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Top 5 Causes of Performance Issues During Online Holiday Shopping Season

Mehdi Daoudi

With Black Friday and Cyber Monday just weeks away, Catchpoint has identified the top five technical items most likely to cause web or mobile shopping sites to perform poorly.

When an online retail site is unavailable on a big shopping day, it is essentially the same as shutting the doors of a physical store

Every Black Friday-Cyber Monday weekend in the last decade has seen at least one major online retailer with web or mobile site outages or slowdowns. Memories of last year’s Black Friday problems, and Amazon’s Prime Day missteps this summer, should remind retailers that no company, big or small, is immune to interruptions or slowdowns in its sites’ digital experience.

Online retailers can learn from the mistakes of the past to optimally prepare and best position themselves for a smooth kick-off to the holidays.

The following elements are the most likely to cause slow load times or outages in the upcoming season:

1. Third Parties

These are site elements hosted by outside companies and beyond the direct control of the main site. One sluggish third-party component can slow down an entire web page. Example: in 2016 a high-end home goods retailer experienced very slow page load times intermittently on Black Friday due to problems with a third-party photo display service.

2. Regional View

If an online retailer monitors page load times only using national averages, it could be missing local or statewide performance problems. Example: in 2016 a major retailer experienced problems on its desktop site due to an ad tech provider, ultimately leading to ongoing site blackouts in Phoenix, starting early in the long holiday weekend.

3. Critical APIs

APIs are fundamental components of e-commerce sites, often supporting customer-facing, revenue-generating applications. Like third party services, popular APIs can come under major strain during peak traffic periods. If an API supporting payment options on a site breaks, an abandoned shopping cart will be the likely result.

4. Page Weight

One of the easiest ways to ensure faster load times is to make certain a site’s page weight (amount of data loaded into a shopper’s browser) isn’t too large. This is a technique large and small retailers often employ during peak traffic days, usually by eliminating excess images or graphics.

5. Server Scalability

The Amazon Prime Day outage was reported to be the simple result of overloaded servers. Load testing internal servers is one of the most straightforward, simple things one can do, as well as having additional servers on standby.

When an online retail site is unavailable on a big shopping day, it is essentially the same as shutting the doors of a physical store. And when your page load time slows, that’s the same as forcing a customer to stand in a long checkout line.

It’s important to remember that comprehensive monitoring from the end-user perspective is the definitive way to gain visibility into all the performance-impacting elements in the delivery chain, including those beyond one’s own firewall.

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Top 5 Causes of Performance Issues During Online Holiday Shopping Season

Mehdi Daoudi

With Black Friday and Cyber Monday just weeks away, Catchpoint has identified the top five technical items most likely to cause web or mobile shopping sites to perform poorly.

When an online retail site is unavailable on a big shopping day, it is essentially the same as shutting the doors of a physical store

Every Black Friday-Cyber Monday weekend in the last decade has seen at least one major online retailer with web or mobile site outages or slowdowns. Memories of last year’s Black Friday problems, and Amazon’s Prime Day missteps this summer, should remind retailers that no company, big or small, is immune to interruptions or slowdowns in its sites’ digital experience.

Online retailers can learn from the mistakes of the past to optimally prepare and best position themselves for a smooth kick-off to the holidays.

The following elements are the most likely to cause slow load times or outages in the upcoming season:

1. Third Parties

These are site elements hosted by outside companies and beyond the direct control of the main site. One sluggish third-party component can slow down an entire web page. Example: in 2016 a high-end home goods retailer experienced very slow page load times intermittently on Black Friday due to problems with a third-party photo display service.

2. Regional View

If an online retailer monitors page load times only using national averages, it could be missing local or statewide performance problems. Example: in 2016 a major retailer experienced problems on its desktop site due to an ad tech provider, ultimately leading to ongoing site blackouts in Phoenix, starting early in the long holiday weekend.

3. Critical APIs

APIs are fundamental components of e-commerce sites, often supporting customer-facing, revenue-generating applications. Like third party services, popular APIs can come under major strain during peak traffic periods. If an API supporting payment options on a site breaks, an abandoned shopping cart will be the likely result.

4. Page Weight

One of the easiest ways to ensure faster load times is to make certain a site’s page weight (amount of data loaded into a shopper’s browser) isn’t too large. This is a technique large and small retailers often employ during peak traffic days, usually by eliminating excess images or graphics.

5. Server Scalability

The Amazon Prime Day outage was reported to be the simple result of overloaded servers. Load testing internal servers is one of the most straightforward, simple things one can do, as well as having additional servers on standby.

When an online retail site is unavailable on a big shopping day, it is essentially the same as shutting the doors of a physical store. And when your page load time slows, that’s the same as forcing a customer to stand in a long checkout line.

It’s important to remember that comprehensive monitoring from the end-user perspective is the definitive way to gain visibility into all the performance-impacting elements in the delivery chain, including those beyond one’s own firewall.

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As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...