• PaaS for back-end components, including external data ingestion APIs, front-end web service APIs, hosting of static front-end application assets, back-end data processing pipeline microservices, APIs to storage infrastructure (Cloud SQL and Memcached), and data processing pipeline task queues and cron jobs. Task queue fan-out and auto-scaling of back-end microservice instances provide parallelism for high velocity data processing.

  • Back-end datastore.

  • Continuous integration and deployment.

  • Source code repository.

  • Issue tracking.

  • Package management and build automation for the back-end, plus integration of front-end build automation using Gulp/Bower/NPM.

  • Back-end application logic.

  • Front-end application logic.

  • Componentize the front-end web client.

  • Bind data models to visual layouts in front-end web client.

  • "Idiot proof MVC" using transactional pub/sub between models, views, and controllers to establish reliable one-way data flow. Combines well with Polymer web components to create a modular, loosely coupled front-end architecture.

  • Remote broker and local client for incoming data feeds. Local broker for republishing data feeds to other systems.

  • Infrastructure for Google App Engine, Google Cloud Endpoints, Memcached, and Google Cloud SQL components, as well as Git repository and Jenkins CI server.

  • Foundation for front-end web client.

  • Distributed cache exposed through Google App Engine APIs; use to stage fresh data (incoming and recently processed) for faster access in data processing pipeline.

  • Configuration for ActiveMQ message broker and Apache Camel routes in data feed ingestion module.

  • Package manager; dependency for Bower and Gulp in build pipeline.

  • Package manager for front-end JavaScript dependencies; part of the overall build pipeline.

  • Build automation for front-end web client.

  • Develop and debug Java code using standard Eclipse distribution. No special plugins; standard Maven and Git integration.