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Google Cloud Next 2024: AI innovation for Google Cloud

Dynatrace

In today’s rapidly evolving landscape, incorporating AI innovation into business strategies is vital, enabling organizations to optimize operations, enhance decision-making processes, and stay competitive. The annual Google Cloud Next conference explores the latest innovations for cloud technology and Google Cloud.

Google 258
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Dynatrace innovates again with the release of topology-driven auto-adaptive metric baselines

Dynatrace

With the advent and ingestion of thousands of custom metrics into Dynatrace, we’ve once again pushed the boundaries of automatic, AI-based root cause analysis with the introduction of auto-adaptive baselines as a foundational concept for Dynatrace topology-driven timeseries measurements. In many cases, metric behavior changes over time.

Metrics 207
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Accelerating innovation with Kubernetes and Dynatrace

Dynatrace

Running workloads on top of Kubernetes is significantly valuable, not just for application teams, but for infrastructure teams as well. When it comes to observing Kubernetes environments, your approach must be rooted in metrics, logs, and traces —and also the context in which things happen and their impact on users. What’s Next.

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What is observability? Not just logs, metrics and traces

Dynatrace

In IT and cloud computing, observability is the ability to measure a system’s current state based on the data it generates, such as logs, metrics, and traces. An advanced observability solution can also be used to automate more processes, increasing efficiency and innovation among Ops and Apps teams.

Metrics 363
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AIOps for infrastructure monitoring: The observability advantage

Dynatrace

Infrastructure complexity is costing enterprises money. AIOps offers an alternative to traditional infrastructure monitoring and management with end-to-end visibility and observability into IT stacks. As 69% of CIOs surveyed said, it’s time for a “radically different approach” to infrastructure monitoring.

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Data lakehouse innovations advance the three pillars of observability for more collaborative analytics

Dynatrace

The short answer: The three pillars of observability—logs, metrics, and traces—converging on a data lakehouse. You’re getting all the architectural benefits of Grail—the petabytes, the cardinality—with this implementation,” including the three pillars of observability: logs, metrics, and traces in context.

Analytics 182
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Infrastructure Monitoring tools: 3 steps to evolve ITOps into AIOps

Dynatrace

Infrastructure monitoring is the process of collecting critical data about your IT environment, including information about availability, performance and resource efficiency. Many organizations respond by adding a proliferation of infrastructure monitoring tools, which in many cases, just adds to the noise. Dynatrace news.