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Logistics Performance Testing

About Client:

With a strong motivated 1300+ team and headquartered in Bangalore, our client is the best option for express logistics, and operates a pan India network covering 230 + locations and over 20,000+ pin codes. Our 13 major depots and 29 transit hubs ensure timely and secure movement of goods. With a vast, well-established network and professional resources, our client offers best in class logistics services to an array of sectors viz. Hi-Tech, Automotive, Engineering, Pharmaceutical, Electronics & Electricals and Lifestyle & Retail.

Client Requirement:

Our client’s logistics services are supported by an application, which required to undergo performance testing for the following business workflows:

  • Lead Creation
  • Rate Card Proposal
  • Agreement Signing
  • Customer Code Creation
  • Pickup Order Creation
  • Pickup Order Assigning to Vendor
  • Shipment Pickup by Vendor
  • Origin Service Centre Booking
  • TC at Origin Service Centre
  • THC at Origin HUB
  • Incoming THC at Destination HUB
  • Incoming TC at Destination SC
  • Shipment Delivery
  • Loading sheet Preparation
    • Billing at HO
    • Validation
    • Submit to Customer
    • Invoice Generation
      • Weekly
      • Fort Nightly
      • Monthly

Solution Offered:

After a thorough understanding and analysis of end-to-end- workflows of the client application, we have designed four cycles of Performance Tests.

First Cycle:

In the first cycle, we have conducted performance tests to baseline the existing performance of the application. Unfortunately, load tests failed at 10 concurrent users with 6.8% error rate, and response time for most of the pages stood at 6.4 seconds.

We have identified that the client has been using a single physical server as both “App Server” and “Database”, and recommended to use two physical servers for each.

Second Cycle:

In the second cycle, our Performance tests have shown 30% improvement in response time compared to baseline. After second cycle of benchmark tests, we have provided page recommendations with query changes and code changes.

Third Cycle:

In the third cycle, our Performance tests have shown 100% improvement in response time compared to baseline.

We have also conducted load tests with incremental concurrent user load, stress tests and soak tests. These load tests with different user load variations have given us understanding of application, app server and database performance.

Overall 200 SQL queries were identified for performance optimization and server configurations were recommended.

Fourth Cycle:

At the end of fourth cycle, our performance and load tests have shown 176% page level performance improvement, and overall 60% performance improvement of the system

Outcome:

  • Page level performance improvement by 176%
  • Database performance improvement by 70.4%
  • 200 SQL queries performance tuned to the execution time less than 3 seconds under peak load
  • Overall system performance improvement by 60%

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