Dotcom-Montior

NOVEMBER 27, 2018

LoadView, our on-demand, cloud-based load and stress testing platform , takes an outside-in approach to performance testing. Executing an internal test can tell you how well your application or site handles an increase in traffic, but it will never reflect real-world conditions.

Performance Testing 40

Performance Testing Strategy Testing Performance 40

Apica

OCTOBER 29, 2019

Understanding the market and this massive growth in applications, having a modern performance testing platform will ensure you can test streaming, API-based, and XML-based applications including set-top boxes and game stations among other application types in DevOps friendly way. The short answer is that they aren’t.

Performance Testing 40

Performance Testing Testing Performance Software 40

Apica

SEPTEMBER 21, 2020

Application monitoring is one of the highest IT priorities in today’s business. By upgrading to the Apica Synthetic monitoring solution, you gain access to a long list of features legacy tools don’t have, including the following: Proactive monitoring to identify issues before users experience a problem. Preparation.

Monitoring 52

Monitoring Tuning Virtualization Cloud 52

Dynatrace

SEPTEMBER 4, 2020

It’s a free virtual event so I hope you join me. In our recent Performance Clinic Automate Business Level Objective Monitoring with Dynatrace & Keptn I was able to live demo the latest version of the Dynatrace SLI Provider for Keptn which now accepts a Dynatrace dashboard as input as you can see in the following example!

DevOps 244

DevOps Metrics Innovation Azure 244

Dotcom-Montior

JUNE 19, 2017

Today we’ll be reviewing LoadView , an on-demand load-testing platform from Dotcom-Monitor that makes realistic load testing possible without an up-front investment in hardware or software infrastructure. Thanks to cloud-based virtual servers, LoadView can send traffic to your site or application from around the world.

Performance Testing 40

Performance Testing Testing Performance Virtualization 40

Scalegrid

DECEMBER 16, 2019

What’s most impressive is that you’re not compromising performance for cost. We ran performance tests for MongoDB on DigitalOcean vs. AWS vs. Azure and found that DigitalOcean performance was in line with, if not better, on both high throughput and low latency in the deployment. Monitoring Performance.

Azure 187

Azure AWS Latency Database 187

Dynatrace

SEPTEMBER 8, 2020

Additionally, chaos engineering can be used to verify your monitoring. You might create chaos experiments which break single components of a distributed system and want to make sure that your monitoring system informs about such failures (but the system should work either way). to Staging) and re-tested. 3: 5 Steps.

Engineering 139

Engineering Cloud Monitoring Testing 139

Dynatrace

SEPTEMBER 15, 2020

After every experiment run Akamas changes application, runtime, database or cloud configuration based on monitoring data it captured during the previous experiment run. Akamas is an on-premises product and simply needs one virtual machine to get started. Q3: Is Akamas a SaaS offering or on-premise? or do you pull different percentiles?

Performance 180

Performance Java Metrics Cloud 180

Dynatrace

DECEMBER 6, 2022

But, manual steps — such as reviewing test results and addressing production issues resulting from performance, resiliency, security, or functional issues — often hinder these efforts. This approach was presented virtually in the on-demand observability clinic, Getting Started with Observability-Driven DevOps and SRE Automation.

DevOps 212

DevOps Metrics Engineering Speed 212

Dynatrace

MAY 28, 2020

After a new build gets deployed and automated tests executed, SLIs are evaluated against their SLOs and, depending on that result, a build is considered good (promoted) or bad (rolled back). “ Firstly, start by installing the Dynatrace OneAgent on the hosts where you’ll be running your application test. SimpleNodeJsService.

Engineering 188

Engineering Performance Metrics Best Practices 188

Smashing Magazine

OCTOBER 31, 2023

And when discussing the two types of data, we’re actually talking about what is called real-user monitoring , or RUM for short. For example, the data is pretty slow to update, refreshing every 28 days, meaning it is not the same as real-time monitoring. Type 1: Observed Data Observed data is performance as the browser sees it.

