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Understanding and Managing Latency in APISIX: A Comprehensive Technical Guide

DZone

A common query from users revolves around the precise measurement of latency in APISIX. When utilizing APISIX, how should one address unusually high latency? In reality, discussions on latency measurement are centered around the performance and response time of API requests.

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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. 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. One way to achieve this is by storing data closer to the users.

Latency 246
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Mastering Latency With P90, P99, and Mean Response Times

DZone

In the fast-paced digital world, where every millisecond counts, understanding the nuances of network latency becomes paramount for developers and system architects. Latency, the delay before a transfer of data begins following an instruction for its transfer, can significantly impact user experience and system performance.

Latency 147
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Comparing Approaches to Durability in Low Latency Messaging Queues

DZone

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. However, latency is often a key factor in why the throughput isn’t high enough. This is the first time I have benchmarked it with a realistic example.

Latency 275
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Simulate Network Latency and Packet Drop In Linux

DZone

There may be a scenario when you want to test an application when the network is slow(we also call it high network latency). Or you are reproducing a customer scenario(having high network latency) where some anomalous behavior is observed. In the Chrome browser, we can easily Simulate a slower network connection.

Latency 239
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Reducing Network Latency and Improving Read Performance With CockroachDB and PolyScale.ai

DZone

This versatility provides a cost-effective solution to reduce global network latency by bringing the database closer to the end user. PolyScale operates a global network of PoPs (Points of Presence). Think of PoPs as regional database connections.

Latency 242
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Allegro Reduces Kafka Producer Latency Outliers by 82% After Switching to XFS

InfoQ

Allegro experimented with different performance optimization options to improve Apache Kafka producer tail latency and eventually switched all its clusters to the XFS filesystem. The company used Kafka protocol sniffing, JVM profiling, and eBPF, which proved instrumental in identifying and eliminating performance bottlenecks.

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