Artillery vs Storm.dev

Overview

Storm.dev

Stacks1

Followers0

Votes0

GitHub Stars10

Forks1

Artillery

Stacks11

Followers11

Votes0

GitHub Stars8.8K

Forks545

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An open source load testing tool

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Detailed Comparison

Storm.dev	Artillery
Monitor your web resource status, get notifications in real time, load test on your web app, Endpoint Health services and Dynamic DNS You just have to install the storm client on your servers and throw away the access key, you will no longer need the shell, do everything from our dashboard. You can extend the node agent at will by creating customized plugins, or use our constantly evolving archive. You can run any command on your node, receive data, view it in graphs and receive notifications in real time. You can create concatenate commands by creating WORKFLOW without writing a line of code.	It is a modern, open-source, powerful & easy-to-use performance testing toolkit. Use it to ship scalable applications that stay performant & resilient under high load. It prioritizes developer productivity and happiness and follows the “batteries-included” philosophy.
Load Test web application; Host monitoring; Run Host Command; Concatenate commands workflow; Endpoint health check; Dynamic DNS; DNS checker	Planet-scale performance testing; Millions of requests per second; Multiple geographical regions; Load testing; Smoke testing
Statistics
GitHub Stars 10	GitHub Stars 8.8K
GitHub Forks 1	GitHub Forks 545
Stacks 1	Stacks 11
Followers 0	Followers 11
Votes 0	Votes 0
Integrations
Linux macOS Windows	Amazon VPC AWS IAM AWS Fargate

What are some alternatives to Storm.dev, Artillery?

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Kibana

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Prometheus

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Nagios

Nagios is a host/service/network monitoring program written in C and released under the GNU General Public License.

Netdata

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Zabbix

Zabbix is a mature and effortless enterprise-class open source monitoring solution for network monitoring and application monitoring of millions of metrics.

k6

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Sensu

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Locust

Locust is an easy-to-use, distributed, user load testing tool. Intended for load testing web sites (or other systems) and figuring out how many concurrent users a system can handle.