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Another Black Friday, Another eCommerce Meltdown

Michelle McLean

Black Friday. Retailers know it's coming every year, and still – every year – someone has a spectacular failure. This year Macy's gets top billing – asking customers to wait to shop. Since 500 milliseconds of web delay is estimated to cost 5% of revenue, how much can we guess Macy's lost by asking EVERY shopper, for hours, to wait to shop? It's clearly in the millions of dollars. And how many of those who clicked over to Nordstrom's or Kohl's in frustration will just keep shopping on those other sites?



 
So what did Macy's get wrong? Scaling infrastructure for big traffic increases is fairly easy across most technology areas. Organizations know how to scale WAN links, network infrastructure, and web servers. So what did Macy's miss? Likely, the database.

"You have handle 5x to 15x your usual traffic on Black Friday," says Craig Thayer, CTO of Sazze, parent company to numerous eCommerce websites including Black Friday FM. "Turns out the database is the hardest part of the infrastructure to scale fast, because you have to also make application changes. You change the code, iterate, test, rinse and repeat."
 
Often, when you can't reach a site or app during a busy time, it's the database that has hit a wall. Organizations of all sizes these days are rushing to take advantage of additional capacity in modern databases. Microsoft is pushing its SQL Server 2016 launch, and the open source world is embracing MySQL 5.6. Both modern databases offer more capacity and better failover, aimed at improving application uptime.

The challenge for organizations, as Sazze's Thayer points out, is that applications have to know how to talk to those databases. That takes time – and can't be done in rapid response in the middle of a Macy's meltdown during Black Friday. It's got to be done in advance.
 
Organizations have a couple choices for how to adopt these databases. They can recode their apps – teaching those apps how to send some traffic to additional database servers to spread out the load. Or they can use technology like they have for their web server farms – load balancing technology – in front of their databases and have that software redirect the database load automatically. The benefit of using database load balancing software is that it avoids the application recoding – and subsequent "rinse and repeat" cycles that Sazze's Thayer is keen to avoid. So that option can often be implemented faster than recoding an app and provides additional benefits such as seamless failover.

Black Friday often serves as a warning for the rest of the December online shopping spree. The hope is that companies that experienced – or watched others have – a Black Friday meltdown can scale their infrastructure in time to be ready for that holiday shopping traffic.

Michelle McLean is VP of Marketing at ScaleArc.

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Another Black Friday, Another eCommerce Meltdown

Michelle McLean

Black Friday. Retailers know it's coming every year, and still – every year – someone has a spectacular failure. This year Macy's gets top billing – asking customers to wait to shop. Since 500 milliseconds of web delay is estimated to cost 5% of revenue, how much can we guess Macy's lost by asking EVERY shopper, for hours, to wait to shop? It's clearly in the millions of dollars. And how many of those who clicked over to Nordstrom's or Kohl's in frustration will just keep shopping on those other sites?



 
So what did Macy's get wrong? Scaling infrastructure for big traffic increases is fairly easy across most technology areas. Organizations know how to scale WAN links, network infrastructure, and web servers. So what did Macy's miss? Likely, the database.

"You have handle 5x to 15x your usual traffic on Black Friday," says Craig Thayer, CTO of Sazze, parent company to numerous eCommerce websites including Black Friday FM. "Turns out the database is the hardest part of the infrastructure to scale fast, because you have to also make application changes. You change the code, iterate, test, rinse and repeat."
 
Often, when you can't reach a site or app during a busy time, it's the database that has hit a wall. Organizations of all sizes these days are rushing to take advantage of additional capacity in modern databases. Microsoft is pushing its SQL Server 2016 launch, and the open source world is embracing MySQL 5.6. Both modern databases offer more capacity and better failover, aimed at improving application uptime.

The challenge for organizations, as Sazze's Thayer points out, is that applications have to know how to talk to those databases. That takes time – and can't be done in rapid response in the middle of a Macy's meltdown during Black Friday. It's got to be done in advance.
 
