Skip to main content

Two Words for the Holiday Rush: Adequate Capacity

Scott Hollis

Depending upon your specific industry, the holiday rush can account for 75% – 85% of your total revenue. You cannot be caught unprepared and your systems have to be able to handle the surge in traffic. So how do you make sure your systems are not going to let you down?

Two words, adequate capacity. Capacity is the #1 reason for service degradation or failure.

Start with historical data. What was the load on your systems last year? This will probably give you the best baseline and starting point.

Now estimate how and why that will change this year. Do you have a blockbuster toy? Or are you offering the iPhone 6 at significant discount? Have you launched a massive marketing campaign or is the marketing group planning something new? Whatever it is, understand how that will impact your demand and how long the additional demand can be expected to last. Make sure you provision for it.

Harness the clouds. You certainly do not want to carry excess capacity all year round, just for this one day or a relatively short time period. Reach out for on-demand capacity from a public or private cloud provider. Run synthetic transactions using your APM tools to ensure your infrastructure will not fold under pressure. Use cloud bursting for as long as needed and dial down as you notice decline in demand. As you move your services to and from the cloud, remember, the location of your services should be transparent to the customers.

Unified monitoring tools can manage your services whether they are running on your local infrastructure, on your private cloud or even a third party public cloud. When issues happen (yes – "when" not "if") you can quickly identify the root cause and get a rapid resolution, hopefully well before the customer is impacted.

You want your customers to be able to access your site and more importantly, you want them to be able transact business while they are there. Make it easy for them and less of a headache for you and your organization.

Scott Hollis is Director of Product Marketing for Zenoss.

The Latest

Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...

AI is usually talked about as a software tool, but it also depends heavily on the network behind it. Whether a company is using AI for chatbots, automation, monitoring, analytics, or employee support, all of that information has to move across the network in a reliable and secure way. That means AI is not just an application decision. It is also an infrastructure decision. Before organizations rush into AI, they should ask a simple question: Is our network ready to support it? ...

Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...

Enterprise networks rarely behave the same way for very long. A routing adjustment in one region may unexpectedly alter application performance in another. A cloud migration may introduce hidden dependencies that go unnoticed until an outage occurs. All the while, the network is managed by several different teams, each of whom use different tool sets — and as a result, have different views of the network ... There’s usually an engineer who remembers why traffic fails over a certain way between sites, or which transparent firewall was added where. The problem is that human memory cannot scale alongside enterprise-scale networks ...

Ask an infrastructure team how confident they are in their ability to govern AI, and most will tell you they've got it handled. A recent survey of 406 IT decision-makers and platform engineering leaders found 86% expressing exactly that confidence. Ask the same group whether they have a formal written AI governance policy, and the number drops to 30%, according to Spacelift's Infrastructure Automation Report ...

In MEAN TIME TO INSIGHT Episode 27, Shamus McGillicuddy, EMA VP of Research, Network Infrastructure and Operations, and Parker Hathcock, EMA Research Director covering IT Service/Operations (ServiceOps), discuss observability unification in modern IT operations ... 

Virtual Private Networks became a cornerstone of enterprise security at a time when corporate infrastructure looked very different from today ... For years, this model worked well. But the architecture behind VPNs assumed a centralized corporate environment—one where the network itself was the hub of activity. In a cloud — first world, that assumption no longer holds ...

Website outages get resolved just as fast in August as they do in November. I went looking for the opposite: the summer slowdown everyone assumes is there once the people who fix things are away. It isn't in the data we collected, covering 1.8 million confirmed outages across tens of thousands of websites ...

This year, many of the cloud infrastructure contracts signed in the early days of the AI boom will come up for renewal. As the year goes on, I anticipate we'll see a significant amount of cloud vendor swapouts and multi-cloud adoption, and the reason isn't just GPU depreciation. It's because they're tired of their current cloud providers ...

There's a moment the many observability teams have experienced days into bringing a new service into production: you realize that the vendor's claims of "intelligent" behavior included a large serving of hype. Their dashboards look nice until they don't, the failure modes are a black box, and no one on the team can confidently explain why the system did what it did at 2 am. Agentic AI is about to force every Ops team to relive that moment at web-scale until they start treating these systems as the dependencies they actually are ...

Two Words for the Holiday Rush: Adequate Capacity

Scott Hollis

Depending upon your specific industry, the holiday rush can account for 75% – 85% of your total revenue. You cannot be caught unprepared and your systems have to be able to handle the surge in traffic. So how do you make sure your systems are not going to let you down?

