Ngrinder vs Storm.dev
Overview
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CLI (Node.js)
Manual
Detailed Comparison
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 platform for stress tests that enables you to execute script creation, test execution, monitoring, and result report generator simultaneously. It offers easy ways to conduct stress tests by eliminating inconveniences and providing integrated environments. |
Load Test web application; Host monitoring; Run Host Command;
Concatenate commands workflow; Endpoint health check; Dynamic DNS; DNS checker | Use Jython script to create test scenario and generate stress in JVM using multiple agents;
Extend tests with custom libraries(jar, py). It's unlimited practically;
Provide web-based interface for project management, monitoring, result management and report management;
Run multiple tests concurrently. Assign the pre-installed multiple agents to maximize each agent's utilization;
Deploy agents on multiple network regions. Execute tests on various network locations;
Embed Subversion to manage scripts;
Allow to monitor the state of agents generating stress and target machines receiving stress;
Proven solution which is used to test huge systems having more than 100 million users in NHN |
Statistics | |
GitHub Stars 10 | GitHub Stars 2.1K |
GitHub Forks 1 | GitHub Forks 482 |
Stacks 1 | Stacks 6 |
Followers 0 | Followers 2 |
Votes 0 | Votes 0 |
Integrations | |
| No integrations available | |
What are some alternatives to Storm.dev, Ngrinder?
Grafana
Grafana is a general purpose dashboard and graph composer. It's focused on providing rich ways to visualize time series metrics, mainly though graphs but supports other ways to visualize data through a pluggable panel architecture. It currently has rich support for for Graphite, InfluxDB and OpenTSDB. But supports other data sources via plugins.
Kibana
Kibana is an open source (Apache Licensed), browser based analytics and search dashboard for Elasticsearch. Kibana is a snap to setup and start using. Kibana strives to be easy to get started with, while also being flexible and powerful, just like Elasticsearch.
Prometheus
Prometheus is a systems and service monitoring system. It collects metrics from configured targets at given intervals, evaluates rule expressions, displays the results, and can trigger alerts if some condition is observed to be true.
Nagios
Nagios is a host/service/network monitoring program written in C and released under the GNU General Public License.
Netdata
Netdata collects metrics per second & presents them in low-latency dashboards. It's designed to run on all of your physical & virtual servers, cloud deployments, Kubernetes clusters & edge/IoT devices, to monitor systems, containers & apps
Zabbix
Zabbix is a mature and effortless enterprise-class open source monitoring solution for network monitoring and application monitoring of millions of metrics.
k6
It is a developer centric open source load testing tool for testing the performance of your backend infrastructure. It’s built with Go and JavaScript to integrate well into your development workflow.
Sensu
Sensu is the future-proof solution for multi-cloud monitoring at scale. The Sensu monitoring event pipeline empowers businesses to automate their monitoring workflows and gain deep visibility into their multi-cloud environments.
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.
Graphite
Graphite does two things: 1) Store numeric time-series data and 2) Render graphs of this data on demand
