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Arctic Wolf Networks - Log source management design
Arctic Wolf Networks - Log source management systems design.
Arctic Wolf security analysts solution provided SMEs with 24×7 monitoring of their digital networks, endpoints, and cloud environments to help them detect, respond, and recover from modern cyber security attacks. 
Lead UX/UI designer
I was the lead UX/UI designer for two main products and the digital on boarding experience at Arctic Wolf Networks. 

I led the design of a new log source management system, redesigned the cloud solution customer portal view and redesigned new client on boarding. Conducted requirements gathering research with stakeholders in California and Canada, competitive product research, service blueprint mapping, ideation, wire framing, wire flow diagraming, usability testing and customer discovery interviews were all methods used to continuously improve the security analyst's work flow and end customers web portal experience.

Collaborated daily with in-house security analysts and software developers to evaluate and improve the current work flow friction points.
Main areas of responsibility:​​​​​​​
• Systems thinking, software work flow analysis and end to end design of a new log source management interface.

• Redesigned the customer facing cloud portal.

• Champion of using best design practices and sharing my learnings.

• Service Blueprint Mapping, design of the end to end digital on boarding experience.

• Usability Testing.

• Hired first UX co-op and mentored Jr. developers.

• Lo-fi sketching and Hi-fi mockups, wire-flow design, rapid prototyping.

• Interaction design, working in tight communication loops with software development team and introduced front end developers to the user testing and customer discovery process. 
Project summary
Arctic Wolf Networks is a security operations company that combines a cloud platform with a concierge Security Analyst as a service model to monitor a customers network.

On this project I applied new research methods such as Jobs to be done (JBTD) and Service blueprint mapping in order to understand complex big data systems and how security analyst identify anomalies in fragmented network data. I had to learn how data is structured at the root level in raw log format and understand why unstructured data is such a challenge to work with. 

I was able to job shadow and conduct daily and weekly observation studies with the security analysts, capture friction points in their work flow, establish deep empathy into how they perform their role in order to design solutions to their most pressing challenges. 
The challenge
User needs:

Security analyst use multiple software applications and the terminal/command line interface to perform health check scans on various customer networks, the security scanning work flow caused a tremendous amount of application context switching that slowed down their ability to quickly scan many customer networks within a given work day.
They desired UX/UI improvements that would allow them to reduce the amount of mental context switching they performed when scanning customer network data. 

Business requirements:

The business of offering a concierge Security Analyst as a service model wasn't scalable unless an analyst could scan many networks faster then traditional vulnerability scanning methods.
The solution
Pain points the new experience solved:

The Security Analyst's mental context switching between ~ 4 to 8 different computer monitors and constantly opening and closing various security intelligence software interfaces meant that we needed to create our own in-house centralized system in order to call APIs from multiple sources into one user interface that reduced the amount of context switching costs and simplified the analyst workflow. 
Results 
Lessons learned:

Big data is complex but understandable when you spend enough time immersed in user discovery analyzing work flows.  

Big data allows user experience designers to conceptualize and leverage machine learning algorithms as a new tool for solving interaction design challenges. 

I also conceptualized a new machine learning algorithm for a future use case that would reduce notification noise by training a model to understand the common signatures of each customers network data.

This would give the analyst a higher degree of signal to noise ratio confidence when making critical decisions if an anomaly is worth drilling into further or not.


Reflections:
Arctic Wolf Networks secures $200M in series E funding at a valuation of $1.3 Billion.
source: https://arcticwolf.com/resources/press-releases/arctic-wolf-secures-200m-in-series-e-funding-at-a-valuation-of-1-3-billion
Arctic Wolf Networks - Log source management design
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Arctic Wolf Networks - Log source management design

1
31
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Published: