Performance Tuning in a Remote World

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During these turbulent times, one of the main challenges we are all facing is how to cope with working at home, rather than going to the office and interacting with our colleagues face to face.

It is somewhat mitigated by using the closest means of communication we have to f2f meetings: video conferencing tools, such as Zoom, Teams, Skype and Google Hangouts.

Even with these tools, several aspects remain quite challenging:

  • What about sharing our work with others?
  • What about analyzing our data with our colleagues?

Many domain-specific services exist regardless of the current COVID-19 pandemic situation, for offline and online sharing of some of our day-to-day work.

The following is a report outlining the challenges employees and organizations face when working remotely:

Source: https://lp.buffer.com/state-of-remote-work-2020

Seth Godin articulates it well, “The challenge of communication isn’t to never miscommunicate, it’s to cut down the time between the interaction and the realization that the communication didn’t get through. Because the sooner we know we’re not connecting, the sooner we can fix it.”

In the performance tuning domain in particular, it is essential that those who work on experiment management and performance tuning workflows have the ability to share their work with their colleagues and external advisors. This allows them to co-manage an experiment and keep it transparent to the rest of their organization. This is a key aspect of the Concertio Experiment Management System.

We recognized this growing challenge of collaborating remotely in the performance tuning domain. We have invested therefore, in providing the necessary capabilities and turning our existing Optimizer Studio product into an experiment management system, with collaboration features natively integrated to best fit this need.

The following is an example of how Concertio shares its own demo experiment with customers, and how other teams can share experiments with others:

As seen in the graph above, experiment projects are often shared with multiple people. As such, the graph above allows for them to watch the samples as they’re gathered in real-time, analyze the results of the experiments, and define their own filters (coming soon!), in order to make their own observations and tag the experiments they wish.

Users can also examine and update the experiment definition based on other users’ versions and can run their own experiments from where their colleagues left off. Additionally, there are share/invite/team features (that we are all familiar with from other software-as-a-service solutions), which were missing in our experimentation and performance tuning domain. Here is an example:

When working remotely, these features are crucial for productivity, and so we are giving them for free as a part of our SaaS platform! 

When adopted, this platform shows each employee’s productivity and provides the necessary transparency, in order to save everyone’s time – fewer sync meetings, shorter yet more fruitful discussions, easier collaboration with management and external work-force, etc.

I believe that this is the future of experimentation management, and it starts with performance tuning experimentation as the first step.

You can give it a try with our free community edition!

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Seven Productivity Tips for Performance Engineering Teams

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