Cloud Community Fest. DogRun @ Next Tokyo

A fireside chat event with Googlers who are coming to Next Tokyo. You can ask questions directly to the speakers, and the event will be held in English with Japanese translations.

*Please register at the event from the registration site.

####Event Overview####

• Date: Wednesday, Sep 19, 2018
• Time: 19:15 - 21:30
• Venue: Tokyo Prince Park Tower
• Registration site: https://gcpug-tokyo.connpass.com/event/95560/

####Agenda####

• 19:00 Registration opens
• 19:15 Party/Introduction starts
• 19:45 Party ends/move to each track
• 20:00-21:30 Fireside chat (6 tracks)

####GKE track####
Speakers:

• Yoshi Tamura: GKE Product Manager (PM)
• Dawn Chen: Software Engineer (SWE)
• Ines Envid: PM
• Craig Box: Developer Advocate (DA)

In this year's Google Cloud Next SF, Microservice and Istio are taken up as a big topic and Managed Istio was announced as under development. Dashboard dedicated to Kubernetes was also added to Stackdriver Monitoring, and cooperation with Istio was also announced. The product which got updated most in Google Cloud Next SF was GKE. If you are trying to create an application now, you might wonder what architecture to use, such as how to link between Istio and Google Load Balancer, how to use Identity Aware Proxy properly, how do I use it with Cloud Function? How about Monitoring? There are still many things to find out about GKE.

####Spanner / Datastore / Firestore track####
Speakers:

• Dominic Preuss: PM
• Robert Kubis: DA
• Dan McGrath: PM

Spanner's Tokyo Region was released during last year's Google Cloud Next Tokyo. This year, we will talk about how Spanner should be used when it's already been used. Cloud Datastore will be upgraded to Cloud Firestore Datastore Mode. Topics around DB are inconsequential more than before!

####Serverless (Cloud Functions), Firebase track####
Speakers:

• Mike McDonald: PM
• Bret McGowen: DA
• Brian Dorsey: DA

Python and Go support, and a feature that allows users to deploy a Container Image which can not be bound by Cloud Function runtime was added to Cloud Function. Cloud Function has many Firebase event trigger and is a fully managed service. Users do not need to manage the infrastructure, so it is useful for Android, iOS and Web engineers. When using Kubernetes to build rich infrastructure, simple back-end applications is needed within Google App Engine, Firebase, Cloud Functions and other serverless products. What kind of architecture should be applied in order to run applications without Ops? Let's see the world of Serverless together.

####BigQuery / Dataflow track####
Speakers

• Jordan Tigani: Engineering Director, one of the engineers who created BigQuery
• Felipe Hoffa: DA
• Sergei Sokolenko: PM

BQML was announced in Google Cloud Next SF 18, and it became possible to do machine learning in BigQuery, and BigQuery GIS, a feature that will enable user to handle position information in BigQuery. BigQuery feature is targeted for everyone, its use is expanding exponentially. Dataflow Shuffle Service has been added to Dataflow, and Shuffle's performance has improved. Shuffle is also an important element for BigQuery, and it is used in JOIN, GROUP BY and so on. What kind of idea is behind Shuffle for BigQuery and Dataflow? What is the architecture to perform preprocessing for performing BQML with Dataflow? Let's find out.

####Machine Learning / Auto ML####
Speakers:

• Martin Gorner: DA
• Sudheera Vanguri: PM
• Yu-Han Lim: Developer Program Engineer
• Josh Cogan: SWE

Machine learning became viral a few years ago, but the momentum did not wane and became common. However, it is still not as simple as anyone can use. How should we approaches to democratize data and utilize machine learning? This fireside chat will be for engineers who are suffering from the use of data, trying to figured out how to utilize Auto ML, or trying to lean 101 when starting deep reinforcement learning.