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How Ecommerce Businesses Fared During the Last Holiday Season

The 2019 State of E-Commerce Infrastructure Report, from Webscale, analyzes findings from a comprehensive survey of more than 450 ecommerce professionals regarding how their online stores performed during the 2019 holiday season.


Some key insights from the report include:

Revenue and Traffic

While only 34.9% of online merchants expected more than 2X their average monthly site traffic during the holiday season, 41.8% actually ended up at 2X or higher. These numbers become more significant given that more than 29% of online merchants generate almost 50% of their annual revenue during the fourth quarter.

Downtime

"Many are still struggling with downtime and cyberthreats"

24.3% of merchants experienced expensive downtime in excess of 5 minutes on Black Friday/Cyber Monday 2019, while 6.6% of storefronts crashed for more than 30 minutes. In our pre-holiday survey though, only 18.6% of merchants said that they were worried about impending downtime during the holiday shopping season.

Slowness

A pre-holiday survey revealed that 37.2% of online merchants were worried about slow page loads. However, 49.7% of them experienced page load times in excess of 3 seconds, 22.2% had page load times over 5 seconds, and 4.8% had intolerable page load speeds over 9 seconds.

Security issues

Last year, 21% of merchants admitted to experiencing cybersecurity-related incidents, ranging from DDoS attacks to credit card theft attempts, during the Cyber Weekend. This year, the number increased to 32.6%, a significant percentage of the hundreds of thousands of ecommerce websites operating globally.

Hosting Challenges

12.9% of online merchants cited cyberthreats as their #1 challenge on Black Friday/Cyber Monday, 9.4% of merchants were plagued by downtime worries, and 8.9% stated site slowdowns were their biggest concern. Over 18% of respondents reported heavy struggles with all three challenges.

"While we saw some improvements this year, indicating that ecommerce merchants are investing more seriously in their site performance, many are still struggling with downtime and cyberthreats, finding it difficult to manage the infrastructure themselves, or working with providers who lack the depth of cloud expertise to deliver a superior user experience,” said Sonal Puri, CEO of Webscale.

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One of the earliest lessons I learned from architecting throughput-heavy services is that simplicity wins repeatedly: fewer moving parts, loosely coupled execution (fewer synchronous calls), and precise timing metering. You want data and decisions to travel the shortest possible path. The goal is to build a system where every strategy and each line of code (contention is the key metric) complements the decision trees ...

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The numbers back this urgency up. A recent Zapier survey shows that 92% of enterprises now treat AI as a top priority. Leaders want it, and teams are clamoring for it. But if you look closer at the operations of these companies, you see a different picture. The rollout is slow. The results are often delayed. There's a disconnect between what leaders want and what their technical infrastructure can handle ...

Kyndryl's 2025 Readiness Report revealed that 61% of global business and technology leaders report increasing pressure from boards and regulators to prove AI's ROI. As the technology evolves and expectations continue to rise, leaders are compelled to generate and prove impact before scaling further. This will lead to a decisive turning point in 2026 ...

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If you work with AI, you know this story. A model performs during testing, looks great in early reviews, works perfectly in production and then slowly loses relevance after operating for a while. Everything on the surface looks perfect — pipelines are running, predictions or recommendations are error-free, data quality checks show green; yet outcomes don't meet the ground reality. This pattern often repeats across enterprise AI programs. Take for example, a mid-sized retail banking and wealth-management firm with heavy investments in AI-powered risk analytics, fraud detection and personalized credit-decisioning systems. The model worked well for a while, but transactions increased, so did false positives by 18% ...

Basic uptime is no longer the gold standard. By 2026, network monitoring must do more than report status, it must explain performance in a hybrid-first world. Networks are no longer just static support systems; they are agile, distributed architectures that sit at the very heart of the customer experience and the business outcomes ... The following five trends represent the new standard for network health, providing a blueprint for teams to move from reactive troubleshooting to a proactive, integrated future ...

APMdigest's Predictions Series concludes with 2026 AI Predictions — industry experts offer predictions on how AI and related technologies will evolve and impact business in 2026. Part 5, the final installment, covers AI's impacts on IT teams ...

How Ecommerce Businesses Fared During the Last Holiday Season

The 2019 State of E-Commerce Infrastructure Report, from Webscale, analyzes findings from a comprehensive survey of more than 450 ecommerce professionals regarding how their online stores performed during the 2019 holiday season.


Some key insights from the report include:

Revenue and Traffic

While only 34.9% of online merchants expected more than 2X their average monthly site traffic during the holiday season, 41.8% actually ended up at 2X or higher. These numbers become more significant given that more than 29% of online merchants generate almost 50% of their annual revenue during the fourth quarter.

