Apache JMeter vs. Datadog

JMeter is well suited for Java applications where the user can script the scenario once and make changes to accommodate for as many numbers of users for load test execution. The image and selection of any files or exporting files scenario is handled well.

It is less appropriate to test Ajax applications where it is required to script click per use.

Incentivized

Where Datadog is good: - Real-time Visibility During Incidents: During high-severity incidents, Datadog dashboards, coupled with real-time logging and APM traces, provide immediate insight into system health and enable fast triage. For example, we’ve used trace ID correlation between logs and APM to quickly identify downstream service failures due to network degradation during a major outage. - Service Ownership at Scale: With over 50 engineering teams, providing self-service monitoring is essential. We use Datadog monitors, SLO dashboards, and templates so teams can track their own service health without reinventing the wheel. Tagging and RBAC features help us scope data access appropriately. Where Datadog can improve: While Datadog’s logging capabilities are powerful, storing all application logs in Datadog can become cost-prohibitive at high volumes.

Incentivized

• Easy of use - in generate load like HTTP requests, and processing/analyzing the responses. No coding is necessary at the basic level, just need to understand load testing and the infrastructure being tested.
• Automatic management of things like cookies to help with session state support - so you don't specifically have to worry about it or handle it
• Lots of testing/configuration options to suit your needs in making the right load generation (sampling requests), and analyzing the results, including any pre and post processing of the results first. Things like the Beanshell/BSF pre/post processors, response assertion, regular expression extractor, XPath extractor, CSV data set config
• There is a JMeter cloud service called BlazeMeter that I think would be useful for those that need to scale up high load without provisioning their own systems. I've not personally tried it though, but I recently attended a meetup presentation that highlighted nice useful features that BlazeMeter provides. One should evaluate the service if they are considering JMeter and need to expand beyond existing hardware resources.

• Create Dashboards as per application, environments, and Custom metrics in one panel.
• Log aggregation, one-stop Application monitoring tools for the whole infrastructure.
• Playbooks, SLA definition, success and error quotas, request visualizations.
• DB monitoring, Serverless stack monitoring.
• Alerting of Production incidents so we can quickly resolve the issues on time.

Incentivized

• Jmeter requires many tweaks with respect to its configuration file and thread properties. users need to edit theses files themselves. There could be some interface where we can edit this fields.
• Jmeter cannot handle more threads and hangs up when we increase the number of threads. This causes lot of inconvenience. In these situations, user can be notified that such change would be lead to slow performance so that user can do as required. The same appears when we try to view huge files on graph listener.
• Jmeter should optimize the read and write access to output csv since it acts as overhead to the I/O performance. This affects our test results for the application which we are testing.

• Alert windows cause lag in notifications (e.g. if the alert window is X errors in 1 hour, we won't get alerted until the end of the 1 hour range)
• I would appreciate more supportive examples for how to filter and view metrics in the explorer
• I would like a more clear interface for metrics that are missing in a time frame, rather than only showing tags/etc. for metrics that were collected within the currently viewed time frame

Incentivized

Price, Wiki and user sharing. Having access to the information provided by the developers and other open source providers is key for me. The ability to share information and get answers directly is very important to success in software testing. And the price of this product currently is amazing. Too many companies charge way too much money for products that are far behind in their value and pertinence

I can jump right into a new test plan and start building from scratch. The natural progression from test plan to thread group and then designing the basic format of the process is very streamlined and smooth. With only slight modifications I can build out a very complex model from a very basic beginning.

Datadog's user interface is quite friendly and easy to navigate. With menus clearly categorized, and ability to bookmark important dashboards, one can easily find what they're looking for. For dashboards, ability to move and resize visualizations and group them, is really helpful to organize dashboards. Automatic suggestions from Datadog for important visualizations based on the metrics and logs would provide another level of ease of use.

Incentivized

I have been using JMeter for the last year. By using this tool, you can make sure the system will work under varied loads. It helps us to simulate real time scenarios by creating required virtual users and make sure the application will work under load. Perform load, stress, and stability testing using JMeter.

Incentivized

The support team usually gets it right. We did have a rather complicate issue setting up monitoring on a domain controller. However, they are usually responsive and helpful over chat. The downside would be I don’t think they have any phone support. If that is important to you this might not be a good fit.

Incentivized

I have used LoadRunner and Silkperformer, and so far Jmeter turns out be the easiest to use of all these. While each of them have their own ROI, Jmeter can be picked by anyone in hours and start testing within a day. While with other tools, we need to get license, install them (takes a while) and setup tests and firewalls, etc.

We are still trying other products, but people still like Datadog. After setting up a dashboard, it's great for monitoring instances on Datadog. Also, the DevOps team had a good time setting up Datadog. It means Datadog was way easier to set up compared to those others.

Incentivized

• Good ROI on improving the performance of the application.
• Finding issues in the performance.
• Benchmark the performance results.
• CON: Need skillset to create and maintain the scripts in Java.
• Scripts are reusable and it is executed by any user.
• Need Client and Server setup to execute the scripts.

Incentivized

• Saved us (time & money) from developing our own monitoring utilities that would pale in comparison
• Alerts allow us to remedy issues before our customers even know about them
• Tracking resource usage over time allows us to better plan for future needs, before it becomes a pain-point.

Incentivized