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Don't Let an IT Service Disruption Lead to Catastrophic Downtime

Krishna Dunthoori
Apty

Over the years, we've seen several high-profile examples of how even the slightest human error can induce devastating bouts of downtime. One infamous example came several years ago, when Amazon's S3 service was knocked offline, obliterating service to social media platforms, web publishers, and other leading websites. The cause? A simple typo — an authorized employee intended to take a small number of servers offline to fix a problem with the billing system, but accidentally entered a command incorrectly and removed a large number of servers instead.

Within several hours, Amazon's S3 service was back online, but the incident had lasting ramifications. Numerous popular apps and websites were impacted, and the estimated cost to S&P 500 companies was $150 million, while US financial services companies lost an estimated $160 million in revenue.

Even for the average organization (i.e., one not of Amazon's size), the cost of application downtime stands at a staggering $5,600 per minute. Moreover, outages are continuing to increase, as more people within an organization are empowered to make changes to IT services. In fact, a large majority of all incidents reported to an IT service desk are caused by change.

IT Service Management (ITSM) solutions are widely available to help solve this problem, with incident management as one of its main pillars. Incident management enables the rapid identification, notification, and resolution of critical application outages, and provides a clear, documented process to follow if and when things go wrong. The reported percentage of IT projects that result in failure depends on the article or survey you read, but most put the number at 55 - 75 percent. So why do so many ITSM implementations fail?

Like other software implementations, ITSM often suffers from a lack of user adoption. This is because people, by nature, are resistant to change. Sometimes, organizations and their training teams erroneously believe they can communicate once or twice about a new software implementation, deliver a round of training, and sit back and expect to realize software value. However, in prioritizing go-live, many training teams fail to properly support user adoption in the ensuing days and months, and adoption never reaches meaningful levels.

But in an incident response context, something else seems to be going on. Any strong emotion that temporarily impairs our thinking — anxiety, fear, or anger, for example — can result in a "brain freeze," or a temporary decline in cognitive functioning. So when an incident occurs, the ensuing panic among employees who are likely unfamiliar with the ITSM solution anyway, makes the situation that much more grim.

So how can organizations and training teams harness the full potential of ITSM solutions to maximize application uptime?

There are several areas to focus on, including:

Seamless onboarding and increasing user adoption - Organizations and their training teams need to simplify the ITSM onboarding process by providing real-time, in-app, context-driven guidance. This reduces the learning curve and eliminates the fear of embracing the new technology, while providing the right support at the right time.

Supporting change processes - Given the pace and frequency of change, context-driven guidance also makes it easier for ITSM users to implement changes posing fewer risks and disruptions, ensuring that changes are carried out much more smoothly.

Reducing all-important mean-time-to-repair (MTTR) - Especially in times of strain, context-driven guidance can also help ITSM users swiftly find information and efficiently resolve those IT issues they don't necessarily encounter every day, by providing in-the-moment, step-by-step guidance. This leads to augmented user productivity and satisfaction while minimizing service disruptions.

The Amazon S3 example may seem like an egregious example of "breaking the internet." Yet it clearly highlights how the slightest change or error can induce disaster, as well as the fragility of modern infrastructures — realities impacting all organizations. Successfully implementing and training on ITSM, and specifically incident management as part of an ITSM approach, can be vital in avoiding expensive downtime when a disruption occurs. The key is to have ongoing training and guided risk management in place so there is little to no pause in response when the inevitable error or disruption happens. This is where solutions like digital adoption platforms (DAPs) come into play to streamline and solve IT disruption downtime challenges — ensuring seamless and efficient adoption of ITSM tools.

Krishna Dunthoori is Founder and CEO of Apty

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Don't Let an IT Service Disruption Lead to Catastrophic Downtime

Krishna Dunthoori
Apty

Over the years, we've seen several high-profile examples of how even the slightest human error can induce devastating bouts of downtime. One infamous example came several years ago, when Amazon's S3 service was knocked offline, obliterating service to social media platforms, web publishers, and other leading websites. The cause? A simple typo — an authorized employee intended to take a small number of servers offline to fix a problem with the billing system, but accidentally entered a command incorrectly and removed a large number of servers instead.

Within several hours, Amazon's S3 service was back online, but the incident had lasting ramifications. Numerous popular apps and websites were impacted, and the estimated cost to S&P 500 companies was $150 million, while US financial services companies lost an estimated $160 million in revenue.

Even for the average organization (i.e., one not of Amazon's size), the cost of application downtime stands at a staggering $5,600 per minute. Moreover, outages are continuing to increase, as more people within an organization are empowered to make changes to IT services. In fact, a large majority of all incidents reported to an IT service desk are caused by change.

IT Service Management (ITSM) solutions are widely available to help solve this problem, with incident management as one of its main pillars. Incident management enables the rapid identification, notification, and resolution of critical application outages, and provides a clear, documented process to follow if and when things go wrong. The reported percentage of IT projects that result in failure depends on the article or survey you read, but most put the number at 55 - 75 percent. So why do so many ITSM implementations fail?

Like other software implementations, ITSM often suffers from a lack of user adoption. This is because people, by nature, are resistant to change. Sometimes, organizations and their training teams erroneously believe they can communicate once or twice about a new software implementation, deliver a round of training, and sit back and expect to realize software value. However, in prioritizing go-live, many training teams fail to properly support user adoption in the ensuing days and months, and adoption never reaches meaningful levels.

But in an incident response context, something else seems to be going on. Any strong emotion that temporarily impairs our thinking — anxiety, fear, or anger, for example — can result in a "brain freeze," or a temporary decline in cognitive functioning. So when an incident occurs, the ensuing panic among employees who are likely unfamiliar with the ITSM solution anyway, makes the situation that much more grim.

So how can organizations and training teams harness the full potential of ITSM solutions to maximize application uptime?

There are several areas to focus on, including:

Seamless onboarding and increasing user adoption - Organizations and their training teams need to simplify the ITSM onboarding process by providing real-time, in-app, context-driven guidance. This reduces the learning curve and eliminates the fear of embracing the new technology, while providing the right support at the right time.

Supporting change processes - Given the pace and frequency of change, context-driven guidance also makes it easier for ITSM users to implement changes posing fewer risks and disruptions, ensuring that changes are carried out much more smoothly.

Reducing all-important mean-time-to-repair (MTTR) - Especially in times of strain, context-driven guidance can also help ITSM users swiftly find information and efficiently resolve those IT issues they don't necessarily encounter every day, by providing in-the-moment, step-by-step guidance. This leads to augmented user productivity and satisfaction while minimizing service disruptions.

The Amazon S3 example may seem like an egregious example of "breaking the internet." Yet it clearly highlights how the slightest change or error can induce disaster, as well as the fragility of modern infrastructures — realities impacting all organizations. Successfully implementing and training on ITSM, and specifically incident management as part of an ITSM approach, can be vital in avoiding expensive downtime when a disruption occurs. The key is to have ongoing training and guided risk management in place so there is little to no pause in response when the inevitable error or disruption happens. This is where solutions like digital adoption platforms (DAPs) come into play to streamline and solve IT disruption downtime challenges — ensuring seamless and efficient adoption of ITSM tools.

Krishna Dunthoori is Founder and CEO of Apty

Hot Topics

The Latest

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 ...

The gap is widening between what teams spend on observability tools and the value they receive amid surging data volumes and budget pressures, according to The Breaking Point for Observability Leaders, a report from Imply ...