Major Insurer Improves Application Quality with Appvance IQ
This large insurer is relying increasingly on an array of
internally developed applications to support their
worldwide growth. Customer expectations for fast quotes
and online self-service capabilities, as well as internal
process improvements, have spurred the growth of their
software portfolio.
Until recently, their development teams have been using a combination of manual and automated testing. To enable automation, teams have largely been using open source tools. As the number of applications has continued to grow, and code re-use and best practices are being deployed globally, the company has begun to run into challenges with the consistency of their testing, the time commitment required to support their array of open source technologies, and their lack of visibility into test results and trends. They determined they needed a different approach.
Until recently, their development teams have been using a combination of manual and automated testing. To enable automation, teams have largely been using open source tools. As the number of applications has continued to grow, and code re-use and best practices are being deployed globally, the company has begun to run into challenges with the consistency of their testing, the time commitment required to support their array of open source technologies, and their lack of visibility into test results and trends. They determined they needed a different approach.
Objectives
The company launched an effort to select an AI-enabled
test automation platform to achieve a series of objectives
centered around their key challenges. Their evaluation
criteria included the following platform requirements:
- Generates scripts quickly
- Provides ease of use
- Requires little maintenance
- Enables functional and API testing
- Integrates with their CI/CD tools
These requirements were specifically designed to address
their pain-points of slow product release cycles and large
numbers of undetected bugs when using manual testing,
and time-consuming test creation and maintenance, lack of
visibility into test results, and difficulty scaling when using
automated testing.
Quick Facts
Industry
Property & Casualty
Insurance
Size
Fortune 100
Geographies
US-based +
> 25 countries
worldwide
Employees
> 25,000
Applications Under Test
> 5,000
The Appvance IQ™ Solution
Appvance IQ (AIQ) was selected because it provided a
comprehensive solution that fulfilled all the insurer’s
requirements as well as providing what they call “bonus
features” — performance and load testing capabilities and
security / application penetration testing functionality.
The company began its implementation with just a small set of applications to prove out the results and build organizational skills gradually. Their first two applications leveraging AIQ had different areas of focus: one was switching from manual testing to automation with autonomous AI-driven testing for a new application launching within six months, while the second was shifting its open source tests to AIQ and increasing coverage by adding new self-healing UI and API tests along with load/performance and security tests. Working with the Appvance customer success team, the company deployed AIQ to their AWS Cloud and integrated with their GIT repositories. Their implementation is scalable, with ondemand test nodes spinning up and down to drive their test scenarios on an as-needed basis.
Test results including snapshots, logs, and error messages are published to an interactive dashboard which provides application health status, easy triage/prioritization of issues, and root cause analysis.
AIQ has enabled consistent automation testing control globally and streamlined the QE/QA process and toolset while enabling the company’s dev teams to focus on new feature releases rather than regression tests. This step forward has led to higher code quality and happier customers. This happy Appvance customer is now rolling out AIQ to additional applications to unlock these benefits across more of their software portfolio.
The company began its implementation with just a small set of applications to prove out the results and build organizational skills gradually. Their first two applications leveraging AIQ had different areas of focus: one was switching from manual testing to automation with autonomous AI-driven testing for a new application launching within six months, while the second was shifting its open source tests to AIQ and increasing coverage by adding new self-healing UI and API tests along with load/performance and security tests. Working with the Appvance customer success team, the company deployed AIQ to their AWS Cloud and integrated with their GIT repositories. Their implementation is scalable, with ondemand test nodes spinning up and down to drive their test scenarios on an as-needed basis.
Test results including snapshots, logs, and error messages are published to an interactive dashboard which provides application health status, easy triage/prioritization of issues, and root cause analysis.
AIQ has enabled consistent automation testing control globally and streamlined the QE/QA process and toolset while enabling the company’s dev teams to focus on new feature releases rather than regression tests. This step forward has led to higher code quality and happier customers. This happy Appvance customer is now rolling out AIQ to additional applications to unlock these benefits across more of their software portfolio.
Key Results
AI-generated scripts have resulted in 97% code coverage
Resolved a serious Log4j vulnerability
Enabled continuous delivery of code