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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

Key Takeaways Critical performance indicators such as latency, CPU usage, memory utilization, hit rate, and number of connected clients/slaves/evictions must be monitored to maintain Redis’s high throughput and low latency capabilities. These essential data points heavily influence both stability and efficiency within the system.

Metrics 130
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An open-source benchmark suite for microservices and their hardware-software implications for cloud & edge systems

The Morning Paper

An open-source benchmark suite for microservices and their hardware-software implications for cloud & edge systems Gan et al., Systems built with lots of microservices have different operational characteristics to those built from a small number of monoliths, we’d like to study and better understand those differences.

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Grafana Dashboards: A PoC Implementing the PostgreSQL Extension pg_stat_monitor

Percona

Querying the data While it is reasonable to create panels showing real-time load in order to explore better the types of queries that can be run against pg_stat_monitor, it is more practical to copy and query the data into tables after the benchmarking has completed its run. A script executing a benchmarking run: #!/bin/bash

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Redis vs Memcached in 2024

Scalegrid

Benchmarking Cache Speed Memcached is optimized for high read and write loads, making it highly efficient for rapid data access in a basic key-value store. Redis’s support for pipelining in a Redis server can significantly reduce network latency by batching command executions, making it beneficial for write-heavy applications.

Cache 130
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Supercomputing Predictions: Custom CPUs, CXL3.0, and Petalith Architectures

Adrian Cockcroft

on Myths and Legends of High Performance Computing  — it’s a somewhat light-hearted look at some of the same issues by the leader of the team that built the Fugaku system I mention below. HPCG is led by Japan’s RIKEN Fugaku system at 16 petaflops, which is 3% of it’s peak capacity. Next generation architectures will use CXL3.0

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Netflix at AWS re:Invent 2019

The Netflix TechBlog

4:45pm-5:45pm NFX 202 A day in the life of a Netflix Engineer Dave Hahn , SRE Engineering Manager Abstract : Netflix is a large, ever-changing ecosystem serving millions of customers across the globe through cloud-based systems and a globally distributed CDN. We explore all the systems necessary to make and stream content from Netflix.

AWS 100
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Netflix at AWS re:Invent 2019

The Netflix TechBlog

4:45pm-5:45pm NFX 202 A day in the life of a Netflix Engineer Dave Hahn , SRE Engineering Manager Abstract : Netflix is a large, ever-changing ecosystem serving millions of customers across the globe through cloud-based systems and a globally distributed CDN. We explore all the systems necessary to make and stream content from Netflix.

AWS 100