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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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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 ...

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

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 ...