Businesses today are using every tool available to boost productivity and gain an edge in their highly competitive markets. Against this backdrop of demands for high output from every business line, developers are turning to third-party code, including open source software (OSS), to save time and build their applications faster. Recent research by TechTarget’s Enterprise Strategy Group showed that this tactic is increasingly popular for developers across industries, though it may pose challenges even as it solves efficiency problems.
Insight
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Vulnerabilities to cyberattacks across the software supply chain plague today’s cybersecurity teams. From attacks targeting the open source software (OSS) in their code to cloud misconfigurations and stolen secrets, a variety of attack vectors means approaches to software supply chain security must be multifaceted. Recent research by TechTarget’s Enterprise Strategy Group examined these trends to find out where organizations are in their journey to a comprehensive software supply chain security strategy.
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As organizations across industries seek to gain a competitive advantage by efficiently delivering feature-rich applications to their customers, employees, and partners, their developers increasingly leverage third-party and open source code components. This saves time from having to build custom code but poses challenges for security teams, who need to know the inventories of their applications—including all the software components, dependencies, and metadata in the applications—to effectively manage risk and rapidly respond to threats or attacks. As attacks have often targeted the software supply chain, regulations increasingly call for a software bill of materials (SBOM) to proactively mitigate software supply chain risk. Recent research by TechTarget’s Enterprise Strategy Group examined how organizations are using SBOMs and how they can best use SBOMs for effective software supply chain security.
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Along with the excitement of using AI to supercharge business operations comes anxiety about protecting the massive data sets used in the models. Recent research by TechTarget’s Enterprise Strategy Group revealed that at large and smaller organizations, IT practitioners charged with backing up AI-generated data are struggling to keep up and face numerous challenges.
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Data protection teams are under constant pressure to perform in light of mounting regulations, high-profile ransomware attacks, and more. Recent research by TechTarget’s Enterprise Strategy Group showed that data backup and recovery professionals are increasingly looking to AI for help with their operations, though their journey to deployment looks different depending on their organizations’ size.
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Injecting efficiency into operations to gain competitive advantages is a constant business mandate, but using technologies like automation, AI, and machine learning to do so can be a new frontier for some industries. Recent research by TechTarget’s Enterprise Strategy Group examined the willingness and enthusiasm for using these technologies for data backup and recovery processes in different industries.
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Facing demands to increase productivity and scale, organizations are moving to cloud-native application development and delivery leveraging Kubernetes to automate deployment. However, security teams are struggling to keep up. Consequently, organizations are more broadly adopting DevSecOps practices that incorporate security into development processes to reduce the security misconfigurations deployed to the cloud. Additionally, organizations are looking to leverage platforms procured from a smaller set of vendors to realize a unified cybersecurity posture across distributed cloud environments. TechTarget’s Enterprise Strategy Group recently surveyed IT, cybersecurity, and application development professionals to gain insights into these trends.
To learn more about these trends, download the free infographic, The State of Cloud Security Platforms and DevSecOps.
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Amid the breakneck pace of AI integration into nearly every facet of today’s businesses, organizations increasingly face the difficult challenge of ensuring responsible AI use across their entire ecosystems. Effective policies and strategies ultimately comprise a host of crucial considerations with data used in AI models and technologies, including accountability, transparency, accuracy, security, reliability, explainability, bias, fairness, privacy, and others. TechTarget’s Enterprise Strategy Group recently surveyed professionals involved in the strategy, decision-making, selection, deployment, and management of AI initiatives and projects to gain insights into these trends.
To learn more about these trends, download the free infographic, Evaluating the Pillars of Responsible AI.
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Facing demands to increase productivity and scale, organizations are moving to cloud-native application development and delivery leveraging Kubernetes to automate deployment. However, security teams are struggling to keep up, resulting in security incidents that cause application downtime, unauthorized access, data loss, and compliance fines. Consequently, organizations are more broadly adopting DevSecOps practices that incorporate security into development and DevOps processes to reduce the security misconfigurations deployed to the cloud and more quickly mitigate security issues when they are found in running applications. Additionally, organizations are looking to leverage suites and platforms procured from a smaller set of vendors or even a single vendor to reduce complexity and realize a unified cybersecurity posture across distributed cloud environments.
To gain further insight into these trends, TechTarget’s Enterprise Strategy Group surveyed 374 IT, cybersecurity, and application development professionals at organizations in North America (US and Canada) responsible for evaluating or purchasing cloud security technology products and services.
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Recently, Dell Technologies and Nutanix announced two new solutions: Dell XC Plus and Dell PowerFlex with Nutanix Cloud Platform. Available now, Dell XC Plus provides a turnkey hyperconverged infrastructure (HCI) appliance that integrates the Nutanix Cloud Platform software on Dell PowerEdge hardware. The Dell PowerFlex with Nutanix Cloud Platform announcement is a preview of an upcoming release, where Dell and Nutanix will integrate Dell PowerFlex storage to offer users an external storage option for Nutanix Cloud Platform.
To learn more, download the free brief, Dell Technologies and Nutanix Reignite Their Partnership.
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Amid the breakneck pace of AI integration into nearly every facet of today’s businesses, organizations increasingly face the difficult challenge of ensuring responsible AI use across their entire ecosystems. Creating robust, comprehensive policies that ensure AI technologies are developed and used ethically and responsibly is now a top priority, even for organizations still in the early stages of AI deployments. Effective policies and strategies ultimately comprise a host of crucial considerations with data used in AI models and technologies, including accountability, transparency, accuracy, security, reliability, explainability, bias, fairness, privacy, and others.
Without effective responsible AI strategies, organizations risk numerous impacts to their businesses and processes, ranging from reputational damage and legal consequences to increased costs and slower time to market. While the need for responsible AI is clear, execution is a challenging endeavor for most organizations as they work to keep pace with a fast-moving market, as well as stay ahead of evolving regulations that increasingly define the overall use of AI. To gain further insight into these trends and challenges, TechTarget’s Enterprise Strategy Group surveyed 374 professionals at organizations in North America (US and Canada) involved in the strategy, decision-making, selection, deployment, and management of artificial intelligence initiatives and projects.
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Headless content management and commerce strategies can enable enterprises to keep up with the evolution of devices, apps, and channels their customers use, but traditional content management systems make the headless approach difficult or unattainable. Many content management software vendors have transitioned from on-premises to cloud offerings and broken their application features into microservices. This has led to a wider range of choices for buyers and paved the way for API-driven headless architecture as well as hybrid and decoupled CMSs. TechTarget’s Enterprise Strategy Group recently surveyed IT and business professionals responsible for digital transformation strategies, digital experience platforms (DXPs), and customer experience ecosystems to understand how DXPs are evolving.
To learn more about these trends, download the free infographic, The Evolution of Digital Experience Platforms.