Track: Going Serverless

Location: Ballroom A

Day of week:

The public cloud continues to offer new X’s in their x-as-a-service paradigm forcing us to rethink the way we build applications and the architectures that support them. The revolution is far from over with the latest transformation coming to the area of compute! Under the banner of serverless and with names like Azure functions, GCP Cloud Functions, or AWS Lambdas, this new paradigm advances the public cloud promise to provide undifferentiated heavy-lifting, allowing the developer to manage only his/her applications and some (minimal) configuration. In some respects, these cloud functions are only the latest in a portfolio of services that we have come to love and that the public vendors have been providing all along : e.g. Kinesis/Pub-sub, S3/Cloud Storage, DynamoDB/Cloud BigTable, etc…. Adding serverless compute to these other serverless offerings allows us to innovate faster, recover faster from failures, and reduce our costs. Come to this track to learn how you can leverage the latest advances in the world of Serverless from the companies that build them and build on them!

Track Host: Sid Anand

Hacker at Large, Co-chair @QCon & Data Council, PMC & Committer @ApacheAirflow

Sid Anand recently served as PayPal's Chief Data Engineer, focusing on ways to realize the value of data. Prior to joining PayPal, he held several positions including Agari's Data Architect, a Technical Lead in Search & Data Analytics @ LinkedIn, Netflix’s Cloud Data Architect, Etsy’s VP of Engineering, and several technical roles at eBay. Sid earned his BS and MS degrees in CS from Cornell University, where he focused on Distributed Systems. In his spare time, he is a maintainer/committer on Apache Airflow, a co-chair for QCon, and a frequent speaker at conferences. When not working, Sid enjoys spending time with family and friends.

Serverless IoT @iRobot

iRobot entered the Smart Home market with the launch of our first internet-connected Roomba in 2015. Despite a long history of developing networked robots and selling millions of (unconnected) consumer robots per year, building an elastic, scalable cloud infrastructure for the Internet of Things was outside of our core expertise. Utilizing serverless architecture enabled us to completely bypass that undifferentiated lifting and focus on delivering features.

Ben Kehoe, Cloud Robotics Research Scientist @iRobot

Serverless & GraphQL

Like a good wine and cheese, some technologies are just meant to be paired. Serverless can help you implement and scale new services rapidly. GraphQL can help you present a unified and pleasant experience for users of your services and APIs, while maintaining a complex infrastructure behind the scenes. When pairing Serverless & GraphQL you can implement some unique patterns and architectures for performance, security, and user experience gains.

In this session, we'll dive deep into why, how, and when to pair these two, with takeaways for implementing your first greenfield Serverless GraphQL API or migrating existing APIs.

Jared Short, Director of Innovation @Trek10

Scaling Marketplaces at Thumbtack

As Paul Graham writes, creating marketplaces is incredibly hard, and they take "heroic measures" to get rolling. From humble beginnings, Thumbtack today helps millions of customers complete their projects, generating more than $1B / year in business for our professionals. In this talk, I will share some of our key learnings on our journey to scale: from a PHP/PostgreSQL monolith with a self-managed Hadoop cluster, to Dockerized microservices paired with managed/serverless data infrastructure, and our future with fully-managed systems.

Nate Kupp, Technical Infrastructure Lead @Thumbtack

With Great Scalability Comes Great Responsibility

This is a story of how I took down one of our vendor’s services with an innocent serverless application. I wanted to retrieve data from one of our monitoring platforms to analyze SPS Commerce’s software performance. Initially, I wrote a script to collect the data using python multiprocessing. To gather this data in a more scalable, fast, and efficient way, I decided to pivot to a serverless architecture. Unfortunately, my solution ended up spawning requests faster than the REST API could handle. In this talk, we will cover the contextual pros and cons of a number of architectural patterns given real world scalability constraints; from orchestrating Lambdas with AWS step functions to multiprocessing with S3 triggers to rate limiting with queues like SQS.

Dana Engebretson, Performance Engineer @SPS Commerce

Securing Serverless – By Breaking In

Serverless rocks the security boat. Ad-hoc servers we don’t manage rids us of certain security concerns, while the proliferation of cheap micro services raises others. In this talk, we’ll experience these security concerns live. We’ll break into a vulnerable Serverless application and exploit multiple weaknesses, helping you better understand the mistakes you can make, their implications, and how you can avoid them.

Guy Podjarny, Co-founder @Snyk.io

Going Serverless Open Space

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