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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.

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AI observability serves several roles across an organization. AI engineers use it to build, evaluate, and improve AI systems. SREs use it to operate those systems reliably and efficiently in production, including managing their cost. Leaders need it to connect AI behavior and operational performance to business outcomes. The common need is a clear understanding of whether AI systems are delivering the intended result ...

Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...

Part 3 reports on the current state of AI observability. Most experts agree: enterprises are moving faster with AI than they are with the operational discipline needed to run it safely ...

When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...

In this extensive 14-part series that will post over the next three weeks, experts across observability and AI will provide insight and opinions on the need for AI Observability, the challenges, the benefits, the current state, and predictions for the future ...

Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...

AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...

For more than a decade, the default infrastructure play has been simple. Move more workloads to the cloud, retire on-premises gear and treat the data center as a cost to shrink. That logic held while public cloud offered near-limitless capacity at predictable prices, and AI demand is now testing both halves of that assumption ...

Most enterprise IT leaders can tell you exactly how many applications are running across their organization. They can surface a dashboard showing telecom spend by region, pull a report on SaaS license utilization, or call up a real-time view of mobile device inventory. The data is there, and IT leaders have largely delivered on the promise of visibility. Yet, in most organizations, that visibility has not translated into business value ...