Catchpoint
2025 - 2026
Empowering Customers with full visibility of their Internet Stack
Designing a mobile experience that helps users discover new music, explore playlists, and connect with artists through a simple and engaging interface.
Overview
Project under NDA
The Internet Stack Map is an advanced observability solution that provides an interactive, end-to-end view of IT Teams’ critical services. By mapping connections across internal systems and external providers, the Internet Stack Map helps IT teams instantly identify upstream and downstream dependencies during service disruptions and outages accelerating root-cause analysis and drastrically minimizes downtime.
The Impact
The Internet Stack Map transformed how IT and Network Operations teams triage incidents across hybrid environments. By pairing critical service maps directly with live internet health data, this new solution replaced tedious manual correlation with a single, scannable tool. Interactive nodes surface deep telemetry on hover and click, enabling engineers to instantly distinguish between internal infrastructure failures and external outages eliminating inter-team finger-pointing and dramatically speeding up root-cause analysis.
Additionally, the Internet Stack Map served a broader strategic purpose for Catchpoint: driving product-led growth/adoption and platform stickiness. By transforming dense, multi-provider network telemetry into a clean, intuitive visual map, the Internet Stack Map reduced onboarding friction for enterprise clients, lowered customer support inquiries related to complex telemetry, and expanded platform usage from specialized network engineers to broader IT leadership.
Problem
Diagnosing internet dependencies felt unnecessarily complex
IT and Operations teams struggle to diagnose complex internet outage paths across hybrid infrastructure, third-party CDNs, and SaaS vendors. Legacy telemetry views present data in dense, fragmented tables that require manual correlation, leading to high cognitive load, and prolonged mean time to diagnosis (MTTD) & Mean time to resolution (MTTR).
Research
Looking beyond the numbers
To better understand where friction appeared while identifying and diagnosing internet outages, I conducted customer interviews with Site Reliability Engineers, Network engineers, general IT practitioners who regularly diagnose and resolve Site outages to better understand their overall workflows and pain points while resolving outages.
Conducting this research helped identify key insights that impacted the product strategy and overall business goal for the solution.
Competitive Analysis
Beyond gathering user and stakeholder insights, we audited direct and adjacent SaaS competitors to map their strengths and key experience gaps. This research revealed critical industry pain points—specifically around visual clutter and slow triage workflows—allowing us to design a tool that directly addressed unmet user needs.
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User Needs
Business Goals
Hypothesis
To guide the design with clear intent, we established a central hypothesis around how SREs and IT Ops teams manage complex internet infrastructure during critical incidents.
Hypothesis
SREs and Network Engineers managing multi-vendor internet stacks struggle to quickly pinpoint whether a service disruption originates from internal infrastructure or an external provider when relying on fragmented, tabular telemetry.
Proposed Solution
By unifying service dependency mapping and real-time internet path telemetry into an interactive visual topology, we can reduce cognitive load, empower teams to instantly isolate outage root causes, and significantly cut down resolution times while improving overall platform adoption.
Ideation
Designing for clarity and confidence within complex data
User Flows
Low Fidelity Iteration
MVP Design
User Testing
Does the design work as intended?
Test Objectives
Test the ease of use and navigation of the Internet Stack Map
Test the overall workflow and how our tool integrates with their monitoring workflow
Observe any friction, frustration, or hesitation within user interactions
Gather any additional information around the data SREs use to monitor their sites
Test Conclusions
Through user testing our MVP design we learned the stack map’s usability could be improved specifically when trying to build the map itself and while trying to navigate the map
The design does not scale well when working with large maps with a high volume of layers and services
The size/format of both layers and services is cumbersome and does not provide additional benefit to users’ overall workflow
