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locust VS Commit Together by Github

Compare locust VS Commit Together by Github and see what are their differences

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locust logo locust

An open source load testing tool written in Python.

Commit Together by Github logo Commit Together by Github

Now add co-authors to your commits
  • locust Landing page
    Landing page //
    2021-10-11
  • Commit Together by Github Landing page
    Landing page //
    2022-11-04

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.

Commit Together by Github features and specs

  • Enhanced Collaboration
    Commit Together allows multiple authors to be credited in a single commit, which fosters a more collaborative environment and ensures everyone involved receives recognition for their contributions.
  • Improved Code Review Process
    With multiple authors clearly listed, reviewers can better understand who contributed to which parts of the code, facilitating more directed questions and discussions.
  • Accountability
    By attributing every change to the respective author, teams can easily track who made specific changes, which helps in accountability and understanding the history of a project.
  • Efficiency in Pair Programming
    When pair programming, both developers can be credited for their combined effort, streamlining the process of sharing code ownership during collaborative sessions.

Possible disadvantages of Commit Together by Github

  • Complex Commit History
    Having multiple authors for a single commit may lead to a more complex commit history, making it harder to pinpoint individual contributions over time.
  • Potential Workflow Conflicts
    Teams that are used to single-author commits may experience workflow conflicts or require adjustments in practices to accommodate multi-author contributions.
  • Initial Setup Overhead
    Learners and new users might face a learning curve or require additional setup to understand and correctly implement the multi-author commit feature.
  • Tooling Compatibility
    Some third-party tools and extensions might not fully support or display multi-author commits, leading to inconsistencies in those environments.

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.

locust videos

Locust review - GTA Online guides

More videos:

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

Commit Together by Github videos

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Category Popularity

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Monitoring Tools
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Developer Tools
0 0%
100% 100
Website Testing
100 100%
0% 0
Productivity
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User comments

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Social recommendations and mentions

Based on our record, locust seems to be a lot more popular than Commit Together by Github. While we know about 65 links to locust, we've tracked only 1 mention of Commit Together by Github. 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.

locust mentions (65)

  • 15 Common Kubernetes Pitfalls & Challenges
    Regularly review your cluster's utilization to check whether it's still suitable for your workloads. Test autoscaling rules by using a load-testing tool like Locust to direct excess traffic to your cluster. This lets you spot problems earlier, ensuring your Pods will scale seamlessly when real traffic arrives. - Source: dev.to / 9 months ago
  • Small-Scale Chaos Testing: The Missing Step Before Production
    Locust: While primarily a load testing tool, it can be used to simulate user behavior under stress. - Source: dev.to / 10 months ago
  • Log Spikes? Noย Sweat: How Top DevOps Teams Tame Bursty Workloads
    But you donโ€™t have to operate at Netflixโ€™s scale to benefit from the same mindset. Effective teams simulate log floods during load tests, which push traffic through staging environments while tracking how ingestion, indexing, and alerting respond to the increased load. Tools like Grafanaโ€™s k6 and Locust can simulate thousands of requests per second, while synthetic log generators mimic bursty error scenarios. - Source: dev.to / about 1 year ago
  • Serving 200M requests per day with a CGI-bin
    I mean honestly - the "classic" Apache model of throwing things into the www root is very strong for rapid development. Hot code reloading is sometimes finicky, you can end up with unexpected hidden state and lose sanity over a stupid heisenbug. Trust me. IMO you don't need to compensate for bad configs if you're using a proper staging environment and push-button deployments (which is good practice regardless of... - Source: Hacker News / about 1 year ago
  • 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 year ago
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Commit Together by Github mentions (1)

  • Ask HN: Do you rewrite pull requests?
    There is "Co-authored-by" which is supported on GitHub [1] and seems appropriate if the maintainer is basing the solution on someone's code. [1] https://github.blog/2018-01-29-commit-together-with-co-authors/. - Source: Hacker News / about 4 years ago

What are some alternatives?

When comparing locust and Commit Together by Github, you can also consider the following products

Apache JMeter - Apache JMeterโ„ข.

Refined GitHub - Browser extension that makes GitHub cleaner & more powerful

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

GitHub for Mobile - The worldโ€™s development platform, in your pocket

AT Internet - Transform your data into action with our powerful and flexible digital analytics solution.

GitHub for Atom - Git and GitHub integration right inside Atom