Arctic Wolf

Project Context

Arctic Wolf Networks offers cybersecurity services to businesses, including Raw Log Search, a product currently grappling with usability issues. Our project aims to enhance customer satisfaction and retention for Raw Log Search by investigating design solutions that improve the user experience.

What is a Raw Log Search?

A raw log is an unprocessed file with event records, encompassing data like errors, access logs, and debugging info. The Raw Log Search tool helps customers sift through this data using keywords or preset examples, enhancing query accuracy

“Raw Log Search allows customers to look at their unprocessed data — none of this data is enriched so it’s a giant text file.”

Marcus Russell

Senior Product Owner @ Arctic Wolf

Problem Definition

Crafting a Problem Statement

The Raw Log Search is plagued by a number of issues, including poor usability, a lack of user knowledge concerning the most efficient search methods, and the need to access multiple products. These factors all contribute to a significant level of friction, which ultimately hinders the usability of the Raw Log Search and comprises the overall user experience.

Problem areas in the Raw Log Search

Raw log search has a low usage rate, not many customers use this tool

The Raw log search is not easily accessibly since its hidden within multiple tabs

High costs incur due to inefficient researches

“How might we make the Raw Log search more intuitive to use?”

Project Goal

The project aims to make the search process intuitive, allowing users to easily find the information they need. Opportunities for this project include improving search functionality, making the interface more user-friendly, and providing educational resources to help users understand how to perform efficient searches.

Research

Current Design - How would you initiate your search?

The key elements of the existing user interface for the Raw Log Search tool are outlined below, along with an explanation of how the search operates currently while highlighting usability issues.

1. Search Filters: The “log sources”, “time range” and “examples” are effective ways to narrow down the research results in this tool. Log sources refer to different databases that the user wants to search from, while the time range selection enables users to specify the desired search period. The examples dropdown provides pre-defined search query examples for popular searches.

2. Case Sensitivity: The current design has auto checked case sensitivity. This decision help reduce search run time, but increased user frustration because they often missed this box.

3. Histogram: This graph represents the frequency of the search queries over time. Specifically, this histogram plays a critical role as an investigative tool utilized by internal teams. The export button enables users to export the queries into an Excel file.

4. Search: In order to reset a search query, users should select the "New Search" button. To execute a search, the "Search" button must be selected.

5. Support: The "Ask your CST about this view" is a hyperlink that directs users to the relevant help documentation for further assistance.

Audit of Competitor Research

By analyzing the raw log data search of Arctic Wolf’s competitors, it helped the team gain valuable insights into user interactions, and patterns used by industry leader, Rapid7. This audit helped can help identify strengths and weaknesses in Arctic Wolf raw log interface, helping areas of improvement.

Hello

Rapid7's Raw Log Search Interface, a competing product...

Rapid7’s Search Ribbon components

Hello

Hello

Competitor Analysis

To enhance the usability and functionality of Raw Log Search, a competition analysis was undertaken. The analysis focused on evaluating two log search products, Crowdstrike and Rapid7, as competitors. The findings of this research highlighted that Arctic Wolf's Raw Log Search was relatively less developed compared to the industry-leading competitors.

Hello

Hello

Ideating & Wireframing

Low-fi Wireframes Iterations

After my team specified the key features that needed to be included on the sign-up page, we developed three distinct design ideas to address the problem space, based on our research findings.

Hello

Wireframe 1

In contrast to the original design, this iteration features a user-friendly search ribbon that is organized cohesively in a single row. Unlike before, the search ribbon is no longer spread across multiple rows. There is still an opportunity to provide explanations for certain technical filters and guide users on how to effectively utilize them.

Hello

Hello

Wireframe 2

This exploration concentrated on strategies to integrate diverse technical and non-technical filters. It became clear that having a single-row search ribbon might not be advantageous if it leads to cramming and cluttering of the ribbon due to the multitude of elements and filtering components.

Hello

Hello

Design Decisions

Zighra is a company that specializes in behavioral biometrics and AI-driven solutions to enhance privacy and security in digital interactions. My team at Zighra was focused on building a decentralized content creation platform called Spur to explore this technology to such platforms to enhance user security and privacy.

Hello

Hello

This navigation is consistency with other page navigation on this product

Hello

More prominent as it is positioned at the bottom of the search input.

Hello

Enables precise navigation to the desired results.

Hello

Provide guidance on conducting searches more efficiently for faster results.

Hello

Support text to help understand what each input requires

Hello

Clearly visible primary and secondary actions are distinguishable.

Hello

Users have the option to hide the histogram if it's not necessary, which helps declutter the interface.

Hello

Final Design

Hello

Hello

Project Outcome

The revised Raw Log Search design was developed in early 2023. This project proved to be highly valuable as it provided significant learning experiences in terms of working with design systems and successfully executing an end-to-end project.  