Sprint 3 Review

This sprint we did the following:

  • Rebuilt the backend response in different endpoints.
  • Redeployed all the infrastructure, because the services were down.
  • Changed the credentials needed for the Redis.
  • Developed the frontend needed to show in real time the information (bikes available and the ones disabled).
  • Developed a serverless function which retrieves the data on real time and calculates a new output every time we want to consult the web page.

week 6 planning

This week we will do the following:

  • Make a PoC using Random Forest
    • Develop in Python a Markov Chain with the datasets disposed
  • Test backend service
    • Do unit testing
    • Do integration testing
  • Complete the Homepage view (frontend)
    • Only boilerplate
    • UX is the priority
  • Configure CircleCI
    • For automating tests
    • In a short term will help to deploy
  • Configure TCP sockets in backend
    • Impment TCP Connection Address in GO

Week 5 planning

This week we will do the following:

  • Research using Data IQ
    • Analyze the distribution of the data
  • Make a PoC using Random Forest
    • Develop in Python a Markov Chain with the datasets disposed
  • Define endpoints needed for backend
    • Make a PoC for every endpoint using Redis
    • Testcases included
    • Try to do a TDD strategy
  • Complete the Homepage view (frontend)
    • Only boilerplate
    • UX is the priority
  • Configure CircleCI
    • For automating tests
    • In a short term will help to deploy
  • Configure TCP sockets in backend
    • Impment TCP Connection Address in GO

Week 4 plan

This week we are going to do the following

  • Frontend Boilerplate
    • This week we will start doing scaffolding in the homepage, and maybe in one or two more views. (Samuel)
  • Define Backend models/entities
    • There are about 3 to 4 entities, we will define each one with their respective properties this week. (Victor and Estefany)
  • Define Web HTTP frameworks for Go backend service
    • We are considering to use Gorilla, Gin, Revel or whatever framework which fits better for our project. (Julia)
  • Create A Multinomial Logisitic Regression model
    • This will be a rebalanced model, which will be developed together with the team from Bosch. (Victor)
  • Do a presentation of our currently deliverables in Bosch. (Victor)