We conducted a series of three two-hour workshops using digital whiteboarding and telecommunication tools over the course of a week. The data we collected helped us identify three main focus areas and will be used to prioritize enhancements to the OpenShift logging tools.

What Is an Empathy Workshop?

Empathy workshops are a design-thinking and user-research method designed by the Red Hat User Experience Design (UXD) team to identify and deeply understand customer pain points, goals, and use cases. This method combines the best parts of focus groups (collaboration and different points of view, for example) with gamification techniques to build an engaging and structured group exercise.

Workshops consist of these four activities:

• Warm-up: Break the ice with a brief game. 
• Empathize: Discover and explore problem areas with activities designed to capture impressions and reveal concerns.
• Define: Collaborate to describe the most important problems and define points of focus.
• Ideate: Brainstorm ways to address the identified issues using improvisation techniques.

Before COVID sent us into quarantine mode, these activities took place in person using the tried-and-true tools of the design-thinking trade: sticky notes and markers. Since COVID, we modified this method slightly to approximate the experience in videoconference and digital whiteboard tools. While it is always great to see people in person, the workshop structure and outcomes have fared well in the age of working from home and will continue to be a valuable tool for the UXD team. 

Virtual empathy workshops swap paper and markers for pixels and keyboards. Our workshop participants added their thoughts about OpenShift logs in real-time, with the help of online collaboration tools like Miro.

Log Jams

The main purpose of this workshop series was to learn what bothers our users the most about their current logging tools. In the first few activities, we encouraged our participants to dredge up past frustrations so that we could find trends among them. Across our three sessions, participants noted dozens of frustrations, most of which could be grouped into several categories:

• *Setup:* A lack of sensible default settings and limited guidance make setup frustrating.
• *Multicluster logging:* Many logging stacks do not  have a good way to direct logs from multiple sources to a single place.
• *Querying:* Query language syntax is hard to understand and some users do not want to take the time to learn it.
• *Dashboards:* User-created dashboards are not shareable and can create too much clutter.
• *Sharing:* Users currently have to send screenshots screenshots because there is no way for non-platform users to view logs.
• *Security:* Sensitive logs must be manually removed before data can be shared.
• *Scaling:* Logging tools slow down significantly with more clients.
• *Inspecting:* Once relevant objects are located, viewing their details is inconvenient.
• *Correlation:* It is hard to make connections between logs, alerts, and object status to solve problems.

What Is  Next?

In the last section of each of our workshops, we spent time brainstorming and voting on solutions to some of these problems. Though the specific topics of each session were different, we were able to determine three main areas of focus that will provide the most value to our users. 

Going forward, the improvements we make to OpenShift logging tools will focus on answering:

1. How might we provide better out-of-the-box configurations?
2. How might we help users find logs that are relevant for their current problems?
3. How might we easily pass log data we’ve found to the people who need it?

Our goal is to create a simple, integrated logging solution that will enable a majority of users to accomplish their goals with minimal configuration and provide options to expand to other tools for further customization. 

If you would like to learn more about our plans, or if you have suggestions for how to address these issues, email us or share your thoughts in our OpenShift Container Platform survey. 

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