Today, “the office” can be anywhere, and traditional security just can’t keep up. That’s where Cisco Umbrella comes in. Powered by predictive intelligence, Umbrella acts as your first line of defense against threats. Read this ebook to learn how this unique advantage can make a difference for your organization.
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Get proven success factors for your security program based on data from 4,800 security experts
We asked respondents about their organization’s adherence to 25 security practices spanning governance, strategy, spending, architecture, and operations.
We then asked about each program’s level of success across roughly a dozen high-level security objectives or outcomes organized into three main categories:
Next, we conducted extensive multivariate analysis to identify security practices that correlate strongly with successful program-level outcomes.
We’ve broken down their answers into best practices, and determined which have the most impact on security outcomes and objectives.
In other words: based on what your organization wants to achieve in security, these are things you should be doing to increase your chances of success. You’ll learn which security practices rank most effective, and which are making the least difference. We found quite a few unexpected correlations. Get the study to learn more.
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Are you using vulnerable cloud apps that open the door to ransomware, malware, or other types of network attacks? Our Cisco Umbrella infographic reveals the three riskiest ones in 2021.
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An astonishing 98% of cloud services are adopted without any IT oversight.
And when your employees act as their own tech professionals to use their favorite chat, cloud storage, and other insecure apps, that’s more than just conducting shadow IT, it’s directly putting your network at risk.
Your challenge? Protecting your network against ransomware, malware, and other attacks. In 3 steps to managing shadow IT, you’ll learn how to:
In 3 steps to managing shadow IT, we highlight the app security tools you need to block threats from streaming, messaging, and other insecure apps. Use these tips to keep your network, data, and workers safe.
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Despite the ongoing push to “shift left” testing for Agile and DevOps, in-sprint UI test automation remains infeasible. Human-driven UI testing is incredibly intuitive, but UI test automation is considered too slow, too fragile, and way too late for today’s fast-paced teams. Automated UI tests traditionally require a fully-implemented — and stable — UI to be in place before they are created. This means they’re often delayed until a later sprint or scrapped altogether.
But making UI test automation more human-like can resolve these challenges, enabling you to create resilient UI test automation even before a single line of code is written. Read this paper to learn how a new AI-driven approach to this traditionally slow test automation practice can dramatically simplify your testing and get you to “done done” in record time.
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Reducing testing costs is often the first thing organizations think about when they consider adopting test automation. After all, software testing is shockingly expensive; it accounts for an average of 23-35% of the overall IT spend, per the latest World Quality Report. Test automation frees humans to focus on more interesting and value-added tasks while routine checks are performed faster, more frequently, and with increased precision.
Clearly, the value is there. However, even open-source testing tools require a resource investment, and that requires the buy-in of someone higher up. How do you convince the business that test automation is really worth the time, effort, and cost required?
This paper outlines what’s needed to build a strong business case for test automation. It covers:
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With every business becoming a digital enterprise, the ability to rapidly release reliable applications is now a core strategic advantage. Are Fortune 500 and equivalent organizations prepared for the digital race ahead? The answer may lie in their software testing process, which can be either a curse or catalyst to speedy innovation.
Continuous Testing enables software to be released 10x faster than traditional testing allows. Yet, its adoption is limited – particularly among large enterprise organizations.
This first-of-its-kind report sheds light on how industry leaders test the software that their business (and the world) relies on. Read this benchmark report to learn:
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At the top of every CIO’s mind is how to drive forward innovation at speed, increase levels of productivity, deliver superior and highly scalable digital products and services that increase customer satisfaction, and save costs – all at the same time. Unfortunately, without modernizing your testing with intelligent automation, and treating testing as a strategic component to your digital success, you won’t be as competitive and you can’t innovate as quickly. How do we get there?
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AI isn’t the future of testing; it’s the present-day reality, with ever-increasing significance as organizations are propelling into the next normal. New approaches to AI-powered automation relieve many of the lingering pains that have impeded test automation for decades. Using AI to drive the application like a human would, your team can build extremely resilient future-proof tests across any technology.
Read this paper to learn:
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A recent study from Tricentis on the state of enterprise testing reveals that dev and test cycles are out of sync. The average test cycle time of 23 days is ill-suited for today’s fast-paced development lifecycles. That’s because neither manual testing nor legacy, script-based tools offer enough efficiency or capability to handle today’s accelerated dev cycles.
Read this white paper and learn:
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