Neoworks
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This document discusses delivery method integration and Shutl, a delivery service built by Neoworks. Shutl offers two delivery options: Shutl Now for rapid delivery within 15 minutes, and Shutl When for delivery within a specified hour. The document provides code examples for integrating Shutl services into a Hybris e-commerce platform and outlines some features and considerations for message caching, file endpoints, database transactions, and ensuring data consistency.
Neoworks
- 1. Delivery Method Integration Conrad Koppitz conrad@neoworks.com
- 2. Vendors share ≒ Similar goods ≒ Similar pricing Differentiators ≒ Customer experience ≒ Delivery Delivery Matters
- 3. ≒ Links stores and couriers ≒ Handles the hard stuff ≒ Courier selection ≒ Price calculation ≒ Lead times ≒ Exposes a simple API Shutl
- 4. ≒ Shutl Now ≒ Rapid delivery, as soon as possible ≒ Can be as fast as 15 minutes ≒ Shutl When ≒ Delivery within a specified hour Shutl services
- 5. ≒ Built by neoworks ≒ Data model and business services ≒ Location service ≒ Delivery service ≒ CS cockpit widget Shutl Hybris Extension
- 6. locs = ls.getNearbyShutlLocations( cart.getDeliverAddress(), 20.0); Quote = ds.getDeliveryQuotation(cart, locs.get(0), cart.getDeliveryAddress(), null); cart.setDeliveryQuotation(quote); conf = ds.bookDelivery(cart); For a demo, go to thetoyshop.com Shutl Now Example
- 7. ≒ Cancel quote ≒ Failure in process after quote was booked ≒ Preview quotes ≒ Rapid, approximate Feature wish list
- 8. ≒ Separate retrieval of data and processing ≒ Retrieved data leaves audit trail ≒ Good for debugging ≒ No need to refetch data if the error was local ≒ Remember to clean up ≒ Some data expires Message Caching
- 9. ≒ Add file end points for inbound data interfaces ≒ Allows for easy production fixes ≒ Remember to track the source of the data ≒ Spring integration is good for this File Endpoints
- 10. ≒ Atomicity, Consistency, Isolation, Durability ≒ Stock example ≒ Stock numbers guaranteed by ACID properties ≒ What happens when some stock is destroyed? ≒ Downside: bottleneck due to locking Database Transactions
- 11. ≒ Stock example ≒ Many people buy the same goods ≒ Web applications are very concurrent ≒ Single SQL statement ≒ UPDATE StockLevel SET qty = 98 WHERE qty = 100 AND sku = 1234 ≒ Retry if no rows updated No transactions?