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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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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.

Latency 275
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Optimising for High Latency Environments

CSS Wizardry

This gives fascinating insights into the network topography of our visitors, and how much we might be impacted by high latency regions. Round-trip-time (RTT) is basically a measure of latency—how long did it take to get from one endpoint to another and back again? What is RTT? That’s exactly what this article is about.

Latency 234
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Next-level interaction and customization of data visualizations in Dynatrace Dashboards and Notebooks

Dynatrace

New: identify hotspots with the honeycomb visualization Honeycombs are great for visualizing health in complex and distributed systems, enabling you to visualize countless entities effectively and at scale. To achieve the best visual outcome, we recommend experimenting with the available customization options.

Latency 246
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Rapid Event Notification System at Netflix

The Netflix TechBlog

To this end, we developed a Rapid Event Notification System (RENO) to support use cases that require server initiated communication with devices in a scalable and extensible manner. In this blog post, we will give an overview of the Rapid Event Notification System at Netflix and share some of the learnings we gained along the way.

Systems 334
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Single-core memory bandwidth: Latency, Bandwidth, and Concurrency

John McCalpin

Understanding sustained memory bandwidth in these systems starts with assuming 100% utilization and then reviewing the factors that get in the way (e.g., This requires a completely different approach to modeling the memory system — one based on Little’s Law from queueing theory.

Latency 71
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Build systems more reliably with Dynatrace: Chaos Engineering

Dynatrace

These releases often assumed ideal conditions such as zero latency, infinite bandwidth, and no network loss, as highlighted in Peter Deutsch’s eight fallacies of distributed systems. With Dynatrace, teams can seamlessly monitor the entire system, including network switches, database storage, and third-party dependencies.