Two words, adequate capacity. Capacity is the #1 reason for service degradation or failure.

Start with historical data. What was the load on your systems last year? This will probably give you the best baseline and starting point.

Now estimate how and why that will change this year. Do you have a blockbuster toy? Or are you offering the iPhone 6 at significant discount? Have you launched a massive marketing campaign or is the marketing group planning something new? Whatever it is, understand how that will impact your demand and how long the additional demand can be expected to last. Make sure you provision for it.

Harness the clouds. You certainly do not want to carry excess capacity all year round, just for this one day or a relatively short time period. Reach out for on-demand capacity from a public or private cloud provider. Run synthetic transactions using your APM tools to ensure your infrastructure will not fold under pressure. Use cloud bursting for as long as needed and dial down as you notice decline in demand. As you move your services to and from the cloud, remember, the location of your services should be transparent to the customers.

Unified monitoring tools can manage your services whether they are running on your local infrastructure, on your private cloud or even a third party public cloud. When issues happen (yes – "when" not "if") you can quickly identify the root cause and get a rapid resolution, hopefully well before the customer is impacted.

You want your customers to be able to access your site and more importantly, you want them to be able transact business while they are there. Make it easy for them and less of a headache for you and your organization.

Scott Hollis is Director of Product Marketing for Zenoss.

The Latest

Rapid AI adoption and the unique ways AI workloads operate is redefining the scope and structure of what these teams must deliver. This shift is forcing organizations to rethink how they manage scale, automation, and control, according to The State of SRE and Platform Engineering 2026, a new report from Dynatrace ...

AI is usually talked about as a software tool, but it also depends heavily on the network behind it. Whether a company is using AI for chatbots, automation, monitoring, analytics, or employee support, all of that information has to move across the network in a reliable and secure way. That means AI is not just an application decision. It is also an infrastructure decision. Before organizations rush into AI, they should ask a simple question: Is our network ready to support it? ...

Enterprise AI often lacks governed access to where business processes actually execute. Without that access, AI agents may be able to reason, but they cannot operate reliably across enterprise workflows. For AI agents to effectively carry out workflows, they will require integration-layer context and controls. Organizations can implement these prerequisites by providing AI with managed access to the middleware layer ...

Enterprise networks rarely behave the same way for very long. A routing adjustment in one region may unexpectedly alter application performance in another. A cloud migration may introduce hidden dependencies that go unnoticed until an outage occurs. All the while, the network is managed by several different teams, each of whom use different tool sets — and as a result, have different views of the network ... There’s usually an engineer who remembers why traffic fails over a certain way between sites, or which transparent firewall was added where. The problem is that human memory cannot scale alongside enterprise-scale networks ...

Ask an infrastructure team how confident they are in their ability to govern AI, and most will tell you they've got it handled. A recent survey of 406 IT decision-makers and platform engineering leaders found 86% expressing exactly that confidence. Ask the same group whether they have a formal written AI governance policy, and the number drops to 30%, according to Spacelift's Infrastructure Automation Report ...

In MEAN TIME TO INSIGHT Episode 27, Shamus McGillicuddy, EMA VP of Research, Network Infrastructure and Operations, and Parker Hathcock, EMA Research Director covering IT Service/Operations (ServiceOps), discuss observability unification in modern IT operations ... 

Virtual Private Networks became a cornerstone of enterprise security at a time when corporate infrastructure looked very different from today ... For years, this model worked well. But the architecture behind VPNs assumed a centralized corporate environment—one where the network itself was the hub of activity. In a cloud — first world, that assumption no longer holds ...

Website outages get resolved just as fast in August as they do in November. I went looking for the opposite: the summer slowdown everyone assumes is there once the people who fix things are away. It isn't in the data we collected, covering 1.8 million confirmed outages across tens of thousands of websites ...

This year, many of the cloud infrastructure contracts signed in the early days of the AI boom will come up for renewal. As the year goes on, I anticipate we'll see a significant amount of cloud vendor swapouts and multi-cloud adoption, and the reason isn't just GPU depreciation. It's because they're tired of their current cloud providers ...

There's a moment the many observability teams have experienced days into bringing a new service into production: you realize that the vendor's claims of "intelligent" behavior included a large serving of hype. Their dashboards look nice until they don't, the failure modes are a black box, and no one on the team can confidently explain why the system did what it did at 2 am. Agentic AI is about to force every Ops team to relive that moment at web-scale until they start treating these systems as the dependencies they actually are ...