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Why applying chaos engineering to data-intensive applications matters

Dynatrace

Stream processing One approach to such a challenging scenario is stream processing, a computing paradigm and software architectural style for data-intensive software systems that emerged to cope with requirements for near real-time processing of massive amounts of data. This significantly increases event latency.

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How To Scale a Single-Host PostgreSQL Database With Citus

Percona

About the cluster Following a step-by-step process, the objective is to create a four-node cluster consisting of: PostgreSQL version 15 Citus extension (I’ll be using version 11, but there are newer ones available.) In order to speed up the benchmark indexes must be added.

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Detecting Speech and Music in Audio Content

The Netflix TechBlog

Iroro Orife , Chih-Wei Wu and Yun-Ning (Amy) Hung Introduction When you enjoy the latest season of Stranger Things or Casa de Papel (Money Heist) , have you ever wondered about the secrets to fantastic story-telling, besides the stunning visual presentation? Let’s have a look at a few applications. What constitutes music or speech?

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Grafana Dashboards: A PoC Implementing the PostgreSQL Extension pg_stat_monitor

Percona

The collected data is aggregated and presented in a single view. This simplifies debugging and analysis processes by enabling users to execute the same query. A script executing a benchmarking run: #!/bin/bash pg_stat_monitor About pg_stat_monitor is a Query Performance Monitoring tool for PostgreSQL.

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How to maximize CPU performance for PostgreSQL 12.0 benchmarks on Linux

HammerDB

HammerDB doesn’t publish competitive database benchmarks, instead we always encourage people to be better informed by running their own. So over at Phoronix some database benchmarks were published showing PostgreSQL 12 Performance With AMD EPYC 7742 vs. Intel Xeon Platinum 8280 Benchmarks .

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The top 5 reasons to run your own database benchmarks

HammerDB

Some opinions claim that “Benchmarks are meaningless”, “benchmarks are irrelevant” or “benchmarks are nothing like your real applications” However for others “Benchmarks matter,” as they “account for the processing architecture and speed, memory, storage subsystems and the database engine.”

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Crucial Redis Monitoring Metrics You Must Watch

Scalegrid

Key metrics like throughput, request latency, and memory utilization are essential for assessing Redis health, with tools like the MONITOR command and Redis-benchmark for latency and throughput analysis and MEMORY USAGE/STATS commands for evaluating memory. This plays a crucial role in supervising the replication process.

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