shift left performance testing

Author

Shivaram

Director - Digital & Cloud Quality Assurance Services


The author is experienced in Application Lifecycle Management (ALM), Performance Engineering & Application Security and has executed high volume load tests using HP LoadRunner, Microsoft Visual Studio & JMeter for various applications across domains.

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When a Global Retail & Entertainment Conglomerate (G-REC) in the Middle East decided to migrate its entire core business from finance to supply chain onto a new SAP S/4HANA omnichannel platform, the risk was exponential.

I was involved in this compelling project where the core challenge was guaranteeing stability for one of the most volatile retail environments in the world.

Surviving the “White Friday” Rush

Our client, a market leader in the UAE and MENA region, was embarking on a major digital transformation. They were consolidating core functions onto SAP S/4HANA, integrated with public-facing e-commerce systems.

The risk wasn’t normal traffic. It was the unpredictable load spikes during regional mega-sales like Ramadan and “White Friday”. Transaction volumes were projected to surge by up to 350% above normal traffic.

A single performance failure, a database deadlock or a slow API, during these periods would result in catastrophic revenue loss and severe reputational damage.

The mandate was clear:

  • Accurately simulate peak-hour transactions across diverse SAP interfaces: Fiori, classic SAP GUI and critical API integrations.
  • Validate system stability by simulating over 40,000 concurrent virtual users.

Here’s What We Did – Shift-Left Performance Engineering with Tricentis NeoLoad

We implemented a “shift-left” performance engineering program. The goal was simple: to proactively identify and resolve performance bottlenecks long before they could hit production.

Here’s how we tackled the challenge:

  1. Massive Scale Simulation: We leveraged Tricentis NeoLoad’s cloud scaling capabilities to simulate 40,000 concurrent virtual users. This load was 2.0x higher than the client’s historical peak, giving them confidence for future growth.
  2. True Omnichannel Emulation: We didn’t just hit the back-end. We used NeoLoad’s specialised support for SAP protocols (Fiori, GUI, RFC/IDoc) alongside its RealBrowser technology to accurately simulate end-to-end customer journeys from “Click & Collect” in the e-commerce platform to in-store transactions.
  3. CI/CD Integration: Performance validation was integrated into the DevOps pipeline, meaning performance metrics were checked automatically with every release, turning QE/QA into a continuous quality gate.

Here’s The Impact

The results validated our strategic approach. We didn’t just confirm the system was fast, we made it faster and more resilient than ever before.

Metric
Outcome
What This Means for the Business
Response Time Improvement 55% reduction Key SAP business processes dropped from over 4.5 seconds to under 2.0 seconds.
Peak Load Validation 200% historical peak Confirmed the system could handle 40,000+ VUs, securing capacity for years to come.
Defect Prevention Zero production issues 19 critical performance bottlenecks (including database deadlocks and slow APIs) were resolved pre-go-live, resulting in zero performance-related issues during the first major holiday period.
Efficiency Gains 65% test maintenance savings NeoLoad’s low-code design made scripts cheaper and faster to maintain.

When migrating to a complex platform like SAP S/4HANA, especially in a high-stakes environment, pre-emptive performance engineering is not an expense; it’s business insurance. It turned a massive risk into a source of confidence and operational excellence for our client.

Is your QE/QA strategy just check boxes, or are you stress-testing for the 350% surge?