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Best practices and key metrics for improving mobile app performance

Dynatrace

As a result, organizations need to monitor mobile app performance metrics that are meaningful and actionable by gaining adequate observability of mobile app performance. There are many common mobile app performance metrics that are used to measure key performance indicators (KPIs) related to user experience and satisfaction.

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Nine ways technology executives can get significant business value with the right observability platform

Dynatrace

Realizing that executives from other organizations are in a similar situation to my own, I want to outline three key objectives that Dynatrace’s powerful analytics can help you deliver, featuring nine use cases that you might not have thought possible. Change is my only constant.

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Redis® Monitoring Strategies for 2024

Scalegrid

Buckle up as we delve into the world of Redis® monitoring, exploring the most important Redis® metrics, discussing essential tools, and even peering into the future of Redis® performance management. Identifying key Redis® metrics such as latency, CPU usage, and memory metrics is crucial for effective Redis monitoring.

Strategy 130
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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. If you’ve read about observability, you likely know that collecting the measurements of logs, metrics, and distributed traces are the three key pillars to achieving success.

Metrics 363
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Why applying chaos engineering to data-intensive applications matters

Dynatrace

Stream processing systems, designed for continuous, low-latency processing, demand swift recovery mechanisms to tolerate and mitigate failures effectively. This significantly increases event latency. Spark Structured Streaming can also provide consistent fault recovery for applications where latency is not a critical requirement.

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Implementing service-level objectives to improve software quality

Dynatrace

By implementing service-level objectives, teams can avoid collecting and checking a huge amount of metrics for each service. Establish realistic SLO targets based on statistical and probabilistic analysis. This process includes benchmarking realistic SLO targets based on statistical and probabilistic analysis from Dynatrace.

Software 269
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Enhanced AI model observability with Dynatrace and Traceloop OpenLLMetry

Dynatrace

OpenTelemetry has become a standard for collecting traces, metrics, and logs. Utilizing an additional OpenTelemetry SDK layer, this data seamlessly flows into the Dynatrace environment, offering advanced analytics and a holistic view of the AI deployment stack. Maintained under the Apache 2.0 However, Python models are trickier.