Aws Re:invent 2017

In this session, discover how to build a multichannel conversational interface that leverages a preprocessing layer in front of Amazon Lex. This preprocessing layer can enable customers to integrate their conversational interface with external services and use multiple specialized Amazon Lex chatbots as part of an overall solution. As an example of how to integrate with an external service, learn how to integrate with Skype. Watch it in action through a chatbot demonstration with interaction through Skype messaging and voice.

Oracle enterprise applications and middleware such as E-Business Suite, PeopleSoft, Siebel, and WebLogic are central to many IT departments. They often require complex deployments that can greatly benefit from the flexibility, scalability, and security of the cloud. In this session, we discuss architecture patterns and best practices for migrating these applications to and running these applications on AWS. We cover how to work with Oracle enterprise applications and multiple services including Amazon RDS, AWS Database Migration Service, Amazon Elastic File System, and AWS CloudFormation. As part of this, we show examples of successful customer deployments.

Amazon EMR is one of the largest Hadoop operators in the world, enabling customers to run ETL, machine learning, real-time processing, data science, and low-latency SQL at petabyte scale. In this session, we introduce you to Amazon EMR design patterns such as using Amazon S3 instead of HDFS, taking advantage of both long and short-lived clusters, and other Amazon EMR architectural best practices. We talk about lowering cost with Auto Scaling and Spot Instances, and security best practices for encryption and fine-grained access control. Finally, we dive into some of our recent launches to keep you current on our latest features.

In this session, you will learn how to deploy, monitor and manage your serverless APIs in production. We will deep dive into advanced capabilities of API Gateway that enable customers to build large scale data ingesting applications and dynamic websites. We will show you how to set up alarming and analyze logging for Amazon API Gateway and AWS Lambda using AWS CloudWatch, and automate common maintenance and management tasks for your services. In addition, we will review latest features that provide customers more control over their integrations and more insight into API usage.

When you plan your data center migration to the cloud, it's critical to consider how workloads will run to ensure maximum performance and availability. With Microsoft applications making up 60% or more of most on-premises data centers, more and more customers are moving their Microsoft workloads to AWS to improve performance, increase availability, and improve their security posture. In this session, we discuss how customers are accomplishing this task. We cover the common architectural patterns for moving Microsoft applications such as SQL Server, SharePoint, and Dynamics, and we discuss how to integrate with Active Directory for a seamless transition. We also examine tools like AWS Application Discovery and AWS Server Migration Service that can help make your move faster and easier.

Most companies are over-run with data, yet they lack critical insights to make timely and accurate business decisions. They are missing the opportunity to combine large amounts of new, unstructured big data that resides outside their data warehouse with trusted, structured data inside their data warehouse. In this session, we take an in-depth look at how modern data warehousing blends and analyzes all your data, inside and outside your data warehouse without moving the data, to give you deeper insights to run your business. We will cover best practices on how to design optimal schemas, load data efficiently, and optimize your queries to deliver high throughput and performance.  

AWS Step Functions makes it easy to coordinate AWS Lambda functions, run business workflows, and automate operations using state machines. The product has been live in the field for a year now, and it's time to learn from what people are doing with it. In this session, we'll present a series of innovative, high-impact, and just plain crazy applications of state machines from all sorts of customers. Guest-star Coca-Cola will show how they used Step Functions to support vending loyalty programs and product nutrition syndication. Managing application state is a central problem of building the serverless apps of the future; learn how Step Functions does it simply and scalably. Warning: there will be code!

In this session, we explore multi-account considerations for compliance and auditing. We include topics such as API call prefiltering, a repeatable approach to SCP and IAM policy creation, internal separation of duty and need to know, compliance scope ring-fencing, scope of impact limitation, and mandatory access control. We review approaches for log and event analytics and log record lifecycle management (including redaction where necessary) and alerting. We also discuss how you can deploy compliance assessment tools in multi-account environments and how you can interpret these tools' output so it makes sense. Finally, no set of detailed multi-account sessions is complete without discussing tools for visualization.

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 service

Join us to learn what's new in serverless computing and AWS Lambda. Dr. Tim Wagner, General Manager of AWS Lambda and Amazon API Gateway, will share the latest developments in serverless computing and how companies are benefiting from serverless applications. You'll learn about the latest feature releases from AWS Lambda, Amazon API Gateway, and more. You will also hear from FICO about how it is using serverless computing for its predictive analytics and data science platform.

