Data on Kubernetes San Francisco #1(in person meetup!)

Hi!
Welcome to our July DOK San Francisco Meetup! Join us in person on 20th July at Accel. In order to comply with Accel's Covid protocol, all attendees will be required to fill out a questionnaire upon arrival.

TALKS

• Life in the Herd: Cloud Native ClickHouse
  Robert Hodges - CEO, Altinity

Of all services, databases are perhaps the most resistant to the cloud native cattle-not-pets model. So what does it really mean to run a large database on Kubernetes? Using ClickHouse as an example, we'll discuss the changes from software packaging to operational management and learn how mission-critical databases find true happiness in a cloud native world.

• Leveraging Running Stateful Workloads on Kubernetes for the Benefit of Developers
  Ramiro Berrelleza - Founder & CEO, Okteto

Kubernetes comes with a lot of useful features like Volumes and StatefulSets, which make running stateful workloads simple. Interestingly, when combined with the right tools, these features can make Kubernetes very valuable for developers wanting to run massive production databases in development! This is exactly what was seen at "Extendi".

The developers at Extendi deal with a large amount of data in their production Kubernetes clusters. But when developing locally, they didn't have an easy way of replicating this data. This replication was needed because it allowed developers to test new features instantaneously without worrying if they would work as expected when pushed to production. But replicating a 100Gb+ production database for development wasn't turning out to be an easy task!

This is where leveraging Kubernetes + remote development environments came to the rescue. Running data on Kubernetes turned out to be way faster than any of the traditional approaches because of Kubernetes' ability to handle stateful workloads exceptionally well. And since Extendi already used Kubernetes in production - the setup process was fairly simple.

This talk will cover practical steps on how leveraging Kubernetes based development environments allowed dev teams at Extendi to run production data on Kubernetes during development using features like Volume Snapshots, having a huge positive impact on developer productivity.

• Running AI/ML Workloads in Kubernetes
  Patrick McFadin - Apache Cassandra and Developer Relations, DataStax

Model generation, feature engineering, and especially model serving can all be done in Kubernetes and works amazing. There are cloud native projects that are even built to do this! Let's talk about what you can do today using projects like Apache Spark, Ray, KServe and Feast. What would a modern A/MLI stack in Kubernetes look like if combined? Deploying your entire application stack into Kubernetes gives you a lot more options and efficiency. Surveys show organizations that make it work are much more agile and move faster. Are you ready?

• Breaking Down Barriers: An Argument for Simplifying Kubernetes DevOps
  Abhi Vaidyanatha - Head of Community, Plural

While Kubernetes is an incredibly powerful tool and carries powerful customizability, it is often difficult to recommend to teams that don’t want to choose between lots of hands-on management or the high-cost of managed services. This is especially true for stateful workloads, and applies to the vast ecosystem of various applications that need to live in harmony on a Kubernetes installation. This leads to a difficult fork in the road for companies looking to adopt it; do they remain stagnant and not adopt powerful new technologies, or do they commit large amount of resources (internal or external) to make it happen?

In this talk, we’ll learn how we got to this state, what we need to do to make Kubernetes more accessible for stateful workloads, and the massive strides we can make in cloud-native adoption.