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6 Lessons the ACLU.org Web Team Can Learn from Online Retailers

Tammy Everts

If the events of this past weekend are anything to go by, the American Civil Liberties Union (ACLU) and similar organizations should take their cues from the retail industry.

I’m not talking about tactics when it comes to responding in court to the current administration's executive orders. I’m talking about how they manage online traffic.

Consider what happened this weekend after President Trump signed a controversial executive order. As a result of this action, the ACLU received more than $24 million in online donations – seven times the amount it receives in an entire year – from 356,306 people. Not surprisingly, this traffic spike caused the site to briefly go down.

Traffic surges can happen when you least expect them. Political events can have a huge impact on people’s online behavior, as the ACLU’s website outage clearly demonstrates. While the ACLU might reasonably have expected online donations to increase in light of recent events, they had no way of knowing they were about to experience the largest surge in donations in their 97-year history.

Online retailers know they need to ensure they’re “always open” in today's 24/7 on-demand world. Fortunately, thanks to modern load testing and performance monitoring technologies, site owners can load test at massive scale via the cloud to ensure their sites can handle immense traffic, along with unprecedented visibility into the real-time speed and availability of their sites.

Here are 7 tips that organizations like the ACLU can borrow from the retail world:

1. Remember that every site fails eventually

There’s no such thing as 100% uptime. When a site goes down, it isn’t because someone forgot to flip a switch. It’s because modern websites are complex mechanisms. Any complex system will fail eventually.

2. Accept that you can’t performance test for every contingency

Performance tests are a reliable way to guarantee that your site won’t go down — as long as it’s subjected to the same conditions defined within your test parameters. But you can’t test every single variation of every single parameter. When loads are different from what you modeled in your tests, you may have problems.

3. Know that the past is not a predictor of the future

Load patterns are unpredictable. Yes, you can and should take past load patterns into account when preparing your site, but this won’t cover you for every contingency. Just because you experienced certain load patterns for one event doesn’t mean that load pattern will be consistent for other events.

Over time — even very short periods of time — your site changes, your visitors change and your visitors’ behavior changes. There are no constants. Surprises happen.

4. See failure as an opportunity

Outages suck. There’s no sugarcoating that. But if you must experience one, then you should learn everything you can from it. Make it your mission to get to the root cause of the problem and develop new testing processes to prevent the issue from recurring.

5. Embrace continuous improvement

The web is a dynamic space, which means none of us ever get to stand back, dust off our hands and exclaim: “There! It’s finished!” Instead we build, we evolve, we fail (sometimes), we learn, we evolve some more, so on. We value small evolutionary steps—adding new tools and processes gradually — versus huge overnight changes. We recognize that rigorous performance testing and monitoring don’t guarantee 100% uptime, but they do allow us to fail faster and iterate sooner.

6. Be aware that page slowdowns can cause as much — or more — damage to your business as outages

Outages are stressful, but they’re not the worst performance issue that most sites face. If a site goes down, you’ll probably just try it again a few hours later. Most of us accept that these blips happen. But if a site is consistently slow, people could eventually stop visiting altogether.

Ultimately, the ACLU and similar organizations need to realize that the Trump administration will make the news cycle a perpetual “Cyber Monday." They will need to be prepared. Following the example of online retailers will help them be ready for their moment in the spotlight.

Tammy Everts is Director of Content and Editorial at SOASTA.

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6 Lessons the ACLU.org Web Team Can Learn from Online Retailers

Tammy Everts

If the events of this past weekend are anything to go by, the American Civil Liberties Union (ACLU) and similar organizations should take their cues from the retail industry.

I’m not talking about tactics when it comes to responding in court to the current administration's executive orders. I’m talking about how they manage online traffic.

Consider what happened this weekend after President Trump signed a controversial executive order. As a result of this action, the ACLU received more than $24 million in online donations – seven times the amount it receives in an entire year – from 356,306 people. Not surprisingly, this traffic spike caused the site to briefly go down.