In this session, learn how you can enable governance, compliance, and operational and risk auditing of your AWS account through a combination of continuous monitoring, auditing, and evaluation of your AWS resources. With AWS management tools, you can see a history of AWS API calls for your account, review changes in configurations and relationships among AWS resources, and dive into detailed resource configuration histories. You can determine your overall compliance with the configurations specified in your internal guidelines, and you can give developers and systems administrators a secure and compliant means to create and manage AWS resources.

In this session, we use Apache web logs as example and show you how to build an end-to-end analytics solution. First, we cover how to configure an Amazon ES cluster and ingest data using Amazon Kinesis Firehose. We look at best practices for choosing instance types, storage options, shard counts, and index rotations based on the throughput of incoming data. Then we demonstrate how to set up a Kibana dashboard and build custom dashboard widgets. Finally, we review approaches for generating custom, ad-hoc reports.  

Have a lot of real-time data piling up?  Need to analyze it, transform it, and store it somewhere else real quick?  What if there were an easier way to perform streaming data processing, with less setup, instant scaling, and no servers to provision and manage? With serverless computing, you can build applications to meet your real-time needs for everything from IoT data to operational logs without needing to spin up servers or install software. Come learn how to leverage AWS Lambda with Amazon Kinesis, Kinesis Firehose, and Kinesis Analytics to architect highly scalable, high throughput pipelines that can cover all your real-time processing needs. We will cover different example architectures that handle use cases like in-line process or data manipulation, as well as discuss the advantages of using an AWS managed stream.

Enterprises must transform at the pace of technology. Through chatbots built with Amazon Lex, enterprises are improving business productivity, reducing execution time, and taking advantage of efficiency savings for common operational requests. These include inventory management, human resources requests, self-service analytics, and even the onboarding of new employees.  In this session, learn how Infor integrated Amazon Lex into their standard technology stack, with several use cases based on advisory, assistant, and automation roles deeply rooted in their expanding AI strategy. This strategy powers one of the major functionalities of Infor Coleman to enable their users to make business decisions more quickly.

Learn how to take advantage of AWS for disaster recovery. In this session, we examine how traditional disaster recovery concepts can be adapted to the cloud. We also explore ways to cost-effectively reinvent disaster recovery, so it can extend to applications and workloads that have never had it before. This session walks you through tiered technology approaches to apply as part of a disaster recovery strategy that aligns costs to intended business outcomes.

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.

How do you monitor and troubleshoot an application made up of many ephemeral, stateless functions? How do you debug a distributed application in production? In this talk, we walk you through best practices, tools, and conventions using common troubleshooting scenarios. We'll discuss how you can use AWS services to address these scenarios, such as using Amazon CloudWatch for alarms and using AWS X-Ray to detect cross service calls. You will also learn how Financial Engines leverages AWS X-Ray to debug, monitor, and analyze latency data for its serverless applications. It will also share some best practices for debugging and reporting.

When migrating a large number of workloads to AWS, tracking progress across the various applications and services involved can distract your team from core migration activities.  In this session, learn how AWS Migration Hub provides a single place to discover your existing servers and track the status of each application migration. It provides you with better visibility into your application portfolio and streamlines migration tracking, at no additional cost beyond the services you use.

Companies of all sizes are looking for technology to efficiently leverage data and their existing IT investments to stay competitive and understand where to find new growth. Regardless of where companies are in their data-driven journey, they face greater demands for information by customers, prospects, partners, vendors and employees. All stakeholders inside and outside the organization want information on-demand or in “real time”, available anywhere on any device. They want to use it to optimize business outcomes without having to rely on complex software tools or human gatekeepers to relevant information. Learn how IT innovators at companies such as MasterCard, Jefferson Health, and TELUS are using Domo's Business Cloud to help their organizations more effectively leverage data at scale. Session sponsored by Domo

Building and deploying serverless applications introduces new challenges for developers whose development workflows are optimized for traditional VM-based applications. In this session, we discuss a method for automating the deployment of serverless applications running on AWS Lambda. We first cover how you can model and express serverless applications using the open-source AWS Serverless Application Model (AWS SAM). Then, we discuss how you can use CI/CD tooling from AWS CodePipeline and AWS CodeBuild, and how to bootstrap the entire toolset using AWS CodeStar. We will also cover best practices to embed in your deployment workflow specific to serverless applications. You will also hear from iRobot about its approach to serverless deployment. iRobot will share how it achieves coordinated deployments of microservices, maintains long-lived and/or separately-managed resources (like databases), and red/black deployments.