From Gherkin Files to Functional & Performance Tests in Minutes

From Gherkin Files to Functional & Performance Tests in Minutes

Stop rewriting what your QA team already wrote. Cavisson’s intelligent import engine transforms Gherkin feature files into production-ready functional and performance tests — assertions included, zero rework required.

The Problem & The Solution

Every modern QA team maintains a library of Gherkin feature files — carefully crafted BDD scenarios that define precisely how an application should behave. These files represent enormous intellectual investment. Yet when it comes to performance testing, engineering teams typically start from scratch, duplicating intent, duplicating effort, and inevitably introducing drift between functional and performance test coverage.

Cavisson eliminates this duplication entirely. The platform ingests your existing Gherkin .feature files directly and produces test scripts that run as both functional validation suites and high-concurrency performance workloads — from the very same source of truth.

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From PRDs to Performance Tests: How AI Massively Reduces Test Authoring Time

Your requirements documents already contain the blueprint for your load tests. Most teams never unlock it. Here’s how Cavisson’s AI changes that equation.

70%

reduction in test authoring time

3×

faster test coverage across services

90%

of PRD perf criteria captured automatically

Here’s a scenario most performance engineers know intimately: you’re handed a 60-page PRD the week before a major release. Somewhere on page 34, buried between UI mockups and data schema definitions, there’s a line that reads: “The checkout flow shall support 500 concurrent transactions at peak load, with API response times not exceeding 800ms at the 99th percentile.”
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Test Automation with Cavisson

How Cavisson automatically generates test scripts from your backlogs and documents, executes them through your CI pipeline, and feeds failures straight back into your issue tracker — with zero manual handoffs.

Step 1: Generate Test Scripts from Your Existing Sources

Performance testing has always started with a blank script. A ticket gets written. An engineer reads it. Then someone manually translates that intent into HTTP calls, load profiles, and assertions — a process that takes hours and drifts out of date the moment the story is updated. Cavisson’s Generate With AI feature eliminates that translation step entirely. It connects directly to the four places where your team’s requirements already live:
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From One Script to Full Lifecycle Validation: Functional, Performance & Chaos

Functional, Performance & Chaos — All in One Platform

Every engineering team has been there. You have a test script — maybe a Selenium flow, a JMeter plan, or a Postman collection — that validated a critical user journey. It passed. You shipped. Then production fell over under load, or a single node failure cascaded into a 3-hour outage. Sound familiar? The root cause isn’t bad tests. It’s incomplete coverage across the application lifecycle. Most teams test in silos: QA owns functional, a performance team runs load tests on a Friday, and chaos engineering is something you “plan to do someday.” The result? Coverage gaps between each stage that only reveal themselves in production — at the worst possible time. At Cavisson, we built our platform around a single belief: your test script should be the seed of full lifecycle validation — not just a checkbox for one phase. With Performance Testing Tool and Chaos Engineering Tool working as a unified engine, that belief is now a reality.

The Three Phases Every Application Must Survive

Before we talk platform, let’s frame the problem precisely. Modern applications must be validated across three distinct — but deeply connected — dimensions:
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Shift-Left Performance Testing: Reusing Functional Test Scripts for Load Testing

The promise of shift-left performance testing is straightforward: catch performance problems earlier, when they are cheaper and faster to fix. But the practical barrier has always been the same — performance testing requires a separate script, a separate tool, and a separate team. By the time load tests are written and run, the development window has already closed. What if the functional test your QA engineer wrote on Monday could also run as a load test by Friday — without anyone touching it? What if the script that validates a single checkout transaction could, with zero modification, simulate ten thousand concurrent shoppers under peak load conditions?
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Why Your Functional and Performance Tests Shouldn’t Live in Separate Worlds

In most organizations today, functional testing and performance testing exist as parallel universes. Different teams, different tools, different scripts, different schedules. Your QA team builds a comprehensive Selenium suite to validate user journeys, while your performance team recreates those same scenarios from scratch in LoadRunner or JMeter. Sound familiar?
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From Monitoring to Observability: What Modern Enterprises Really Need in 2026

The questions enterprises ask about their systems have fundamentally changed. In 2020, teams asked: “Is my system up?” In 2026, they’re asking: “Why is the user experience degrading? Where exactly is the problem? How fast can we fix it?” This evolution from traditional monitoring to full-scale observability isn’t just a technical upgrade—it’s a survival strategy. Cloud-native architectures, microservices proliferation, AI-driven applications, and unforgiving user expectations have made the old playbook obsolete. At Cavisson Systems, we witness this transformation daily as enterprises abandon siloed metrics for unified visibility across applications, infrastructure, logs, and real user experiences.
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AI-Powered Test Data Generation in Cavisson: Transforming the Way Teams Prepare for Testing

AI-Powered Test Data Generation in Cavisson: Transforming the Way Teams Prepare for Testing

