutions Architect, AWS
Tom Staab, Partner Solutions Architect, AWS

Time: May 31, 2017 l 8:30 - 10:00 AM Pacific Time

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You can use AWS services like Amazon EC2 and Amazon RDS to quickly build, deploy, scale and manage your SQL Server databases, which helps you build more agile applications. This session will cover best practices for running SQL Server on AWS. We will discuss how to choose between Amazon EC2 and Amazon RDS. The lab portion of this webinar will lead you through the steps to launch and configure your first Microsoft SQL Server instance on Amazon Relational Database Service (RDS) and connect it to Microsoft SQL Server Management Studio.

Join the hands-on-lab webinar and receive access to valuable online training. After the webinar, you can take your learning even further with free access to advanced and expert-level labs.

Learning Objectives:
  • Create an Amazon Relational Database Service (RDS) SQL Server instance
  • Connect to the RDS instance using Microsoft SQL Server Management Studio
  • Import data into the database

Who Should Attend:

  • IT Professionals who want to take advantage of the benefits of cloud computing to run development and test workloads, Microsoft SQL Server databases, web hosting services

Presenter:

Martin Kronberg, Technical Evangelist for Intel’s Developer Relations Division

Time: June 13, 2017 l 10:30 - 11:10 AM Pacific Time

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In this session, you will learn how to create a complete Gateway based IoT framework – from the edge to the cloud and back. By using an IoT Gateway as a central data collection, processing, and communication hub you will be able to create IoT connectivity without having to replace legacy hardware. We will show you how to use an Intel NUC gateway and Arduino 101 sensor hub to gather environmental data and step you through establishing a data pipeline to AWS IoT. We will use AWS Lambda to create a rules engine for your data and then send a control signal back down the Intel Gateway.

Learning Objectives:
  • Gather data locally on a Gateway
  • Establish connection to AWS IoT
  • Pass data from AWS IoT to AWS Lambda for processing. Send a control signal back to the Gateway from AWS IoT

Who Should Attend:

  • Developers, Engineers, IT Professionals, Architects

Presenter:

Sid Gupta, Product Manager, AWS Config

Time: June 6, 2017 l 9:00 - 9:40 AM Pacific Time

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As your cloud operations evolve, complexity of governance, compliance, and risk auditing of your AWS account increases. With AWS Config and AWS CloudTrail you can automate your controls and compliance efforts so that they scale with your cloud footprint. You can discover resources that exist in your account, capture changes in configurations, and create alerts for out-of-compliance events. In this session, we will help you use AWS Config, AWS CloudTrail, and other AWS Management Tools to automate configuration governance so that compliance is embedded in the development process.

Learning Objectives:
  • Reduce the complexity of governance
  • Embed compliance in the development process
  • Learn about AWS Management Tools

Who Should Attend:

  • IT Managers, Developers, Cloud Operations

There are currently no webinars in this track. Please check again later. Thank you!  

Presenter:

Nihar Bihani, Sr Mgr, Product Mgmt - Tech, Amazon CloudFront

Time: May 30, 2017 l 12:00 - 1:00 PM Pacific Time

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In this tech talk, you will learn how you can better defend your websites and cloud infrastructure from cyberattacks using edge services from AWS, such as Amazon CloudFront, AWS Shield and AWS WAF. You will go behind the scenes to see how edge services help mitigate common DDoS attacks, how to use advanced protocols and ciphers, and how to enforce end-to-end HTTPS connections. You will also learn how to use additional features like AWS WAF's IP and bot blocking to implement tailored and advanced protection.

Learning Objectives:
  • Discover how to secure your cloud infrastructure with Amazon CloudFront, AWS Shield and AWS WAF
  • Learn how to offload security heavy-lifting to the AWS Edge
  • Learn about the built-in security in Amazon CloudFront
  • Get tips on how to develop an adaptive security strategy for your cloud

Who Should Attend:

  • Technical Decision Makers, IT Developers, Software Developers, Engineers

There are currently no webinars in this track. Please check again later. Thank you!  

