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Enabling Your Website to Survive "The Trump Effect"

Michelle McLean

As President Trump begins his administration, he continues to use a variety of channels to send messages about his thoughts and plans. These take many forms: tweets, Executive Orders, off-the-cuff comments in speeches and press conferences. We've seen the impact these communiqués have had — they move stock prices, spur protests and generate press frenzies.

Some organizations have been majorly impacted by these communications. This past weekend, for example, in the wake of a controversial Executive Order from President Trump, the American Civil Liberties Union (ACLU) found its website crashing under the load of an enormous spike in online donations.

When an organization like the ACLU finds itself unexpectedly caught in "the Trump effect" — to its benefit or detriment — the IT staff may be under instant pressure to reinforce its systems to accommodate significant traffic surges. The following steps may help as a fast response:

Leverage cloud capacity

If there are resources already set up to run in the cloud, consider expanding capacity dedicated to those applications and data sources. Public-facing sites and applications in particular should be ready to take advantage of this kind of surge capacity.

Reinforce web resources

Web server capacity can be increased fairly easily, leveraging additional hardware for scale out, paired with TCP load balancers to distribute the load. Augmenting the infrastructure with additional horizontal scale out will help keep a public website online when experiencing major traffic surges.

Focus on database resources

The database is often the weakest link in many organizations' technology stacks. Without high-performing databases, apps and web servers will grind to a halt — and "slow" becomes the same as "down." It is crucial to monitor database performance, and, like with the web tier, consider horizontal scale out to increase capacity, paired with database load-balancing software to distribute the load.

Monitor the complete application stack

Application Performance Monitoring (APM) software can provide a holistic view of customers' experiences. Where are the bottlenecks in the application's overall performance? What recommendations can the software make for root cause and troubleshooting?

These actions are easier to undertake with some advanced warning, of course. Any organization that anticipates it could be impacted by "the Trump effect" should plan ahead with these steps to the best of their ability. IT teams in such organizations should look across the full technology stack and identify quick steps they can take to make their systems more robust.

Michelle McLean is VP of Marketing at ScaleArc.

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Enabling Your Website to Survive "The Trump Effect"

Michelle McLean

As President Trump begins his administration, he continues to use a variety of channels to send messages about his thoughts and plans. These take many forms: tweets, Executive Orders, off-the-cuff comments in speeches and press conferences. We've seen the impact these communiqués have had — they move stock prices, spur protests and generate press frenzies.

Some organizations have been majorly impacted by these communications. This past weekend, for example, in the wake of a controversial Executive Order from President Trump, the American Civil Liberties Union (ACLU) found its website crashing under the load of an enormous spike in online donations.

When an organization like the ACLU finds itself unexpectedly caught in "the Trump effect" — to its benefit or detriment — the IT staff may be under instant pressure to reinforce its systems to accommodate significant traffic surges. The following steps may help as a fast response:

Leverage cloud capacity

If there are resources already set up to run in the cloud, consider expanding capacity dedicated to those applications and data sources. Public-facing sites and applications in particular should be ready to take advantage of this kind of surge capacity.

Reinforce web resources

Web server capacity can be increased fairly easily, leveraging additional hardware for scale out, paired with TCP load balancers to distribute the load. Augmenting the infrastructure with additional horizontal scale out will help keep a public website online when experiencing major traffic surges.

Focus on database resources

The database is often the weakest link in many organizations' technology stacks. Without high-performing databases, apps and web servers will grind to a halt — and "slow" becomes the same as "down." It is crucial to monitor database performance, and, like with the web tier, consider horizontal scale out to increase capacity, paired with database load-balancing software to distribute the load.

Monitor the complete application stack

Application Performance Monitoring (APM) software can provide a holistic view of customers' experiences. Where are the bottlenecks in the application's overall performance? What recommendations can the software make for root cause and troubleshooting?

These actions are easier to undertake with some advanced warning, of course. Any organization that anticipates it could be impacted by "the Trump effect" should plan ahead with these steps to the best of their ability. IT teams in such organizations should look across the full technology stack and identify quick steps they can take to make their systems more robust.

Michelle McLean is VP of Marketing at ScaleArc.

Hot Topics

The Latest

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

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.