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Measuring the importance of data quality to causal AI success

Dynatrace

Traditional analytics and AI systems rely on statistical models to correlate events with possible causes. It removes much of the guesswork of untangling complex system issues and establishes with certainty why a problem occurred. Fragmented and siloed data storage can create inconsistencies and redundancies. Timeliness.

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Maximizing Performance of AWS RDS for MySQL with Dedicated Log Volumes

Percona

A Dedicated Log Volume (DLV) is a specialized storage volume designed to house database transaction logs separately from the volume containing the database tables. DLVs are particularly advantageous for databases with large allocated storage, high I/O per second (IOPS) requirements, or latency-sensitive workloads.

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Characterizing, modeling, and benchmarking RocksDB key-value workloads at Facebook

The Morning Paper

Characterizing, modeling, and benchmarking RocksDB key-value workloads at Facebook , Cao et al., Or in the case of key-value stores, what you benchmark. So if you want to design a system that will offer good real-world performance, it’s really useful to have benchmarks that accurately represent real-world workloads.

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Redis vs Memcached in 2024

Scalegrid

This article will explore how they handle data storage and scalability, perform in different scenarios, and, most importantly, how these factors influence your choice. It uses a hash table to manage these pairs, divided into fixed-size buckets with linked lists for key-value storage. High data availability is achieved.

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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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Evaluating the Evaluation: A Benchmarking Checklist

Brendan Gregg

These have inspired me to summarize another performance activity: evaluating benchmark accuracy. Accurate benchmarking rewards engineering investment that actually improves performance, but, unfortunately, inaccurate benchmarking is more common. If the benchmark reported 20k ops/sec, you should ask: why not 40k ops/sec?

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How To Scale a Single-Host PostgreSQL Database With Citus

Percona

Rather than listing the concepts, function calls, etc, available in Citus, which frankly is a bit boring, I’m going to explore scaling out a database system starting with a single host. And now, execute the benchmark: -- execute the following on the coordinator node pgbench -c 20 -j 3 -T 60 -P 3 pgbench The results are not pretty.

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