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How zero trust architecture can improve government user experiences

Dynatrace

As federal agencies implement zero trust (ZT) as directed by the White House “Executive Order on Improving the Nation’s Cybersecurity,” there’s growing concern that zero trust architecture and great user experiences can’t coexist. I filled out a form, input my government ID information, and waited for a confirmation code that never came.

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RSA guide 2024: AI and security are top concerns for organizations in every industry

Dynatrace

But only 21% said their organizations have established policies governing employees’ use of generative AI technologies. Additionally, blind spots in cloud architecture are making it increasingly difficult for organizations to balance application performance with a robust security posture.

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How to achieve the pillars of zero trust at federal agencies

Dynatrace

Government Toward Zero Trust Cybersecurity Principles , have increased federal IT and security leaders’ urgency to implement zero trust (ZT). Dynatrace observability provides deep visibility analytics into the cloud, hosts, services, processes, containers, and applications, along with automation and orchestration.

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Causal AI use cases for modern observability that can transform any business

Dynatrace

Software project managers can optimize development processes by analyzing workflow data, such as development time, code commits, and testing phases. Government. Government agencies can learn from cause-and-effect relationships to make more evidence-based policy decisions.

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Who will watch the watchers? Extended infrastructure observability for WSO2 API Manager

Dynatrace

Sure, cloud infrastructure requires comprehensive performance visibility, as Dynatrace provides , but the services that leverage cloud infrastructures also require close attention. Cloud-based application architectures commonly leverage microservices. Extend infrastructure observability to WSO2 API Manager.

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Measuring the importance of data quality to causal AI success

Dynatrace

Improving data quality is a strategic process that involves all organizational members who create and use data. It starts with implementing data governance practices, which set standards and policies for data use and management in areas such as quality, security, compliance, storage, stewardship, and integration.

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IT modernization improves public health services at state human services agencies

Dynatrace

The pandemic has transformed how government agencies such as Health and Human Services (HHS) operate. It may be challenging to accurately catalog where applications are stored if some are maintained within a current infrastructure model while others are not.