CA Technologies announced updates to its mainframe solutions that are designed to accelerate modernization and integration initiatives, allowing enterprises to leverage mainframes as strategic enablers of digital transformation to drive revenue growth. These new and enhanced offerings enable customers to use intelligence and automation to maximize resources and protect data while working with the latest technologies and open innovations, across hybrid environments. For enterprises struggling to keep pace with agile development and DevOps methodologies while dealing with limited resources, updates to CA’s leading Continuous Testing solutions provide mainframe organizations with testing capabilities that enable faster delivery of higher quality software. Development teams can more efficiently conduct software tests by virtualizing mainframe environments with CA Service Virtualization; conduct functional and performance testing with CA BlazeMeter; and create test data that never leaves the mainframe with CA Test Data Manager. IT operations leaders are managing increasingly complex environments that span from the mainframe to a range of cloud and distributed platforms. CA Operational Intelligence recently introduced as part of CA’s AI Ops-driven platform provides comprehensive service intelligence, analyzes diverse structured and unstructured data sources from the cloud to the mainframe to help IT operations teams act on potential issues much earlier, isolate root causes faster and ultimately remediate issues before they impact the business. Leveraging mainframe data and applications to drive new innovative apps and engagements with customers means enterprises are dealing with greater exposure to compliance risks. Compliance is an issue that affects all data and processes, so it’s critical to have simplified solutions that can fully analyze risk exposure on the mainframe. New machine-learning capabilities in CA Data Content Discovery simplifies the creation of custom analytics and data classifiers to enable much higher levels of accuracy, automates the discovery of new data as it is generated to address compliance issues at scale, and improves visualization of key insights to make it easier for mainframe and non-mainframe IT staff to easily understand potential risks across mainframe data infrastructures.