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Down Goes the Internet (Again) – Part Two: 4 Strategies to Ensure Website Performance

Start with Part One of this article: Down Goes the Internet (Again) – Are You Ready?

In this era of unprecedented complexity, it's virtually impossible for a modern website to eliminate all the risk associated with using third parties. However, there are proactive strategies an organization can implement to better manage and minimize their risk. These include:

1. Proactively monitor speed and availability

Proactively monitor the speed and availability of websites, web applications and mobile sites from the true end-user perspective.

Today, there are so many elements out there on the web that stand between your data center and your users, including not just third-party services, but content delivery networks (CDNs), local and regional ISPs, mobile carrier networks and browsers, for example. Measuring performance from your data center alone is insufficient – unless, of course, your users live in your data center, which is highly unlikely.

The true browser-based perspective is the only place where you can accurately gauge your user's experience at the end of an extremely long and complicated technology path known as the application delivery chain. Today's new generation application performance management (APM) solutions are based on this true user perspective.

2. Monitor all transactions

Monitor all transactions, 24x7 along the complete application delivery chain. Sampling is not a sufficient means of gauging performance, of course, because a major performance issue may very well occur outside your testing interval – think of the Amazon EC2 outage that impacted Netflix on Christmas day last year!

Due to the unpredictability of major service outages, you need to be monitoring all transactions around the clock, to identify all performance aberrations and their root causes – both within and beyond the firewall – quickly and accurately, and get ahead of them.

3. Baseline and uphold performance-focused SLAs

Service-level agreements (SLAs) promising a certain level of availability on the part of a third-party service provider mean very little when it comes to performance.

For example, just because your cloud service provider's servers are up and running does not mean your users are experiencing an acceptable level of speed and reliability. Remember, third party services of all types are serving thousands of customers like you around the globe, and a spike in another customer's traffic may impact you.

With little insight into third party service providers' capacity planning decisions, you need to monitor performance levels yourself to ensure they don't drop off, and validate these against performance-focused SLAs. To get a sense of how a third party service provider may be impacting your overall performance, it can be helpful to compare your site's speed and availability before the third party service is added, to afterwards.

4. Utilize industry resources

Utilize industry resources to better assess if the source of a performance problem lies with you or one of your third-party service providers, as well as the likely performance impact on your customers.

These services may not prevent third party service outages from happening, but they can help companies better understand the source of performance problems so they can get in front of them more confidently and efficiently.

Conclusion

The reality is: the delivery chain underlying the services we often take for granted is so tenuous, that it's a marvel they don't break down more often. While outages may be inevitable, this does not make them any less costly or damaging to a company's reputation and revenues.

For example, on August 19, Amazon's North American retail site went down for about 49 minutes, with visitors greeted with the word “oops.” No explanation was given, but one estimate by Forbes put the cost to Amazon at nearly $2 million in sales.

But it's not just the “big guys” like Amazon that you need to focus on. The fact is that little storms are happening on the internet all the time, and you need to be prepared for them. When it comes to surviving and thriving in the age of increasing web complexity, an ounce of prevention can be worth a pound of cure. By taking advantage of several relatively simple and inexpensive approaches, organizations can better exploit all that third party services have to offer, while reducing the inherent risks.

Klaus Enzenhofer is Technology Strategist for Compuware APM’s Center of Excellence.

Down Goes the Internet (Again) – Part One: Are You Ready?

The Latest

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 ...

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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.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

Down Goes the Internet (Again) – Part Two: 4 Strategies to Ensure Website Performance

Start with Part One of this article: Down Goes the Internet (Again) – Are You Ready?

In this era of unprecedented complexity, it's virtually impossible for a modern website to eliminate all the risk associated with using third parties. However, there are proactive strategies an organization can implement to better manage and minimize their risk. These include:

1. Proactively monitor speed and availability

Proactively monitor the speed and availability of websites, web applications and mobile sites from the true end-user perspective.

Today, there are so many elements out there on the web that stand between your data center and your users, including not just third-party services, but content delivery networks (CDNs), local and regional ISPs, mobile carrier networks and browsers, for example. Measuring performance from your data center alone is insufficient – unless, of course, your users live in your data center, which is highly unlikely.

The true browser-based perspective is the only place where you can accurately gauge your user's experience at the end of an extremely long and complicated technology path known as the application delivery chain. Today's new generation application performance management (APM) solutions are based on this true user perspective.

2. Monitor all transactions

Monitor all transactions, 24x7 along the complete application delivery chain. Sampling is not a sufficient means of gauging performance, of course, because a major performance issue may very well occur outside your testing interval – think of the Amazon EC2 outage that impacted Netflix on Christmas day last year!

Due to the unpredictability of major service outages, you need to be monitoring all transactions around the clock, to identify all performance aberrations and their root causes – both within and beyond the firewall – quickly and accurately, and get ahead of them.

3. Baseline and uphold performance-focused SLAs

Service-level agreements (SLAs) promising a certain level of availability on the part of a third-party service provider mean very little when it comes to performance.

For example, just because your cloud service provider's servers are up and running does not mean your users are experiencing an acceptable level of speed and reliability. Remember, third party services of all types are serving thousands of customers like you around the globe, and a spike in another customer's traffic may impact you.

With little insight into third party service providers' capacity planning decisions, you need to monitor performance levels yourself to ensure they don't drop off, and validate these against performance-focused SLAs. To get a sense of how a third party service provider may be impacting your overall performance, it can be helpful to compare your site's speed and availability before the third party service is added, to afterwards.

4. Utilize industry resources

Utilize industry resources to better assess if the source of a performance problem lies with you or one of your third-party service providers, as well as the likely performance impact on your customers.

These services may not prevent third party service outages from happening, but they can help companies better understand the source of performance problems so they can get in front of them more confidently and efficiently.

Conclusion

The reality is: the delivery chain underlying the services we often take for granted is so tenuous, that it's a marvel they don't break down more often. While outages may be inevitable, this does not make them any less costly or damaging to a company's reputation and revenues.

For example, on August 19, Amazon's North American retail site went down for about 49 minutes, with visitors greeted with the word “oops.” No explanation was given, but one estimate by Forbes put the cost to Amazon at nearly $2 million in sales.

But it's not just the “big guys” like Amazon that you need to focus on. The fact is that little storms are happening on the internet all the time, and you need to be prepared for them. When it comes to surviving and thriving in the age of increasing web complexity, an ounce of prevention can be worth a pound of cure. By taking advantage of several relatively simple and inexpensive approaches, organizations can better exploit all that third party services have to offer, while reducing the inherent risks.

Klaus Enzenhofer is Technology Strategist for Compuware APM’s Center of Excellence.

Down Goes the Internet (Again) – Part One: Are You Ready?

The Latest

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.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...