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Which Engine?

Which Engine?

A quick rundown of which GCP computing option makes the most sense to use for different use cases.

Terrence Ryan

June 23, 2017
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  1. @tpryan Virtual machines Compute Engine • 1 - 64 processors

    • .6 - 416 GB (.9 - 6.5 GB per proc) • Disk limits ◦ 65 TB Persistent ◦ 3 TB SSD ◦ 208 RAM • Preconfigured images ◦ Can build your own • Spin up in 10s of seconds
  2. @tpryan Frontend 10.0.0.1 Public 130.91.x.x1 API 10.0.0.2 Public 130.91.x.x2 Data

    10.0.0.3 Kubernetes • Container Orchestration System • Allows for running a large number of containers in production • Organizing them into workloads ◦ Microservices ◦ Scheduled jobs ◦ Batch jobs
  3. @tpryan Containers Container Engine • Managed Kubernetes (Containers as a

    service) • Smart defaults for ◦ Monitoring ◦ Logging ◦ DNS ◦ Service Discovery • Auto scaling App Engine flexible environment • Custom Runtime ◦ Bring your own Dockerfile • Autoscaling • Given one endpoint per service
  4. @tpryan Containers Container Registry • Container image storage • Works

    with ◦ GKE ◦ App Engine flexible ◦ Docker Container Builder • Container building as service • Integrates with Container Registry • Integrated with build processes
  5. @tpryan Serverless App Engine flexible runtime • Languages ◦ Java

    8 / Servlet 3.1 / Jetty 9 ◦ Python 2.7 & 3.5 ◦ Node.js ◦ Ruby ◦ PHP ◦ Go App Engine standard runtime • Languages ◦ Python 2.7 ◦ Java 7 ◦ PHP 5.5 ◦ Go • Constrained capabilities • Incredibly rapid scale
  6. @tpryan Serverless App Engine flexible runtime • Languages ◦ Java

    8 / Servlet 3.1 / Jetty 9 ◦ Python 2.7 & 3.5 ◦ Node.js ◦ Ruby ◦ PHP ◦ Go App Engine standard runtime • Languages ◦ Python 2.7 ◦ Java 7 ◦ PHP 5.5 ◦ Go • Constrained capabilities • Incredibly rapid scale Cloud functions • Javascript / Node.js • Respond to events
  7. @tpryan Virtual machines Containers Serverless Portability at the cost of

    efficiency Efficiency at the cost of portability Current industry compromise