Client:
Global Telecommunications Company
Industry:
Telecommunications
Technology and Platforms:
Akamai CloudTest, OpenText LoadRunner, JMeter, Salesforce Analytics Dashboards, Custom Splunk Dashboards
Our client is one of the largest telecommunications companies in the world. They are a leading provider of mobile, internet and TV services to both businesses and consumers.
Technical Challenge
Our Client was implementing Salesforce to replace the front end of all of their existing customer service agent-facing systems. Salesforce was being integrated to Client’s legacy backend systems via MuleSoft.
Salesforce presents unique challenges for performance testing and has strict rules for performance testing on their platform to prevent impact to other customers.
It was imperative that the integrated Salesforce system perform as well or better than the legacy system under a peak load of 100,000 customer interactions per hour.
Approach & Solution
Forte provided Client with a team of performance testing experts that handled all aspects of ongoing performance testing from requirements through analysis - including overall strategy and approach.
In addition to ongoing performance testing activities, Forte developed innovative solutions to address unique challenges encountered during the project including:
- Integrated performance test that included both Salesforce agent activity as well as Client’s call center IVR system.
- Efficiently handling One Time Passcode functionality under high loads.
- Setup custom Splunk dashboards for trending performance related data across the integrated system as well as within the Salesforce application.
Results & added value
Increased ability to handle peak load conditions
Client was able to roll out Salesforce to their entire customer base with the ability to handle their peak load conditions (100,000 customer interactions per hour) associated with key events like new device launches.
Early identification and correction of design issues
Client identified and corrected design issues that limited scalability early in the implementation when mitigation effort / cost was minimal.
Outcome
- Identify performance issues early in the development process
- Identified design issues at the stage when the impact of changes was minimal
- Ability to handle peak load conditions for 100,000 customer interactions per hour