Percona

AUGUST 22, 2023

Some of the most important elements include: No single point of failure (SPOF): You must eliminate any SPOF in the database environment, including any potential for an SPOF in physical or virtual hardware. Load balancing: Traffic is distributed across multiple servers to prevent any one component from becoming overloaded.

Availability 98

Availability Hardware Open Source Database 98

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

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. It depends upon your application workload and its business logic.

Metrics 130

Metrics Monitoring Latency Cache 130

Alex Russell

MARCH 6, 2021

Hardware Past As Performance Prologue. Using a global ASP as a benchmark can further mislead thanks to the distorting effect of ultra-high-end prices rising while shipment volumes stagnate. But the hardware future is not evenly distributed, and web workloads aren't heavily parallel. Today, either method returns a similar answer.

Performance 127

Performance Network Mobile Metrics 127

Brendan Gregg

SEPTEMBER 25, 2021

Since instances of both CentOS and Ubuntu were running in parallel, I could collect flame graphs at the same time (same time-of-day traffic mix) and compare them side by side. As a Xen guest, this profile was gathered using perf(1) and the kernel's software cpu-clock soft interrupts, not the hardware NMI. But I'm not completely sure.

Speed 103

Speed Java AWS Virtualization 103

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. Where VoltDB fits.

Hardware 56

Hardware Latency Virtualization Cloud 56

KeyCDN

AUGUST 15, 2019

Before you begin tuning your website or application, you must first figure out which metrics matter most to your users and establish some achievable benchmarks. Just because everything works perfectly during production testing doesn’t mean that will be the case when your website is flooded with traffic.

Testing Tools 55

Testing Tools Best Practices Performance Testing Testing 55

Alex Russell

OCTOBER 22, 2017

Budgets are scaled to a benchmark network & device. Deciding what benchmark to use for a performance budget is crucial. Contended, over-subscribed cells can make “fast” networks brutally slow, transport variance can make TCP much less efficient , and the bursty nature of web traffic works against us.

Performance 74

Performance Network Benchmarking Mobile 74

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. Where VoltDB fits.

Hardware 40

Hardware Latency Virtualization Cloud 40

Percona

SEPTEMBER 1, 2023

This results in expedited query execution, reduced resource utilization, and more efficient exploitation of the available hardware resources. This not only enhances performance but also enables you to make more efficient use of your hardware resources, potentially resulting in cost savings on infrastructure.

Tuning 52

Tuning Database Performance Hardware 52

The Morning Paper

MAY 14, 2019

Last time around we looked at the DeathStarBench suite of microservices-based benchmark applications and learned that microservices systems can be especially latency sensitive, and that hotspots can propagate through a microservices architecture in interesting ways. When available, it can use hardware level performance counters.

Big Data 45

Big Data Cloud Performance Hardware 45

Brendan Gregg

SEPTEMBER 25, 2021

Since instances of both CentOS and Ubuntu were running in parallel, I could collect flame graphs at the same time (same time-of-day traffic mix) and compare them side by side. As a Xen guest, this profile was gathered using perf(1) and the kernel's software cpu-clock soft interrupts, not the hardware NMI.

Speed 52

Speed Java AWS Virtualization 52

Percona

JULY 1, 2023

Understanding DBaaS DBaaS cloud services allow users to use databases without configuring physical hardware and infrastructure or installing software. Doing extensive benchmarks will be the subject of a future blog post. In any case, you should benchmark both RDS MySQL and Aurora before taking the decision to migrate.

AWS 52

AWS Database Serverless Storage 52

Brendan Gregg

SEPTEMBER 25, 2021

Since instances of both CentOS and Ubuntu were running in parallel, I could collect flame graphs at the same time (same time-of-day traffic mix) and compare them side by side. As a Xen guest, this profile was gathered using perf(1) and the kernel's software cpu-clock soft interrupts, not the hardware NMI. But I'm not completely sure.

Speed 40

Speed Java AWS Virtualization 40

Smashing Magazine

JANUARY 6, 2020

For Mac OS, we can use Network Link Conditioner , for Windows Windows Traffic Shaper , for Linux netem , and for FreeBSD dummynet. On the other hand, we have hardware constraints on memory and CPU due to JavaScript parsing times (we’ll talk about them in detail later). Lighthouse , a performance auditing tool integrated into DevTools.

Performance 112

Performance Cache Servers Network 112

Smashing Magazine

JANUARY 11, 2021

CrUX generates an overview of performance distributions over time, with traffic collected from Google Chrome users. But account for the different types and usage behaviors of your customers (which Tobias Baldauf called cadence and cohorts ), along with bot traffic and seasonality effects. You can create your own on Chrome UX Dashboard.

Performance 145

Performance Cache Media Metrics 145