Data Platform
Vessel Tracking: Automated Shipping Cut-Off Monitor for MSC, Evergreen, COSCO & OOCL, One Dashboard
Logistics software development case study: track ERD and Rail Cut-Off dates across MSC, Evergreen, COSCO, and OOCL in one dashboard, with instant alerts.
Django
PostgreSQL
Python
React
Redux
4
Ocean Carriers Monitored (MSC, Evergreen, COSCO, OOCL)
5 min
OOCL High-Frequency Polling Interval
2
Critical Dates Tracked Per Booking (ERD + Rail Cut-Off)
The Problem
Freight Forwarders Checking Four Carrier Portals a Day Need Automated Logistics Software Development
Logistics software development for ocean freight has to solve two critical dates per booking: the earliest receiving date and the rail cut-off date. These dates change frequently, and missing a change means missed cargo, rerouting costs, and client penalties. Freight forwarders managing dozens of active bookings across four major carriers were logging into four separate portals multiple times a day, copying dates into spreadsheets, and manually comparing to detect changes, with no automated alerting.
Our Solution
Logistics Software Development With a Four-Carrier Scraping Architecture, Change Detection, and Instant Notifications
Vessel Tracking runs as a Django and React platform with four dedicated carrier scrapers, each matched to that carrier's specific access method. One carrier requires authenticated headless browser access via Playwright, navigating a two-stage login form and extracting dates from a data table. Another runs through direct POST requests with session cookies, extracting dates from specific table positions. A third exposes a public REST API requiring no authentication at all. The fourth routes through an internal microservice proxy. The tracking engine marks each booking as in-progress during scraping to prevent duplicate updates, normalises varied carrier date formats, and preserves old values alongside current ones before overwriting, resetting the notification flag on any change.
Architecture
Django 5 + DRF API. JWT authentication. Celery + django-crontab for scheduled carrier scraping (4-hour standard refresh, 5-minute OOCL fast refresh). Playwright + fake-useragent for MSC authenticated headless scraping. BeautifulSoup + lxml for Evergreen HTML parsing. requests for COSCO REST API and OOCL microservice proxy. python-dateutil for carrier date normalisation. PostgreSQL with new_entry concurrency lock. Threading for non-blocking immediate first scrape. React + Reactstrap + Redux + ApexCharts dashboard. react-select + Flatpickr for filtering.
The Result
Logistics Software Development Replaces Four Carrier Portals With One Dashboard, Every Change Caught Automatically
Vessel Tracking eliminated the four-portal manual checking workflow entirely, replacing it with an automated system that notifies freight forwarders the moment any critical date changes across any of the four carriers. The old-date preservation model gave teams instant change context directly in the booking list. The moment a booking is added, an immediate background scrape fires so first data is available seconds after entry. One carrier's 5-minute fast-refresh cycle matched its higher change frequency without wasting resources on slower-moving carriers. Freight forwarders went from multiple daily portal logins per carrier to a single dashboard view. If your freight forwarding or logistics operation needs similar carrier data automation, from portal scraping to real-time change alerts, this is the kind of logistics software development work we take on, and we are happy to talk through your carrier list.
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