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#PrimeDayFail2016: A Cautionary Tale for Upstart Ecommerce

Ricardo Belmar

While not religious observances in the traditional sense, commercial and sales holidays like Black Friday and Cyber Monday are now celebrated gatherings that bring the masses together – albeit in the name of bargain hunting. Last year, Amazon added another consumer event to the calendar with the announcement of Prime Day, a 24-hour sale on the massive ecommerce site that ended up generating $415 million in sales for the retail behemoth – more than the company's reported revenues for that year's Black Friday.

Prime Day, which is designed to give subscribers of the company's Amazon Prime membership exclusive access to discounted merchandise, illustrates perfectly the retail landscape's transformation into a multi-channel arena. Brick-and-mortar commerce isn't dead, but online shopping has been embraced by the masses and is now the go-to avenue for purchasing both specialty items and everyday wares.

While Prime shoppers enjoy the bargains, few may realize that the success of such massive events hinges on network and application performance. While Amazon regularly operates on such a large scale that their internal networks are usually primed to handle major traffic ebbs and flows, even the world's largest online marketplace can't guarantee smooth user experience during an epic traffic deluge like the one prompted by Prime Day.

#PrimeDayFail2016

This struggle to deliver on Quality of Experience (QoE) expectations was on display for all the Internet to see when the #PrimeDayFail2016 hashtag began trending in the early hours of July 12. Shoppers around the world were unable to check out with their purchases for almost an hour when the event kicked off, which was a major hit to customer satisfaction as well as the company's public perception.

Despite this hiccup – which turned out to be an unanticipated glitch on the Amazon site – Prime Day 2016 still generated massive sales for the company and is again on track to have exceeded figures from this year's Black Friday once all of the receipts are tallied. But for a smaller ecommerce site without the capital or business reach of a giant like Amazon, such a lapse in service could be devastating.

Not All Retailers Have the Clout to Bounce Back

Website or application downtime, for instance – no matter if it's only for a few minutes – can be enough of a deterrent for shoppers to leave the site and not return. Such events are often attributed to spikes in traffic that aren't properly managed, resulting in network degradation that grinds site performance to a halt.

Network infrastructures that are ill-equipped to manage complex applications cause network slowdowns and worse – shoppers to lose patience and move on. To protect against this, retailers must consider Application Performance Management. This will ensure that business-critical applications take priority on the network during high-traffic periods. With consistently reliable app performance, retailers can easily deliver the fast-paced shopping experiences that power flash sales.

The same unified management philosophy also applies to a retailer's internal store network. From the standpoint of inventory management and delivery, for instance, companies need to be sure that there is a clear line of uninterrupted communication from the warehouse to the website.

Even the latest digital in-store experiences are powered by the network and rely on optimal application performance. Experiences such as digital fitting rooms, tablets used by store associates to display rich media product info and mobile POS checkout are just a few applications that create heavy traffic loads on network infrastructure. All of these require proper performance management or shoppers will lose patience waiting for screens to refresh and abandon a purchase. Even 5 seconds waiting for a tablet to display information feels like an eternity to the shopper.

Although a large portion of commerce has moved to the web, taking away the interpersonal aspect of bargain hunting, customers still want to be treated like people, not just numbers. A unified approach to application and network management can enable a high QoE and Quality of Service (QoS) to deliver the personalization shoppers now expect, which will inevitably translate into increased revenue for the retailer.

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The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

#PrimeDayFail2016: A Cautionary Tale for Upstart Ecommerce

Ricardo Belmar

While not religious observances in the traditional sense, commercial and sales holidays like Black Friday and Cyber Monday are now celebrated gatherings that bring the masses together – albeit in the name of bargain hunting. Last year, Amazon added another consumer event to the calendar with the announcement of Prime Day, a 24-hour sale on the massive ecommerce site that ended up generating $415 million in sales for the retail behemoth – more than the company's reported revenues for that year's Black Friday.

Prime Day, which is designed to give subscribers of the company's Amazon Prime membership exclusive access to discounted merchandise, illustrates perfectly the retail landscape's transformation into a multi-channel arena. Brick-and-mortar commerce isn't dead, but online shopping has been embraced by the masses and is now the go-to avenue for purchasing both specialty items and everyday wares.

While Prime shoppers enjoy the bargains, few may realize that the success of such massive events hinges on network and application performance. While Amazon regularly operates on such a large scale that their internal networks are usually primed to handle major traffic ebbs and flows, even the world's largest online marketplace can't guarantee smooth user experience during an epic traffic deluge like the one prompted by Prime Day.

#PrimeDayFail2016

This struggle to deliver on Quality of Experience (QoE) expectations was on display for all the Internet to see when the #PrimeDayFail2016 hashtag began trending in the early hours of July 12. Shoppers around the world were unable to check out with their purchases for almost an hour when the event kicked off, which was a major hit to customer satisfaction as well as the company's public perception.

Despite this hiccup – which turned out to be an unanticipated glitch on the Amazon site – Prime Day 2016 still generated massive sales for the company and is again on track to have exceeded figures from this year's Black Friday once all of the receipts are tallied. But for a smaller ecommerce site without the capital or business reach of a giant like Amazon, such a lapse in service could be devastating.

Not All Retailers Have the Clout to Bounce Back

Website or application downtime, for instance – no matter if it's only for a few minutes – can be enough of a deterrent for shoppers to leave the site and not return. Such events are often attributed to spikes in traffic that aren't properly managed, resulting in network degradation that grinds site performance to a halt.

Network infrastructures that are ill-equipped to manage complex applications cause network slowdowns and worse – shoppers to lose patience and move on. To protect against this, retailers must consider Application Performance Management. This will ensure that business-critical applications take priority on the network during high-traffic periods. With consistently reliable app performance, retailers can easily deliver the fast-paced shopping experiences that power flash sales.

The same unified management philosophy also applies to a retailer's internal store network. From the standpoint of inventory management and delivery, for instance, companies need to be sure that there is a clear line of uninterrupted communication from the warehouse to the website.

Even the latest digital in-store experiences are powered by the network and rely on optimal application performance. Experiences such as digital fitting rooms, tablets used by store associates to display rich media product info and mobile POS checkout are just a few applications that create heavy traffic loads on network infrastructure. All of these require proper performance management or shoppers will lose patience waiting for screens to refresh and abandon a purchase. Even 5 seconds waiting for a tablet to display information feels like an eternity to the shopper.

Although a large portion of commerce has moved to the web, taking away the interpersonal aspect of bargain hunting, customers still want to be treated like people, not just numbers. A unified approach to application and network management can enable a high QoE and Quality of Service (QoS) to deliver the personalization shoppers now expect, which will inevitably translate into increased revenue for the retailer.

Hot Topics

The Latest

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...