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Next-level interaction and customization of data visualizations in Dynatrace Dashboards and Notebooks

Dynatrace

Go to our documentation to learn more about implementing honeycomb visualizations on your dashboards or notebooks. While histograms look much like time-series bar charts, they’re different in that each bar represents a count (often termed frequency) of metric values.

Latency 246
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AI-driven analysis of Spring Micrometer metrics in context, with typology at scale

Dynatrace

Micrometer is used for instrumenting both out-of-the-box and custom metrics from Spring Boot applications. Davis topology-aware anomaly detection and alerting for your Micrometer metrics. Topology-related custom metrics for seamless reports and alerts. Micrometer uses a registry to export metrics to monitoring systems.

Metrics 246
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RabbitMQ vs. Kafka: Key Differences

Scalegrid

Its partitioned log architecture supports both queuing and publish-subscribe models, allowing it to handle large-scale event processing with minimal latency. Apache Kafka uses a custom TCP/IP protocol for high throughput and low latency. Apache Kafka, designed for distributed event streaming, maintains low latency at scale.

Latency 147
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OpenTelemetry 101: A nontechnical guide for IT leaders and enthusiasts

Dynatrace

Observability Observability is the ability to determine a system’s health by analyzing the data it generates, such as logs, metrics, and traces. There are three main types of telemetry data: Metrics. Metrics are typically aggregated and stored in time series databases for monitoring and alerting purposes.

Latency 264
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Get up to 300 new metrics out of the box with AWS supporting services (GA)

Dynatrace

To reduce your CloudWatch costs and throttling, you can now select from additional services and metrics to monitor. Get up to 300 new AWS metrics out of the box. Dynatrace ingests AWS CloudWatch metrics for multiple preselected services. Amazon ElastiCache (see AWS documentation for Memcached and Redis ). Amazon Aurora.

AWS 200
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Maximize user experience with out-of-the-box service-performance SLOs

Dynatrace

These signals ( latency, traffic, errors, and saturation ) provide a solid means of proactively monitoring operative systems via SLOs and tracking business success. While this connection might sound simple, finding the right metrics to measure the needed SLIs takes time and effort. This is what Dynatrace captures as response time.

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Dynatrace automatically monitors OpenAI ChatGPT for companies that deliver reliable, cost-effective services powered by generative AI

Dynatrace

A typical design pattern is the use of a semantic search over a domain-specific knowledge base, like internal documentation, to provide the required context in the prompt. With these latency, reliability, and cost measurements in place, your operations team can now define their own OpenAI dashboards and SLOs.