Presenter:

Ron Cully, Sr. Product Manager, AWS Directory Service

Julien Lepine, Principal Solutions Architect, AWS

Time: June 14, 2017 l 12:00 - 12:40 PM Pacific Time

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Managing your AWS Cloud Windows workloads using Microsoft Active Directory doesn’t require complex networking or synching your identity data across multiple systems. AWS Directory Service for Microsoft Active Directory offers you actual Microsoft Active Directory as a managed service. Attend this tech talk to become an expert at managing single sign-on (SSO) and Group Policy objects (GPOs) for your AWS Cloud Windows workloads. You will also see a demonstration on how to configure trusts between your on-premises and AWS Cloud Microsoft Active Directory domains securely.

Learning Objectives:
  • Learn how to setup SSO for your .NET applications, Amazon QuickSight, and AWS Enterprise IT Applications such as Amazon Workspaces.
  • Learn how to manage your AWS Cloud Windows workloads such as Amazon EC2 for Windows Server and Amazon RDS SQL Server using GPOs.
  • Learn how to configure trusts between your on-premises and AWS Cloud Microsoft Active Directory domains securely.

Who Should Attend:

  • Enterprise Architects, IT Administrators, and Windows Administrators

Presenter:

Chris Munns, Senior Developer Advocate, AWS Lambda

Time: June 1, 2017 l 12:00 - 1:00 PM Pacific Time

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When building applications with AWS Lambda, you need a way to easily model and deploy the resources in your serverless application such as Lambda functions, APIs, Amazon DynamoDB tables, and more. The AWS Serverless Application Model (AWS SAM) is an open source specification which defines simplified syntax for expressing serverless resources. In this session, we will teach you the essentials of using AWS SAM to model and deploy serverless applications in a simple and repeatable manner. You will learn best practices for using AWS SAM and how to deploy it using services like AWS CloudFormation and AWS CodePipeline.
 
Learning Objectives:
  • Learn how to build serverless applications in a simple and repeatable manner
  • Understand the fundamentals of the AWS Serverless Application Model
  • Gain best practices for serverless application development

Who Should Attend:

  • Developers, Software Development Engineers, DevOps Engineers, Architects

Presenter:

Edward Naim, Product Head, Amazon Web Services

Time: June 1, 2017 l 9:00 - 10:00 AM Pacific Time

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The vast majority of applications and workloads interact with data storage via a file system interface and require file system semantics. As businesses move to the cloud they require storage resources that integrates with their existing applications and tools. In this technical session, we will explore file storage with Amazon Elastic File System (Amazon EFS) and its targeted use cases. Attendees will learn about the Amazon EFS features and benefits, how to identify applications that are appropriate for use with Amazon EFS, and details about its performance and security models. We will highlight and demonstrate how to deploy Amazon EFS in our most common use cases and will share tips for success throughout.
 
Learning Objectives:
  • Recognize why and when to use Amazon EFS and the economic benefits versus other solutions
  • Understand key technical, performance, and security concepts
  • See Amazon EFS in action with live demo

Who Should Attend:

  • Application owners who operate or build file-based applications, and application developers

Presenter:

Darryl S. Osborne, Storage Specialist SA, AWS

Time: June 7, 2017 l 9:00 - 9:40 AM Pacific Time

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We’ve made it easy to make a simple point in time backup for your Amazon EC2 Instances. In this tech talk, you will learn about how to use Amazon EBS snapshots to back up your Amazon EC2 environment. We will review the basics of how snapshots work as well as how to tag snapshots, track costs, and automate snapshots leveraging AWS Lambda. We will describe best practices and share tips for success throughout.
 
Learning Objectives:
  • Learn how to use snapshots effectively to backup EC2 Instances
  • Learn how to tag snapshots and leverage tagging for tracking costs
  • Learn how to automate snapshot management

Who Should Attend:

  • Technical Decision Makers, IT Developers, Software Developers, Engineers

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