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

Dynatrace

Take your monitoring, data exploration, and storytelling to the next level with outstanding data visualization All your applications and underlying infrastructure produce vast volumes of data that you need to monitor or analyze for insights. Use color coding to tell a story. Min and max limits.

Latency 246
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Optimising for High Latency Environments

CSS Wizardry

Last week, I posted a short update on LinkedIn about CrUX’s new RTT data. Chrome have recently begun adding Round-Trip-Time (RTT) data to the Chrome User Experience Report (CrUX). This gives fascinating insights into the network topography of our visitors, and how much we might be impacted by high latency regions. What is RTT?

Latency 234
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Dynatrace on Microsoft Azure in Australia enables regional customers to leverage AI-powered observability

Dynatrace

As modern multicloud environments become more distributed and complex, having real-time insights into applications and infrastructure while keeping data residency in local markets is crucial. By keeping data within the region, Dynatrace ensures compliance with data privacy regulations and offers peace of mind to its customers.

Azure 278
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Comparing Approaches to Durability in Low Latency Messaging Queues

DZone

I have generally held the view that replicating data to a secondary system is faster than sync-ing to disk, assuming the round trip network delay wasn’t high due to quality networks and co-located redundant servers. Little’s Law and Why Latency Matters. However, latency is often a key factor in why the throughput isn’t high enough.

Latency 275
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Efficient Multimodal Data Processing: A Technical Deep Dive

DZone

Multimodal data processing is the evolving need of the latest data platforms powering applications like recommendation systems, autonomous vehicles, and medical diagnostics. Handling multimodal data spanning text, images, videos, and sensor inputs requires resilient architecture to manage the diversity of formats and scale.

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Netflix’s Distributed Counter Abstraction

The Netflix TechBlog

By: Rajiv Shringi , Oleksii Tkachuk , Kartik Sathyanarayanan Introduction In our previous blog post, we introduced Netflix’s TimeSeries Abstraction , a distributed service designed to store and query large volumes of temporal event data with low millisecond latencies. Today, we’re excited to present the Distributed Counter Abstraction.

Latency 251
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Improve Application Latency With Read Replicas Using YugabyteDB [Video]

DZone

Scalability and low latency are crucial for any application that relies on real-time data. One way to achieve this is by storing data closer to the users. In this post, we'll discuss how you can use YugabyteDB and its read replica nodes to improve the read latency for users across the globe.

Latency 246