Segment Case Study

Segment provides a service used by businesses to collect customer data in a single hub for later use in analytics, marketing, and for other purposes. The San Francisco–based firm has a broad customer base, ranging from startups to enterprises, including brand names such as Nokia, Angie’s List, Conde Nast, The Motley Fool, and Salesforce Foundation.

• Company originally ran every application, including API backends, data ingestion, and others, on instances alone.
• Provisioning applications was manually intensive, requiring running startup scripts and manual installs; instances wound up being out of sync because configuration settings were all different.
• Moved to Docker for a better configuration management. Applications can be defined with Docker Compose for consistency and remain stateless.
• Wanted to move their new Docker-based architecture into production, but needed a way to manage and schedule containers at scale.
• Evaluated many open source options, but had been using other AWS products, and wanted a solution that was simple and would integrate with the AWS ecosystem.
  

• Started using Amazon EC2 Container Service (Amazon ECS) as a way to offload cluster management and container orchestration to a service.
• Different services such as API, CDN, and App are deployed on different Amazon ECS clusters. Each service is defined by a task definition indicating which version of the container to run, which cluster to choose, and how many containers should be deployed.
• Uses Elastic Load Balancing and Amazon Route 53 for service discovery. Each service registers to an ELB and Amazon Route 53 points a local entry at each ELB. Services can communicate with each other through DNS.
• Segment uses Datadog, an AWS Advanced Technology Partner, to provide metrics and visualizations on usage and latency.
  

• Improved availability thanks to multiple Availability Zones
• Easily runs new services
• Minimizes container management