In modern software delivery, the need for realistic and dependable test data has become central to both functional and performance engineering. Whether organizations are validating an online retail flow, executing a financial transaction simulation, or running large-scale insurance scenarios, their test results are only as accurate as the data that powers them. Unfortunately, traditional approaches to test data—manual spreadsheets, static datasets, or partial clones of production—often lead to inconsistency, privacy concerns, and unreliable outcomes. 
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WELLS FARGO REDUCES MTTR, OPTIMIZES INFRASTRUCTURE COST & DELIVERS SCALABLE APPLICATIONS USING NETDIAGNOSTICS

CHALLENGE

Down fall in distribution caused by application break down. Dealers and distributors were in trouble and not been able to deliver on time for certain application failures. The application collapsed due to massive data process operations. This caused high response that resulted into the failure of back-end application to serve users with 4XX errors. The bigger challenge was understanding what’s happening in production environment in real time during the peak hours. They tried to leverage production logs to diagnose the issue issues but couldn’t find root cause that lead to the application break down during the peak traffic hours every time.

END-TO-END MONITORING AND DIAGNOSTICS

Cavisson enables Wells Fargo to monitor performance across entire enterprise end-to-end. Starting from the user experience, application back-end, DB, Integration points, Application logs as well. Monitoring the complex infrastructure and to do the RCA uponanyissues.

"To ensure their fraud management application system is able to accommodate high volume transaction, banks need to have a proper test and implementation strategy and supporting tools to ensure they are able to cater to millions of transactions every day. Thankfully with Cavisson we do not have to look around anywhere. Their consultants know their job and their technology is way more efficient and superior."
Piyush Thakkar, VP

ABOUT WELLS FARGO

Industry: Banking

Location: United States

Challenge: Legacy System unable to identify issues with online transactions resulting in excessively high MTTR.

Product Used: NetDiagnostics

Result(s): NetDiagnostics’ Database Monitoring used to identify & optimize culprit SQL queries. End to end visibility by detecting multiple unknown issues in bank’s fraud management system.

SOLUTION

Using NetDiagnostics, Wells Fargo was able to uncover production issues that had resulted in security issues with the application ecosystem. Highlights of NetDiagnostics’ implementation:

❖ Analysis carried out by using NetDiagnostics’s powerful drilldown capabilities were instrumental in identifying a large concurrency issue caused by arrival rate and thereby increasing the response time.

❖ The underlying SQL query, the original culprit, was zeroed in on and optimized thereby limiting any further damage to the customer experience.

❖ Predictive alerts were setup to automatically identify anomalies based on trends & patterns. These alerts were instrumental in ensuring that the issue was proactively handled.

❖ Method Summary & Method Timing Reports used to identify time consuming method calls and their dependencies.

❖ Thread and Heap Dump Analysers utilized to pinpoint contentious threads and memory leak issues, leading to better performance and reduced resource utilization.

BENEFITS

NetDiagnostic’s implementation resulted in major optimization(s) across Wells Fargo’s application ecosystem, not only in terms of the product’s ability to detect issues and ensure compliance but also in reducing resource utilization when compared with the legacy tool. Some of the benefits derived post deployment were as follows:

❖ MTTR & MTTD, the two all-important metrics in terms of handling issues were reduced on the back of early identification in test environment.

❖ Resource utilization witnessed a drastic reduction with more than 80% decrease in infrastructure costs.

❖ Application blind spots eliminated by identifying issues integration callouts. with multiple

❖ Ensured compliance with stringent regulatory measures by identifying issues proactively.

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National Health Authority is the successor of National Agency, Turns to Cavisson performance monitoring For fast problem remediation

CHALLENGE

The National Health Agency (NHA) under Ministry of Health and Family Welfare has launched pilot for Beneficiary Identification System (BIS), which is a process whereby the identification criteria (as per AB-NHPM guidelines) will be applied on SECC and RSBY database to confirm application from ‘entitles’ beneficiaries. Ayushman Bharat will target about 10.74 crore poor, deprived rural families and identified occupational category of urban workers’ families as per the latest Socio-Economic Caste Census (SECC) data Yet, as NHA introduced new online BIS services, for 10.74 crore people, The IT team found itself in need to monitor multiple systems to ensure the smooth running of the company’s operations. It was nearly impossible to follow Business Transactions end-to-end through a complex environment of Windows, Linux, MS SQL, MySQL, and Oracle technologies.

“We were unable to find out the RCA for the issues, suddenly the application gets crashed and we were not being alerted to problems “

ABOUT COMPANY

Industry: Healthcare Location: India Challenge: Too much memory consumed by Cache degrades overall server performance, which need to be optimized for better server performance. Product Used: NetDiagnostics Result(s): 1)DB queries which are taking higher executing time now can be tuned. 2)Faster identification and resolution of very slow transactions.
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