A look at the future of software testing: HPE vision for Continuous Testing

Hewlett Packard Enterprise

Many organizations struggle with the implementation of the engineering practices of DevOps, specifically with continuous testing. What if software development teams had a solution that was 100% cloud based (for distributed teams), provided real-time data analytics (for quick feedback), and supported the activities of build, edit and execution of test scripts in the cloud (nothing on the desktop). Couple that with the ability to test mobile apps on multiple devices (for scale and efficiency), the option to use containers plus existing tools (including open source), and support visual UX testing (for user experience and accessibility) while linking directly to existing continuous delivery infrastructure, and the goal of continuous testing becomes in reach.
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Spotlight

As the need for separate tools in some situations is recognized, so is the need for traceability between the two environments. Although business and IT will continue to have different perspectives on process models, governance of the process-modeling life cycle can coordinate modeling efforts between the different participants. This helps to create a seamless integration of the highest-level business models to executing processes, thereby aligning the goals and efforts of business and IT


OTHER ON-DEMAND WEBINARS

Protecting IoT Devices & Networks From Cyber Crime

Cradlepoint

The potential of widely distributed IoT devices to enable new business opportunities, streamline operations, and reduce costs is vast, but so are the security implications. With IoT playing an increasingly big role at branch offices, within vehicles and in the wild, larger attack surfaces are giving IT teams more to worry about than ever before. Well-publicized attacks such as Mirai botnets and WannaCry grabbed headlines, but they're just the tip of the iceberg. IoT threats are becoming too prevalent and advanced to address with traditional security tools. Now is the time for software-defined, policy-based security solutions that isolate IoT devices and protect organizations' most valuable data — regardless of the WAN source.
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The Future of Artificial Intelligence Startups

Founder Institute

Artificial intelligence and machine learning is changing the world as we know it, and entrepreneurs are just starting to scratch the surface on leveraging its power to upend industries like transportation, security, healthcare, finance, and more.
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7 Requirements of Monitoring Cloud Apps & Infrastructure

New Relic

The flexibility, scale, services, and pay-as-you-go pricing options provided by modern cloud platforms—Amazon Web Services (AWS), Microsoft Azure, Google Cloud Platform, and tools like Pivotal among them—have completely changed how you architect applications and deploy infrastructure. In order to effectively manage the dynamic natures of these cloud-based applications and infrastructure, the way you monitor—and the tools you use to do so—need to change, as well.
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A look at the future of software testing: HPE vision for Continuous Testing

Hewlett Packard Enterprise

Many organizations struggle with the implementation of the engineering practices of DevOps, specifically with continuous testing. What if software development teams had a solution that was 100% cloud based (for distributed teams), provided real-time data analytics (for quick feedback), and supported the activities of build, edit and execution of test scripts in the cloud (nothing on the desktop). Couple that with the ability to test mobile apps on multiple devices (for scale and efficiency), the option to use containers plus existing tools (including open source), and support visual UX testing (for user experience and accessibility) while linking directly to existing continuous delivery infrastructure, and the goal of continuous testing becomes in reach.
Watch Now

Spotlight

As the need for separate tools in some situations is recognized, so is the need for traceability between the two environments. Although business and IT will continue to have different perspectives on process models, governance of the process-modeling life cycle can coordinate modeling efforts between the different participants. This helps to create a seamless integration of the highest-level business models to executing processes, thereby aligning the goals and efforts of business and IT

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