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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. Have a look at them on our Dynatrace Playground.

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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.

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Comparing Approaches to Durability in Low Latency Messaging Queues

DZone

A significant feature of Chronicle Queue Enterprise is support for TCP replication across multiple servers to ensure the high availability of application infrastructure. Little’s Law and Why Latency Matters. In many cases, the assumption is that as long as throughput is high enough, the latency won’t be a problem.

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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?

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Introducing Netflix’s Key-Value Data Abstraction Layer

The Netflix TechBlog

Second, developers had to constantly re-learn new data modeling practices and common yet critical data access patterns. These include challenges with tail latency and idempotency, managing “wide” partitions with many rows, handling single large “fat” columns, and slow response pagination.

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Single-core memory bandwidth: Latency, Bandwidth, and Concurrency

John McCalpin

The Multicore Era Over the past ~15 years, server processors from Intel and AMD have evolved from the early quad-core processors to the current monsters with over 50 cores per socket. “Concurrency” is the amount of data that must be “in flight” between the core and the memory in order to maintain a steady-state system.

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Introducing Netflix TimeSeries Data Abstraction Layer

The Netflix TechBlog

Rajiv Shringi Vinay Chella Kaidan Fullerton Oleksii Tkachuk Joey Lynch Introduction As Netflix continues to expand and diversify into various sectors like Video on Demand and Gaming , the ability to ingest and store vast amounts of temporal data — often reaching petabytes — with millisecond access latency has become increasingly vital.

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