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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

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 ...