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SmartMeter.io VS locust

Compare SmartMeter.io VS locust and see what are their differences

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SmartMeter.io logo SmartMeter.io

Performance Testing with Enterprise-Level Features with a familiar jMeter interface

locust logo locust

An open source load testing tool written in Python.
  • SmartMeter.io Landing page
    Landing page //
    2023-07-11
  • locust Landing page
    Landing page //
    2021-10-11

SmartMeter.io features and specs

  • High Performance
    SmartMeter.io is designed to handle a large number of users and transactions, which makes it suitable for testing applications with high performance demands.
  • Comprehensive Reporting
    It provides detailed and comprehensive reports that help in analyzing the performance of the application effectively.
  • Easy Integration
    The tool integrates easily with CI/CD pipelines and various development environments, making it convenient for continuous testing processes.
  • User-friendly Interface
    The interface is intuitive and easy to navigate, which reduces the learning curve for new users.
  • Flexibility
    Offers flexibility in test scripting with support for both GUI-based and script-based test creation.

Possible disadvantages of SmartMeter.io

  • Cost
    SmartMeter.io can be relatively expensive compared to some open-source alternatives, which might be a concern for smaller organizations.
  • Resource Intensive
    The tool can be resource-intensive and may require significant hardware resources to run high-volume tests efficiently.
  • Steeper Learning Curve for Advanced Features
    While basic features are easy to use, mastering advanced features and customizations may require additional learning and experience.
  • Limited Community Support
    Compared to some open-source tools with large communities, SmartMeter.io has more limited community resources and forums.

locust features and specs

  • Scalability
    Locust is designed to distribute the load tests across multiple machines, allowing for high scalability and the ability to simulate millions of users.
  • Python-based
    The tool is written in Python, which makes it highly flexible and suitable for those who are familiar with the language. You can write custom test scenarios easily.
  • Web-based UI
    Locust provides a user-friendly web-based interface that makes it easy to monitor and control the test execution in real-time.
  • Real-time monitoring
    During test execution, you get real-time statistics and charts that help in monitoring the performance and load.
  • Open-source
    Being an open-source tool, Locust allows for community contributions and is free to use, which helps in continuous improvement and support from the user base.

Possible disadvantages of locust

  • Setup Complexity
    Initial setup can be somewhat complex, especially for large scale or distributed tests. Requires experience with Python and potentially other infrastructure setups.
  • Resource Intensive
    Locust can be resource-intensive, requiring significant compute resources, particularly when simulating large numbers of users.
  • Steeper Learning Curve
    Despite its flexibility, the requirement to write test scenarios in Python may present a learning curve for users not familiar with programming.
  • Limited Protocol Support
    Primarily designed for HTTP/HTTPS protocols, Locust might not be suitable for load testing applications that use other protocols without additional customization.
  • Dependence on External Libraries
    While the use of Python offers flexibility, it also means that you might need to rely on external libraries and tools, which can introduce dependency management issues.

Analysis of locust

Overall verdict

  • Locust is a powerful and flexible tool for load testing, particularly advantageous for teams familiar with Python. Its scalability and ease of setup make it a strong choice for both small and large projects.

Why this product is good

  • Locust (locust.io) is considered a good tool for load testing due to its easy-to-use, scalable, and distributed nature. Written in Python, it allows developers to write simple or complex test scenarios in the same language. It enables the simulation of millions of users by distributing tasks across multiple machines, making it highly valuable for performance testing of websites and applications. The web-based user interface is another advantage, allowing real-time monitoring of test progress and results.

Recommended for

  • Development teams looking for a scalable load testing tool.
  • Organizations that prefer open-source solutions.
  • Projects requiring custom test scenarios in Python.
  • Teams needing real-time monitoring and distributed testing capabilities.

SmartMeter.io videos

+ Add

How to edit load test settings in SmartMeter.io

More videos:

  • Review - Review công cụ kiểm thử hiệu suất trang web Smartmeter.io

locust videos

+ Add

Locust review - GTA Online guides

More videos:

  • Review - GTA Online: Ocelot Locust Review
  • Review - GTA 5 - DLC Vehicle Customization - Ocelot Locust and Review

Category Popularity

0-100% (relative to SmartMeter.io and locust)

SmartMeter.io

locust

Monitoring Tools
35 35%
Monitoring Tools
65% 65
Website Testing
32 32%
Website Testing
68% 68
Development
100 100%
Development
0% 0
Analytics
0 0%
Analytics
100% 100

User comments

Share your experience with using SmartMeter.io and locust. For example, how are they different and which one is better?
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Social recommendations and mentions

Based on our record, locust seems to be more popular. It has been mentiond 61 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

SmartMeter.io mentions (0)

We have not tracked any mentions of SmartMeter.io yet. Tracking of SmartMeter.io recommendations started around Mar 2021.

locust mentions (61)

  • 3 Types of Chaos Experiments and How To Run Them
    Use load testing tools like JMeter, Gatling, or Locust to simulate demand spikes and verify that your auto-scaling rules work as expected. This will ensure that your system can handle real-world traffic patterns. - Source: dev.to / about 1 month ago
  • Outgrowing Postgres: How to identify scale problems
    Use load testing tools like Apache JMeter, Gatling, or Locust to measure your application's throughput under various loads and compare it to historical data. - Source: dev.to / 4 months ago
  • Five Advanced Techniques to Improve Automated Testing by 50%
    You should also incorporate performance testing into your daily builds to catch performance regressions early. For this, you can use Locust for load testing. You can also implement performance budgets in your CI/CD pipeline. This will allow you to fail builds that don't meet performance criteria, ensuring performance doesn't degrade over time. - Source: dev.to / 5 months ago
  • Why your FastAPI (or Flask) App performs poorly with high loads
    These tests were done on GCP Cloud Run using a single processor, and 512M RAM machine, and we used Locust, an incredible tool (for Python, LoL). - Source: dev.to / 8 months ago
  • How MySQL Tuning Can Dramatically Improve WordPress Performance
    Our test duration was 2 days. To handle this longer testing period, we switched from BlazeMeter (max test duration of 20 minutes) to Locust, an open-source load-testing tool. - Source: dev.to / 11 months ago
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What are some alternatives?

When comparing SmartMeter.io and locust, you can also consider the following products

WebLOAD - WebLOAD - The most flexible and cost effective software for enterprise load, stress and performance testing, integrated with DevOps processes. Click for details

Apache JMeter - Apache JMeter™.

OctoPerf - OctoPerf is a SaaS load testing solution, based on JMeter.

Loader.io - Loader.io is a simple cloud-based load testing service

StresStimulus - Load testing tool for websites and mobile that works with hard-to-test applications.

gatling.io - Gatling is an open-source load testing framework based on Scala, Akka and Netty

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