Traffic surges can happen when you least expect them. Political events can have a huge impact on people’s online behavior, as the ACLU’s website outage clearly demonstrates. While the ACLU might reasonably have expected online donations to increase in light of recent events, they had no way of knowing they were about to experience the largest surge in donations in their 97-year history.

Online retailers know they need to ensure they’re “always open” in today's 24/7 on-demand world. Fortunately, thanks to modern load testing and performance monitoring technologies, site owners can load test at massive scale via the cloud to ensure their sites can handle immense traffic, along with unprecedented visibility into the real-time speed and availability of their sites.

Here are 7 tips that organizations like the ACLU can borrow from the retail world:

1. Remember that every site fails eventually

There’s no such thing as 100% uptime. When a site goes down, it isn’t because someone forgot to flip a switch. It’s because modern websites are complex mechanisms. Any complex system will fail eventually.

2. Accept that you can’t performance test for every contingency

Performance tests are a reliable way to guarantee that your site won’t go down — as long as it’s subjected to the same conditions defined within your test parameters. But you can’t test every single variation of every single parameter. When loads are different from what you modeled in your tests, you may have problems.

3. Know that the past is not a predictor of the future

Load patterns are unpredictable. Yes, you can and should take past load patterns into account when preparing your site, but this won’t cover you for every contingency. Just because you experienced certain load patterns for one event doesn’t mean that load pattern will be consistent for other events.

Over time — even very short periods of time — your site changes, your visitors change and your visitors’ behavior changes. There are no constants. Surprises happen.

4. See failure as an opportunity

Outages suck. There’s no sugarcoating that. But if you must experience one, then you should learn everything you can from it. Make it your mission to get to the root cause of the problem and develop new testing processes to prevent the issue from recurring.

5. Embrace continuous improvement

The web is a dynamic space, which means none of us ever get to stand back, dust off our hands and exclaim: “There! It’s finished!” Instead we build, we evolve, we fail (sometimes), we learn, we evolve some more, so on. We value small evolutionary steps—adding new tools and processes gradually — versus huge overnight changes. We recognize that rigorous performance testing and monitoring don’t guarantee 100% uptime, but they do allow us to fail faster and iterate sooner.

6. Be aware that page slowdowns can cause as much — or more — damage to your business as outages

Outages are stressful, but they’re not the worst performance issue that most sites face. If a site goes down, you’ll probably just try it again a few hours later. Most of us accept that these blips happen. But if a site is consistently slow, people could eventually stop visiting altogether.

Ultimately, the ACLU and similar organizations need to realize that the Trump administration will make the news cycle a perpetual “Cyber Monday." They will need to be prepared. Following the example of online retailers will help them be ready for their moment in the spotlight.

Tammy Everts is Director of Content and Editorial at SOASTA.

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I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...

Over the past few years, large language models (LLMs) have revolutionized the software industry. Given their ability to excel at multi-step reasoning, LLMs have helped enterprises streamline workflows and adapt to the unknown. However, employing such models comes with sky-high costs, latency issues, and limited flexibility. In the realm of IT operations, it is generally wiser to employ smaller, domain-specific models instead ...

For years, DevOps teams operated under a simple assumption: collect enough telemetry, and you can find and fix any problem. That assumption is breaking down. Modern enterprises now operate across microservices, hybrid cloud environments, APIs, Kubernetes, and highly automated delivery pipelines. Releases happen continuously, dependencies shift constantly, and failures spread faster than teams can diagnose them ...

New Relic surveyed IT and engineering leaders from the media and entertainment (M&E) sector to understand what's working — and where challenges persist with their observability practices. The findings reveal how M&E organizations are navigating rising platform complexity, audience expectations, and AI-driven change. Below are five takeaways that stand out ...

Let me start with something I've seen play out more times than I can count. A team hits a wall with the cloud. Costs creep up, then spike. Performance starts to feel inconsistent. Someone in finance asks a simple question like "why did this double?" and nobody has a clean answer ... Maybe this isn't the right place for everything. That realization feels like a breakthrough, like you've identified the problem. In reality, you've just identified the starting line ...

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...