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How low-code/no-code AutomationEngine advances automated workflows

Dynatrace

But to be scalable, they also need low-code/no-code solutions that don’t require a lot of spin-up or engineering expertise. According to recent Dynatrace data, 59% of CIOs say the increasing complexity of their technology stack could soon overload their teams without a more automated approach to IT operations and automated workflows.

Code 221
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Enhancing Azure data analytics and Azure observability with Dynatrace Grail

Dynatrace

Azure observability and Azure data analytics are critical requirements amid the deluge of data in Azure cloud computing environments. As digital transformation accelerates and more organizations are migrating workloads to Azure and other cloud environments, they need observability and data analytics capabilities that can keep pace.

Azure 188
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Unmatched scalability and security of Dynatrace extensions now available for all supported technologies: 7 reasons to migrate your JMX and Python plugins

Dynatrace

already address SNMP, WMI, SQL databases, and Prometheus technologies, serving the monitoring needs of hundreds of Dynatrace customers. are technologically very different, Python and JMX extensions designed for Extension Framework 1.0 Extensions can monitor virtually any type of technology in your environment. Extensions 2.0

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How unified data and analytics offers a new approach to software intelligence

Dynatrace

However, cloud infrastructure has become increasingly complex. Further, the delivery infrastructure that makes this happen has also become complex. IT pros want a data and analytics solution that doesn’t require tradeoffs between speed, scale, and cost. The next frontier: Data and analytics-centric software intelligence.

Analytics 200
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Why log monitoring and log analytics matter in a hyperscale world

Dynatrace

Log monitoring, log analysis, and log analytics are more important than ever as organizations adopt more cloud-native technologies, containers, and microservices-based architectures. What is log analytics? Log analytics is the process of evaluating and interpreting log data so teams can quickly detect and resolve issues.

Analytics 218
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Extending modern observability for exploratory analytics

Dynatrace

As organizations adopt more cloud-based technologies, the increased volume and variety of data from these ecosystems drive complexity. A modern observability and analytics platform brings data silos together and facilitates collaboration and better decision-making among teams. Here are some examples: IT infrastructure and operations.

Analytics 130
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TTP-based threat hunting with Dynatrace Security Analytics and Falco Alerts solves alert noise

Dynatrace

Not only are cyberattacks increasing, but they’re also becoming more sophisticated, with tools such as  WormGPT  putting generative AI technology in the hands of attackers. In this blog post, we’ll use Dynatrace Security Analytics to go threat hunting, bringing together logs, traces, metrics, and, crucially, threat alerts.

Analytics 205