AWS re:Invent 2017

In some organizations, the theme of “can't we all just get along” accurately describes the relationship between DevOps and network security. DevOps operates at a rapid and dynamic pace, using the cloud to create and deploy. Security teams exercise industry best practices of policy change control to eliminate potential security holes. Inevitably, deployment challenges arise. The ideal solution is one where security becomes part of the DevOps fabric. In this session, Ivan Bojer, automation specialist, and Jaime Franklin, cloud architect, both of Palo Alto Networks, discuss and demonstrate how AWS customers can automate the deployment of the VM-Series next generation firewall to protect DevOps environments on AWS. The topics in this session are based on current customer examples. They include: “touchless” deployment of a fully configured firewall utilizing automation tools, such as AWS CloudFormation templates, Terraform, and Ansible; consuming AWS tags to execute commitless policy updates; using Amazon CloudWatch and Elastic Load Balancing to deliver scalability and resiliency. This session wraps up with a discussion of sample templates and scripts to get started and a video demonstration of a fully automated VM-Series deployment. Session sponsored by Palo Alto Networks

The session will focus on the newly-launched security tool Hammer, which Dow Jones developed after identifying a security vulnerability internally. Users will learn more about Hammer and how it solves certain security configuration issues in the AWS cloud. The team behind the development of Hammer will showcase real-world examples of the tool identifying, analyzing and remediating issues, all as part of Dow Jones' commitment to helping everyone in the community as they make the jump to the cloud.

This presentation will include a deep dive into the code behind multiple security automation and remediation functions. This session will consider potential use cases, as well as feature a demonstration of a proposed script, and then walk through the code set to explain the various challenges and solutions of the intended script. All examples of code will be previously unreleased and will feature integration with services such as Trusted Advisor and Macie. All code will be released as OSS after re:Invent.

Hundreds of microservices, millions of AWS Lambda invocations, and dozens of global regions—the way we design, build, and operate cloud infrastructure and applications is increasingly distributed and composed of ephemeral components. From experience, we know a key to success with these systems is the ability to understand them using data. While there is considerable knowledge around how to use metrics and logs to analyze and troubleshoot traditional applications and infrastructure, emerging technology like serverless functions and orchestrated containers require a new observability approach. This is especially true when trying to understand the relationship between new services, like an IoT or mobile backend, and legacy systems. Session sponsored by New Relic

In this session, attain knowledge about how AWS can help create a differentiated customer experience for your end users and employees, at scale and at the speed of innovation to meet your customer's expectations. Hear from a panel of enterprise IT executives, including Glenn Weinstein, CIO of Appirio, who are innovating and driving real transformations of their business via the AWS Cloud. They are leveraging AWS offerings to build, migrate and run their applications on AWS, including AWS Lex, AWS Lambda, Amazon Kinesis, and Amazon Redshift. Session sponsored by Wipro

In this session, we will discuss how the AWS Serverless Application Repository makes it easy to discover and deploy serverless applications published by fellow developers and companies like Datadog, Here, Splunk, and many others. We will cover how you can use the repository to find applications for a variety of use cases and then deploy them to your AWS account. In addition, we will discuss how you can publish your own applications to the repository. You will also hear from two contributors, Datadog and Here, who will describe their approach to building the serverless applications that they have published to the Serverless Application Repository.

As a fully managed database service, Amazon DynamoDB is a natural fit for serverless architectures. In this session, we dive deep into why and how to use DynamoDB in serverless applications, followed by a real-world use case from CapitalOne. First, we dive into the relevant DynamoDB features, and how you can use it effectively with AWS Lambda in solutions ranging from web applications to real-time data processing. We show how some of the new features in DynamoDB, such as Auto Scaling and Time to Live (TTL), are particularly useful in serverless architectures, and distill the best practices to help you create effective serverless applications. In the second part, we talk about how CapitalOne migrated billions of transactions to a completely serverless architecture and built a scalable, resilient and fast transaction platform by leveraging DynamoDB, AWS Lambda and other services within the serverless ecosystem.

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.

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.

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.