AWS re:Invent 2019: How Ginkgo Bioworks uses AWS to make organisms (STP201)

Ginkgo Bioworks, an organism company, engineers microbes to produce specialty chemicals, replacing petroleum-based products and addressing environmental and agricultural challenges. Ginkgo's foundries compile and debug DNA code, inserting synthetic DNA into organisms like yeast, tested at increasing scales using robots. This process enables the company to offer services to various industries, such as teaching yeast to make paint, while retaining intellectual property applicable to other projects. Ginkgo leverages its discoveries across diverse applications, including cannabinoids and animal-free protein, and also launches new ventures and incubators like Petri to support young bioscience companies. The company uses AWS to manage its extreme automation and data processing needs, which are growing exponentially.

Outlines

Part 1: Introduction, History, and Mission

Part 2: Business Model and Scaling Laws

Part 3: IT Infrastructure and DevOps Strategy

Part 4: AWS Services and Best Practices

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AWS Events

Part 1: Introduction, History, and Mission

Introduction to Ginkgo Bioworks: Creating Life at Scale with AWS

The History of Computing and the Genesis of Synthetic Biology

Ginkgo Bioworks: Company Overview, Mission, and Synthetic Biology Explained

Part 2: Business Model and Scaling Laws

Ginkgo's Foundry Model: Compiling DNA Code and Business Strategy

Knight's Law: Scaling Genetic Engineering and New Company Incubator Petri

Ginkgo's Scale: Deep Learning Models, Data Storage, and DNA Design

Part 3: IT Infrastructure and DevOps Strategy

IT and DevOps Challenges: Managing Growth and Infrastructure on a Dock

IT and DevOps Team Structure and Extreme Automation

AWS Account Structure, Sequencing, and Data Storage Solutions

Part 4: AWS Services and Best Practices

Favorite AWS Services and the Power of Batch Processing

The Importance of AWS and Customer Service

Best Practices: Multi-Account Strategy, Compliance, and Security

AWS re:Invent 2019: How Ginkgo Bioworks uses AWS to make organisms (STP201)

AWS Events

Part 1: Introduction, History, and Mission

00:00Introduction to Ginkgo Bioworks: Creating Life at Scale with AWS

Introduction to Ginkgo Bioworks: Creating Life at Scale with AWS

00:44The History of Computing and the Genesis of Synthetic Biology

The History of Computing and the Genesis of Synthetic Biology

04:11Ginkgo Bioworks: Company Overview, Mission, and Synthetic Biology Explained

Ginkgo Bioworks: Company Overview, Mission, and Synthetic Biology Explained

Part 2: Business Model and Scaling Laws

07:16Ginkgo's Foundry Model: Compiling DNA Code and Business Strategy

Ginkgo's Foundry Model: Compiling DNA Code and Business Strategy

11:37Knight's Law: Scaling Genetic Engineering and New Company Incubator Petri

Knight's Law: Scaling Genetic Engineering and New Company Incubator Petri

17:20Ginkgo's Scale: Deep Learning Models, Data Storage, and DNA Design

Ginkgo's Scale: Deep Learning Models, Data Storage, and DNA Design

Part 3: IT Infrastructure and DevOps Strategy

22:48IT and DevOps Challenges: Managing Growth and Infrastructure on a Dock

IT and DevOps Challenges: Managing Growth and Infrastructure on a Dock

27:13IT and DevOps Team Structure and Extreme Automation

IT and DevOps Team Structure and Extreme Automation

31:36AWS Account Structure, Sequencing, and Data Storage Solutions

AWS Account Structure, Sequencing, and Data Storage Solutions

Part 4: AWS Services and Best Practices

37:35Favorite AWS Services and the Power of Batch Processing

Favorite AWS Services and the Power of Batch Processing

40:23The Importance of AWS and Customer Service

The Importance of AWS and Customer Service

44:11Best Practices: Multi-Account Strategy, Compliance, and Security

Best Practices: Multi-Account Strategy, Compliance, and Security