Engineering the Super Bowl ft. Catherine Johnson, Hydrolix

This isn't your typical "how-to" on scaling. Most companies crumble when traffic spikes. On the latest episode, Catherine Johnson, VP of Global Solutions Engineering at Hydrolix, pulls back the curtain on what it actually takes to manage 1.4 petabytes of data per day during the highest-stakes event in broadcasting: the Super Bowl.

Forget the marketing fluff. Here is the strategic framework for surviving massive scale and the uncomfortable truths about why your current "high-availability" plan is likely insufficient.

1. The Myth of Perfect Simulation

The first uncomfortable truth: You cannot truly test at scale. For the 2025 Super Bowl, Hydrolix wasn't just dealing with volume; they were dealing with variety. During the playoffs, request paths shifted entirely from what they had observed in the regular season. If you rely on synthetic data to validate your architecture, you are preparing for a version of reality that won't exist.

• The Pivot: Instead of aiming for perfect simulation, aim for Data Architecture Agility.

• Tactical Reality: In the second playoff game, regex (regular expression) matching nearly tanked performance. At petabyte scale, regex is computationally expensive. Hydrolix shifted to exact-match indexing for mission-critical paths to maintain 0.5-second query response times.

2. Why Auto-Scaling is a Trap for Critical Events

Engineers love the "magic" of auto-scaling. But when you are broadcasting to 50 million viewers, waiting for a Kubernetes node to spin up is a liability.

• Pre-Scaling is Strategy, Not Waste: Hydrolix scaled to peak capacity before the game.

• The Constraint: They hit the ceiling of what a single AWS region could provide in terms of compute.

• The Framework: They moved to a multi-region deployment not just for redundancy, but because the physical hardware required for that much real-time processing simply didn't exist in one zip code.

3. The "Field CTO" Mindset: Bridging the Gap

Technical solutions fail when they aren't mapped to business outcomes. In the "War Room," the goal wasn't just keeping the database alive; it was ensuring the Fox Sports executives had a dashboard that spoke their language.

Non-Obvious Solutions Engineering Skills:

• Empathy as Accuracy: Empathy isn't "being nice." It is the accurate and correct understanding of a customer's problem. If you don't understand their business, you can't solve their technical debt.

• The Power of the Pause: Technical people jump to "how" too fast. When a customer asks for a feature, ask "Why?" Three layers deep. Often, the complex query they want is a band-aid for a simpler question they haven't articulated.

• Mapping to Revenue: Every technical requirement must map to a business requirement. If it doesn't, it's just expensive noise.

4. Radical Transparency as a Sales Tool

In B2B SaaS, the pressure to say "Yes" to every RFP is immense. Johnson argues the opposite: Honesty is the ultimate trust builder.

• The Qualification Truth: If a customer’s query patterns don't fit Hydrolix’s specialized architecture, they walk away.

• Trusted Advisor vs. Vendor: By telling a prospect "We aren't a fit, talk to this competitor instead," you secure a professional reputation that lasts decades. In the data world, your reputation is the only thing that doesn't depreciate.

Strategic Summary: The Super Bowl Playbook

Final Perspective: The Architecture of Truth

The common denominator in Catherine Johnson’s experience—from the farming industry to the 50-million-viewer pressure cooker of the Super Bowl—is that scale is a magnifying glass. It doesn't create problems; it simply exposes the cracks you chose to ignore during the "happy path" of development.

In the world of B2B SaaS, "Real-Time" and "Scalable" are often used as cheap marketing buzzwords. But true operational excellence requires a shift in mindset:

• Engineering is Political: A 0.5-second query time isn't just a technical achievement; it's the political capital that allows an executive to make a $10M decision with confidence.

• Predictability > Performance: High-speed systems are useless if they are brittle. It is better to have a system that is consistently "fast enough" under extreme load than one that is lightning-fast until it hits 1.1 petabytes and collapses.

• The SE is the Conscience: The most valuable Solutions Engineer in the room isn't the one who knows every feature. It's the one who has the spine to tell a customer, "Your data architecture is the problem, not the tool."

Ultimately, surviving a high-traffic event isn't about the code you write on the day of the game. It’s about the rigor of the simulations you ran six months prior and the radical honesty you maintained with your customer when the results weren't what they wanted to hear.