In the first 90 days of any new mission or assignment, I always ask my eCommerce counterparts, engineering leads, QA teams, and existing SRE teams one crucial question: “How do you watch the shop?” (And no, I’m not referring to Shopify.) The responses I get are varied:
“Here’s our SLO dashboard; we’re at xx%—don’t worry about it.”
“It’s in our backlog.”
But here’s the kicker: Enterprises and eCommerce businesses operate in a hybrid environment. You’re dealing with middleware interfacing with your ERP, cloud functions, edge functions, and platforms like Shopify—all at once. And get this: more than 50% of your store runs on third-party systems, often without your full awareness.
Take Shopify, for example. Its core platform is loaded with features, webhooks, and APIs, but its true power lies in the expansive ecosystem surrounding it. Giants like Klaviyo work together in a dynamic, unregulated symphony—a harmonious interplay that drives value, until sometimes, the balance falters.
On Black Friday, Klaviyo reported that from 9–10 AM ET alone, over 420 million messages were sent, with a staggering 1.3 million orders processed at peak between noon and 1 PM ET.
and Shopify:
The shopping frenzy peaked at 12:01pm EST on Friday when sales reached a dizzying $4.6 million per minute.
Now, imagine if a traffic surge that typically spans five minutes suddenly condenses into 30 seconds. Suddenly, your SLO isn’t just about your custom software; it has to account for Klaviyo’s performance, your fraud detection systems, and a host of other third-party services.
This layered complexity is exactly where traditional SRE teams often hit a wall. They either struggle to adapt or get frustrated by the sheer number of moving parts. And while uptime is essential, user experience observability—tracing why a customer bounces—is rarely a standard SRE metric. In today’s environment, our SLOs need to be far more holistic.
A note for my Product leads, Investor friends and leaders
Losing revenue and tracking tickets for what happened last holiday is no fun, you need answers and how we cannot repeat our failures in slow motion. In certain companies, I was able to track hundreds of thousands of dollars to what felt like recoverable losses due to lack of will and investment in this area - it certainly is not your <Insert team name here>'s problem.
This seems a 3rd party problem not ours
Resilient systems are not built on others roadmaps or tickets
That’s where traceability steps in. You need to know exactly why a user left:
Was it because your privacy vendor failed to deliver last-visit preferences, leaving your API hanging?
Or did your fraud vendor, caught up in a DDoS attack, broadcast their status publicly which you forgot to notice, causing your backend to falter?
One answer is Distributed tracing - by injecting custom headers like x-usersessionid and x-requesttraceid, I’ve followed countless user journeys across multiple systems. I recall one instance where my function was lightning-fast, Shopify performed just okay, but Avalara lagged—Quantum Metrics confirmed it: a customer left. It’s challenging, abstract, and incredibly tough to instrument—but it’s the reality of eCommerce observability.
The traditional solution might be to have a manual team “watch” these services. However, manual observation, alerting, and response are useful when systems are disconnected but quickly start showing wear - they still have a place today. Consider wrapping your third-party requests through your own API gateway—or using a product like APIdeck. This approach gives you complete visibility into the intricate interplay of your shop’s ecosystem.
Over the years, I’ve built a personal stack that’s helped me navigate these challenges:
Alerts:
User Experience Alerts: Tools like Quantum Metrics (User Experience Analytics) monitor anomalies—traffic dips, conversion drops, spikes in third-party errors—and trigger custom alerts when my “secret sauce” events (think AB tests gone awry) deviate from the norm.
Stack Alerts: Aggregated in DataDog (Full-Stack Monitoring & Alerting), these alerts keep me informed about slow functions, API delays, and other performance hiccups.
Cloud alerts - Host cloud systems and traces - a call stack that represents who was involved where and how they reacted - how many times a default timeout of 5 seconds has cause outages on a 3rd party that takes 15.
Overnight failures - slow moving, previous day data that somehow did not show up to the party on black friday.
Performance Threshold approach alerts - A true system is battle tested with journey, platform tests performed in advance not as an after thought and a alert as a backup solution.
Seasoned SRE leaders and Platform owners recognize the kinks in the armor and respond.
Team Composition:
eCommerce teams today require a mix of talents—traditional SRE expertise combined with deep knowledge of eCom observability and a custom stack built from years of hands-on experience.
Of course, not everyone sees the picture the same way. I’ve heard responses like:
“I’m not sure what you mean—I understand you, but I don’t think that’s me. I only do features.”
“I focus on infrastructure CI/CD. This might be a different role altogether—maybe check with someone in eCommerce operations or in marketing?”
These reactions highlight an important point: observability isn’t just for one part of the organization. It spans the entire digital ecosystem—from feature development to infrastructure—and if you only concentrate on one aspect, you might miss critical insights about the overall customer journey.
Team culture goes beyond titles and departments
High-volume events (and not just Black Friday) demand proactive measures—a new monitoring setup, regular housekeeping, and an agile strategy to keep up with a constantly evolving eCommerce/Martech stack. Don’t assume that clients, developers, or third parties will always provide the input you need. Instead, take control by routing your requests through systems that let you observe every twist and turn of your digital shop floor.
And here’s a forward-looking note: AI is rapidly transforming observability. We’re already seeing the early stages of distributed agents that far exceed the capabilities of traditional APM tools.
This new breed of observability solutions—dynamic, self-aware, and distributed—will redefine how we monitor and manage complex digital ecosystems. But until that future arrives, remember: you still gotta watch the shop today.
TL;DR:
Tools to Check Out:
• Quantum Metrics (User Experience Analytics): For real-time monitoring of user interactions and anomaly detection.
• DataDog (Full-Stack Monitoring & Alerting): To aggregate and alert on performance metrics across your entire stack.
• API Deck (API Gateway/Third-Party Observability): Wraps third-party requests to give you complete visibility into your shop’s intricate ecosystem.
Current Strategies:
• Embrace distributed tracing to follow user journeys across multiple systems.
• Wrap third-party requests through your own API gateway to maintain control.
• Set up proactive alerts for both user experience and backend performance anomalies.
Looking Ahead:
AI-driven distributed agents—far beyond traditional APM tools—are on the horizon. This new breed of observability solutions will redefine how we monitor and manage complex digital ecosystems. But until that future arrives, you still gotta watch the shop today.
What are your thoughts on these strategies? How are you preparing your stack for the future of eCommerce observability?