Speed 99

Speed Google Website Metrics 99

Testsigma

JULY 3, 2021

But for the uninitiated, on-premise testing is a form of testing where testers perform tests on local machines, systems, or devices set up at an office. On-premise testing comes with a lot of responsibility. If you configure a test environment and run into any errors, those will reflect in your test efficiency.

Cloud 57

Cloud Testing Storage DevOps 57

Apica

MAY 10, 2019

The spread of where consumers want to consume content, at home, at the office, at the gym, on a plane, at any time where there is connectivity, puts significant pressure on the network and performance monitoring teams for streaming brands. Apica’s scale is enterprise-grade.

Testing 40

Testing Performance Social Media Wireless 40

Testsigma

JUNE 26, 2021

Cloud-based: You can run your tests on a secure, scalable cloud that comes with thousands of real devices. Parallel test execution: Tests can be run simultaneously in multiple environments. that you’d like to perform tests on. API testing: You can automate API tests and browser tests simultaneously.

Testing Tools 52

Testing Tools Testing Analytics Mobile 52

Testsigma

JUNE 26, 2021

Larger automation scope: With codeless automation testing, the automation scope is high. Codeless automation testing tools are designed to test multiple apps from the same platform. For instance, you can perform tests on mobile apps (iOS, Android, native, and hybrid), desktop apps, web apps, virtual apps, etc.,

Testing 57

Testing Testing Tools Automotive Scalability 57

Adrian Cockcroft

JUNE 21, 2022

I adopted the language, called the SE Toolkit , which was a C-based interpreter that understood how to directly read all the performance data out of the kernel, and wrote a lot of scripts over the years, including one called virtual_adrian.se Jim also joined the database performance team. that a lot of people used.

Tuning 52

Tuning Benchmarking Engineering C++ 52

Percona

DECEMBER 20, 2018

In this post we will review the most important Linux settings to adjust for performance tuning and optimization of a MySQL database server. We’ll note how some of the Linux parameter settings used OS tuning may vary according to different system types: physical, virtual or cloud. A Look at MyRocks Performance.

Database 40

Database Tuning Performance AWS 40

HammerDB

OCTOBER 12, 2018

monitoring. Download and install HammerDB on a test client system, Like PostgreSQL another 2 socket server is ideal. Error in Virtual User 1: mysqlexec/db server: Table 'mysql.proc' doesn't exist. It will return to the prompt when built – then restart the MySQL instance and run a single test. . # perf special.

Best Practices 40

Best Practices Scalability Performance C++ 40

Smashing Magazine

FEBRUARY 2, 2022

We can code-split virtually any component in our project. An additional way of identifying those bundles is to run a performance test in a browser or use WebPageTest , and check which bundles block the CPU main thread the longest. We can then run code-splitting for bundles that get caught by the performance budget monitor.

Code 91

Code Performance Network Website 91

The Netflix TechBlog

JANUARY 24, 2022

At Netflix the term “performance” usually encompasses both performance metrics (in the strict meaning) and memory metrics, and that’s how we’re using the term here. Why do we run Performance Tests on commits? What are the Performance Tests? Ideally we catch regressions before they even reach the main branch.

Performance 199

Performance Metrics Performance Testing Testing 199

Brendan Gregg

FEBRUARY 9, 2018

To understand the overhead further I'll need to use instruction-level profiling, such as by using perf annotate, and PMC (Performance Monitoring Counter) analysis of the CPU cycles (more on this later). ## 2. virtual (bgregg-c5.9xl-i-xxx) 02/09/2018 _x86_64_ (36 CPU) 05:24:51 PM proc/s cswch/s. Linux 4.14.12-virtual

Performance 75

Performance Benchmarking Cache Tuning 75

Brendan Gregg

FEBRUARY 8, 2018

To understand the overhead further I'll need to use instruction-level profiling, such as by using perf annotate, and PMC (Performance Monitoring Counter) analysis of the CPU cycles (more on this later). ## 2. virtual (bgregg-c5.9xl-i-xxx) 02/09/2018 _x86_64_ (36 CPU) 05:24:51 PM proc/s cswch/s. Linux 4.14.12-virtual

Performance 40

Performance Benchmarking Cache Tuning 40