Downtime

"Many are still struggling with downtime and cyberthreats"

24.3% of merchants experienced expensive downtime in excess of 5 minutes on Black Friday/Cyber Monday 2019, while 6.6% of storefronts crashed for more than 30 minutes. In our pre-holiday survey though, only 18.6% of merchants said that they were worried about impending downtime during the holiday shopping season.

Slowness

A pre-holiday survey revealed that 37.2% of online merchants were worried about slow page loads. However, 49.7% of them experienced page load times in excess of 3 seconds, 22.2% had page load times over 5 seconds, and 4.8% had intolerable page load speeds over 9 seconds.

Security issues

Last year, 21% of merchants admitted to experiencing cybersecurity-related incidents, ranging from DDoS attacks to credit card theft attempts, during the Cyber Weekend. This year, the number increased to 32.6%, a significant percentage of the hundreds of thousands of ecommerce websites operating globally.

Hosting Challenges

12.9% of online merchants cited cyberthreats as their #1 challenge on Black Friday/Cyber Monday, 9.4% of merchants were plagued by downtime worries, and 8.9% stated site slowdowns were their biggest concern. Over 18% of respondents reported heavy struggles with all three challenges.

"While we saw some improvements this year, indicating that ecommerce merchants are investing more seriously in their site performance, many are still struggling with downtime and cyberthreats, finding it difficult to manage the infrastructure themselves, or working with providers who lack the depth of cloud expertise to deliver a superior user experience,” said Sonal Puri, CEO of Webscale.

The Latest

Most organizations approach OpenTelemetry as a collection of individual tools they need to assemble from scratch. This view misses the bigger picture. OpenTelemetry is a complete telemetry framework with composable components that address specific problems at different stages of organizational maturity. You start with what you need today and adopt additional pieces as your observability practices evolve ...

One of the earliest lessons I learned from architecting throughput-heavy services is that simplicity wins repeatedly: fewer moving parts, loosely coupled execution (fewer synchronous calls), and precise timing metering. You want data and decisions to travel the shortest possible path. The goal is to build a system where every strategy and each line of code (contention is the key metric) complements the decision trees ...

As discussions around AI "autonomous coworkers" accelerate, many industry projections assume that agents will soon operate alongside human staff in making decisions, taking actions, and managing tasks with minimal oversight. But a growing number of critics (including some of the developers building these systems) argue that the industry still has a long way to go to be able to treat AI agents like fully trusted teammates ...

Enterprise AI has entered a transformational phase where, according to Digitate's recently released survey, Agentic AI and the Future of Enterprise IT, companies are moving beyond traditional automation toward Agentic AI systems designed to reason, adapt, and collaborate alongside human teams ...

The numbers back this urgency up. A recent Zapier survey shows that 92% of enterprises now treat AI as a top priority. Leaders want it, and teams are clamoring for it. But if you look closer at the operations of these companies, you see a different picture. The rollout is slow. The results are often delayed. There's a disconnect between what leaders want and what their technical infrastructure can handle ...

Kyndryl's 2025 Readiness Report revealed that 61% of global business and technology leaders report increasing pressure from boards and regulators to prove AI's ROI. As the technology evolves and expectations continue to rise, leaders are compelled to generate and prove impact before scaling further. This will lead to a decisive turning point in 2026 ...

Cloudflare's disruption illustrates how quickly a single provider's issue cascades into widespread exposure. Many organizations don't fully realize how tightly their systems are coupled to thirdparty services, or how quickly availability and security concerns align when those services falter ... You can't avoid these dependencies, but you can understand them ...

If you work with AI, you know this story. A model performs during testing, looks great in early reviews, works perfectly in production and then slowly loses relevance after operating for a while. Everything on the surface looks perfect — pipelines are running, predictions or recommendations are error-free, data quality checks show green; yet outcomes don't meet the ground reality. This pattern often repeats across enterprise AI programs. Take for example, a mid-sized retail banking and wealth-management firm with heavy investments in AI-powered risk analytics, fraud detection and personalized credit-decisioning systems. The model worked well for a while, but transactions increased, so did false positives by 18% ...

Basic uptime is no longer the gold standard. By 2026, network monitoring must do more than report status, it must explain performance in a hybrid-first world. Networks are no longer just static support systems; they are agile, distributed architectures that sit at the very heart of the customer experience and the business outcomes ... The following five trends represent the new standard for network health, providing a blueprint for teams to move from reactive troubleshooting to a proactive, integrated future ...

APMdigest's Predictions Series concludes with 2026 AI Predictions — industry experts offer predictions on how AI and related technologies will evolve and impact business in 2026. Part 5, the final installment, covers AI's impacts on IT teams ...