Scalegrid

JANUARY 25, 2024

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. All these contribute significantly towards ensuring smooth functioning.

Metrics 130

Metrics Monitoring Latency Cache 130

Percona

JUNE 22, 2023

We will also discuss related configuration variables to consider that can impact these KPIs, helping you gain a comprehensive understanding of your MySQL server’s performance and efficiency. Query performance Query performance is a key performance indicator (KPI) in MySQL, as it measures the efficiency and speed of query execution.

Performance 102

Performance Monitoring Traffic Database 102

ACM Sigarch

OCTOBER 12, 2020

To be clear, these languages were not designed to be fast or space-efficient, but for ease of use. Unfortunately, languages like Python have proven resistant to efficient implementation, partly because of their design, and partly because of limitations imposed by the need to interop with C code. As Leiserson et al.

C++ 108

C++ Benchmarking Hardware Architecture 108

Percona

JUNE 22, 2023

Defining high availability In general terms, high availability refers to the continuous operation of a system with little to no interruption to end users in the event of hardware or software failures, power outages, or other disruptions. Load balancers can detect when a component is not responding and put traffic redirection in motion.

Availability 104

Availability Database Open Source Hardware 104

Percona

SEPTEMBER 1, 2023

Enhanced Database Efficiency By adjusting configuration settings, you can markedly enhance the overall efficiency of your MySQL database. This results in expedited query execution, reduced resource utilization, and more efficient exploitation of the available hardware resources. Experiencing database performance issues?

Tuning 52

Tuning Database Performance Hardware 52

The Morning Paper

MAY 23, 2019

Looking across a set of eight Java benchmarks, we find that only two of them are array dominated, the rest having between 40% to 75% of the heap footprint allocated to objects, the vast majority of which are small. Consider a B-Tree node from the B-tree Java benchmark: Uncompressed, it’s memory layout looks like (a) below. Evaluation.

Cache 61

Cache Benchmarking Hardware Java 61

VoltDB

JUNE 1, 2017

An opening scene involving a traffic jam of Viking boats and a musical number (“Love Can’t Afjord to wait”). Hardware Optimizers” want to get the maximum utilization out of hardware. Private Clouds made of commodity hardware are perceived as the logical solution to this problem. Vikings fight zombies.

Hardware 56

Hardware Latency Virtualization Cloud 56