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The capabilities government leaders need as they manage the cloud’s data explosion

Dynatrace

This shift makes it harder to monitor, observe, and analyze data across a distributed technology stack. . But these new technologies are becoming increasingly complex to manage, as CIOs in the sector confirm that a single application transaction crosses 41 different technologies. .

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From observability to sustainability: Reduce your IT carbon footprint with Dynatrace Carbon Impact

Dynatrace

More importantly, these tools are fundamentally backward-looking, lacking both the time and dimensional granularity required for carbon-emission analytics and optimization insights. Environmental sustainability emphasizes our collective responsibility to take action; for this, we need intelligence and analytics, not just historical reports.

Energy 188
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Redis vs Memcached in 2024

Scalegrid

In this comparison of Redis vs Memcached, we strip away the complexity, focusing on each in-memory data store’s performance, scalability, and unique features. Performance Comparison: Redis vs Memcached Although Redis and Memcached are high-performance in-memory data stores, their performance characteristics are distinct.

Cache 130
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APM tools vs. APM platform: What’s the difference?

Dynatrace

Both terms refer to technologies and practices, and both approaches aim to detect and pinpoint application performance issues before real users are impacted. In comparison, APM platforms provide a single integrated platform using AI and automation to deliver a precise, context-aware analysis of the application environment.

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Real-Time Digital Twins: A New Approach to Streaming Analytics

ScaleOut Software

Consider the typical, conventional streaming analytics pipeline available on popular cloud platforms: A conventional pipeline combines telemetry from all data sources into a single stream which is queried by the user’s streaming analytics application. However, real-time digital twins easily bring these capabilities within reach.

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Dynatrace accelerates business transformation with new AI observability solution

Dynatrace

It requires specialized talent, a new technology stack to manage and deploy models, an ample budget for rising compute costs, and end-to-end security. To observe model drift and accuracy, companies can use holdout evaluation sets for comparison to model data. Enterprises that fail to adapt to these innovations face extinction.

Cache 209
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New SNMP platform extensions provide observability at scale for network devices

Dynatrace

The built-in unified analysis pages offer real-time comparison of key performance indicators while applying a topology-first approach to the data. Simplified data analysis presented in topological context. Advanced load balancer analysis.

Network 216