Organizations have a couple choices for how to adopt these databases. They can recode their apps – teaching those apps how to send some traffic to additional database servers to spread out the load. Or they can use technology like they have for their web server farms – load balancing technology – in front of their databases and have that software redirect the database load automatically. The benefit of using database load balancing software is that it avoids the application recoding – and subsequent "rinse and repeat" cycles that Sazze's Thayer is keen to avoid. So that option can often be implemented faster than recoding an app and provides additional benefits such as seamless failover.

Black Friday often serves as a warning for the rest of the December online shopping spree. The hope is that companies that experienced – or watched others have – a Black Friday meltdown can scale their infrastructure in time to be ready for that holiday shopping traffic.

Michelle McLean is VP of Marketing at ScaleArc.

Hot Topics

The Latest

A new study by the IBM Institute for Business Value reveals that enterprises are expected to significantly scale AI-enabled workflows, many driven by agentic AI, relying on them for improved decision making and automation. The AI Projects to Profits study revealed that respondents expect AI-enabled workflows to grow from 3% today to 25% by the end of 2025. With 70% of surveyed executives indicating that agentic AI is important to their organization's future, the research suggests that many organizations are actively encouraging experimentation ...

Respondents predict that agentic AI will play an increasingly prominent role in their interactions with technology vendors over the coming years and are positive about the benefits it will bring, according to The Race to an Agentic Future: How Agentic AI Will Transform Customer Experience, a report from Cisco ...

A new wave of tariffs, some exceeding 100%, is sending shockwaves across the technology industry. Enterprises are grappling with sudden, dramatic cost increases that threaten to disrupt carefully planned budgets, sourcing strategies, and deployment plans. For CIOs and CTOs, this isn't just an economic setback; it's a wake-up call. The era of predictable cloud pricing and stable global supply chains is over ...

As artificial intelligence (AI) adoption gains momentum, network readiness is emerging as a critical success factor. AI workloads generate unpredictable bursts of traffic, demanding high-speed connectivity that is low latency and lossless. AI adoption will require upgrades and optimizations in data center networks and wide-area networks (WANs). This is prompting enterprise IT teams to rethink, re-architect, and upgrade their data center and WANs to support AI-driven operations ...

Artificial intelligence (AI) is core to observability practices, with some 41% of respondents reporting AI adoption as a core driver of observability, according to the State of Observability for Financial Services and Insurance report from New Relic ...

Application performance monitoring (APM) is a game of catching up — building dashboards, setting thresholds, tuning alerts, and manually correlating metrics to root causes. In the early days, this straightforward model worked as applications were simpler, stacks more predictable, and telemetry was manageable. Today, the landscape has shifted, and more assertive tools are needed ...

Cloud adoption has accelerated, but backup strategies haven't always kept pace. Many organizations continue to rely on backup strategies that were either lifted directly from on-prem environments or use cloud-native tools in limited, DR-focused ways ... Eon uncovered a handful of critical gaps regarding how organizations approach cloud backup. To capture these prevailing winds, we gathered insights from 150+ IT and cloud leaders at the recent Google Cloud Next conference, which we've compiled into the 2025 State of Cloud Data Backup ...

Private clouds are no longer playing catch-up, and public clouds are no longer the default as organizations recalibrate their cloud strategies, according to the Private Cloud Outlook 2025 report from Broadcom. More than half (53%) of survey respondents say private cloud is their top priority for deploying new workloads over the next three years, while 69% are considering workload repatriation from public to private cloud, with one-third having already done so ...

As organizations chase productivity gains from generative AI, teams are overwhelmingly focused on improving delivery speed (45%) over enhancing software quality (13%), according to the Quality Transformation Report from Tricentis ...

Back in March of this year ... MongoDB's stock price took a serious tumble ... In my opinion, it reflects a deeper structural issue in enterprise software economics altogether — vendor lock-in ...