DoK Talks #70 - YugabyteDB - Distributed SQL Database on Kubernetes // Amey Banarse

Abstract of the talk…

Kubernetes has hit a home run for stateless workloads, but can it do the same for stateful services such as distributed databases? Before we can answer that question, we need to understand the challenges of running stateful workloads on, well anything. In this talk, we will first look at which stateful workloads, specifically databases, are ideal for running inside Kubernetes. Secondly, we will explore the various concerns around running databases in Kubernetes for production environments, such as: - The production-readiness of Kubernetes for stateful workloads in general - The pros and cons of the various deployment architectures - The failure characteristics of a distributed database inside containers In this session, we will demonstrate what Kubernetes brings to the table for stateful workloads and what database servers must provide to fit the Kubernetes model. This talk will also highlight some of the modern databases that take full advantage of Kubernetes and offer a peek into what’s possible if stateful services can meet Kubernetes halfway. We will go into the details of deployment choices, how the different cloud-vendor managed container offerings differ in what they offer, as well as compare performance and failure characteristics of a Kubernetes-based deployment with an equivalent VM-based deployment.

Bio…

Amey is a VP of Data Engineering at Yugabyte with a deep passion for Data Analytics and Cloud-Native technologies. In his current role, he collaborates with Fortune 500 enterprises to architect their business applications with scalable microservices and geo-distributed, fault-tolerant data backend using YugabyteDB. Prior to joining Yugabyte, he spent 5 years at Pivotal as Platform Data Architect and has helped enterprise customers across multiple industry verticals to extend their analytical capabilities using Pivotal & OSS Big Data platforms. He is originally from Mumbai, India, and has a Master's degree in Computer Science from the University of Pennsylvania(UPenn), Philadelphia. Twitter: @ameybanarse LinkedIn: linkedin.com/in/ameybanarse/