Michael Pytel ( @mpytel ), co-founder and CTO at Fulfilld, shares stories from the team's wins and losses in building out this intelligent managed warehouse solution.
The recording from this Deep Dive includes:
- (2:20) Introduction to Fulfilld
- (4:10) The team's buildout requirements for a cloud-based application, including language support, responsiveness, and data availability
- (9:15) Fulfilld's Android-based scanner's capabilities and hardware
- (12:25) Creating the digital twin with anchor points
- (14:50) Microservice architecture, service consumption, and service data store
- (19:35) Data store options using BigQuery, Firestore, and CloudSQL
- (23:35) Service runtime and runtime options using Cloud Functions
- (28:55) Example architecture
- (30:25) Challenges in deciding between Google Cloud product options
- (31:40) Road map for the warehouse digital assistant, document scanning, and 3D bin packing algorithm
- (39:00) Open community questions
Community Questions Answered
- What does the road map include for security?
- Did using Cloud Functions help with the system design and partitioning codings tasks by clearly defining functions and requirements?
- Do you give your customers access to their allocated BigQuery instance?
- What type of data goes to Firestore versus CloudSQL?
Other Resources
- Google Cloud Platform Architecture Framework
- Google Cloud Hands-On Labs on Coursera
- Google Cloud Release Notes by Product
