performance testing of blue prism intelligent robotic process preview

Performance Testing of Blue Prism Intelligent Robotic Process Automation for Banking

The client is the biggest bank in Europe, with 98 million individual clients, 2.7 million corporate clients, and 278,000 employees. Although they had been using Blue Prism RPA for a while, they decided to perform the first ever load/performance testing of their software, so it was all new to them. PFLB played the guiding part, making the client aware of all the details of load testing and running the service. After the project, the client’s business indicators increased notably, so they returned to us with another service request.

fis profile banking system load testing

FIS Profile Banking System Load Testing

Our client, a large state-owned bank, pays special attention to the stability of the FIS Profile system which serves more than 65 million customers, 55 million contracts, 9 million loan agreements, and 45 million cards. PFLB conducts banking application testing for each of the system releases. On average, a release contains about ten changes to the functionality of the system, each of which requires detailed elaboration and specific testing.

banking system load testing for payroll card programs

Banking System Load Testing for Payroll Card Programs

Our client is one of the largest commercial banks, with European offices and state participation. The bank had a goal to minimize performance and resiliency risks in IT infrastructure and salary program systems, such as possible disruptions in payroll card services, payroll accounting delays, and system failures during registry processing.
PFLB provided performance testing of payroll systems. The testing challenge was to understand the structure of component interaction given a variety of registry types and a large status model.

how to speed up jmeter part 2 preview 1

How to Speed up JMeter. Part 2

We continue our series of articles about optimizing the popular load testing service JMeter. In the previous article, we highlighted the possibilities of significantly speeding up JMeter by configuring agent monitoring and optimizing components and service settings. In this part of the Apache JMeter load testing tutorial, we…

how to speed up jmeter part 1 preview 1

How to Speed up JMeter. Part 1

Apache JMeter load testing doesn’t need to be advertised; nonetheless, not enough attention is paid to the load script speed. In this article, we take a look at different approaches to writing load scripts in an optimal way that allows saving money on the load testing machines. This…

how granularity influences the load testing results with grafana influxdb preview

How Granularity Influences the Load Testing Results with Grafana+lnfluxDB & LoadRunner Analysis

PFLB has worked with load test analysis and test process consulting for many years. During that time we’ve tried many tools and technologies out. In the article, we are going to explain how different configurations for LoadRunner Analysis and Grafana+lndluxDB influence the results and account for data differences. When the operation intensity is high, around […]

creation of the load testing profile preview

Creation of the Load Testing Profile

A load profile is a set of operations whose intensity is chosen to create a load comparable to the production traffic patterns. Load testing preparation is one of the most important steps in load testing services. An incorrect load profile generates testing results unrelated to the production. We recommend to begin the load testing preparation by […]

demo project on monitoring system preview

Demo Project on Monitoring System

Our client is a big American company, whose core business is in IT management tools. They offer numerous solutions, including monitoring systems, which monitor server storage volumes, disk usage and capacity metrics. The systems track key resources, and forecast when you will run out of capacity. In order to demonstrate the monitor systems’ opportunities, the client needed a test infrastructure to fully and tangibly show the monitoring systems’ potential. To solve this task, the client contacted PFLB.