Retail Armageddon is the Least of Our Worries

Target's tech troubles cost them business, but what’s at stake when mission-critical software decides to wreak havoc on our transportation, finances, and healthcare?
Barry Morris
Undo

In a post-apocalyptic world, shopping carts filled with items sit motionless in aisles, left abandoned by the humans who have mysteriously disappeared. At least that's the cliche scene depicted by sci-fi filmmakers over the past two decades. The audience is left to wonder what happened to force people to stop what they were doing and leave everything behind.

If this past weekend was any indication, Armageddon begins when Target's cash registers shut down.

Armageddon begins when Target's cash registers shut down

We have come to expect technology to just, well, work. It has become so integrated into our everyday lives that we hardly give any thought as to what it actually takes to make the complicated code do the things we want it to. We let technology take the wheel even though it's capable of driving us off a cliff.

The Target Corporation endured two days of checkout chaos. Target lost millions of dollars in revenue but received millions of dollars in bad publicity. Its stock fell. People notice disasters, even minor ones.

While Twitter users described #targetdown as "frustrating," "chaotic," and "Armageddon," imagine the potentially life-altering effects of technology failure in other areas we've given it power:

■ Self-driving cars

■ Analysis in medical data

■ Assessment in academics

■ AI-based legal preparation

■ Algorithms determining online loan approval

■ Algorithms for news feeds

What Happened: Is It the Software or Hardware?

Target said the weekend register outages were two separate issues: on Saturday it was an "internal technology issue," and on Sunday, a problem at one of the data centers belonging to Target's payment vendor NCR. They could mean anything, but Target was quick to point out that it wasn't a security issue or data breach — which was the case in 2013 when a data breach exposed millions of customers' credit and debit card information.

Large system outages that last a long time are usually not software issues, or at least not bugs. Sometimes they are of course, but more often it's either a single point of hardware failure or a cascading systematic failure. So some initial digging to discover whether this is a software thing is the first step.

Solving a hardware problem would be easier. Disaster recovery plans are almost always about physical or virtual infrastructure, but this misses where most of today's real disasters happen: in the software.

An Undiagnosed Software Defect Is Like a Ticking Bomb

Companies that were not software companies 10 years ago are now software companies.

Take Target for example. Traditional brick and mortar retailers are constantly warding off threats from e-commerce (specifically Amazon) and relying on software to give them a leg up. More software systems and more points of sale put them at greater risk of failures.

If one point fails it impacts customer sentiment across the entire chain.

The fact therefore is this: as more infrastructure issues become software, and as more systems become interconnected, the cause of disasters is moving around the stack making them much harder to find.

An undiagnosed software defect is like a ticking time bomb. Now imagine that bomb is in your car.

The AI Car vs. the Poodle

Software autonomy in transportation is a much bigger problem that runs the risk of being deadly.

Imagine a Tesla driving on autopilot and a man walking his poodle across the roadway a few feet ahead. The AI vehicle software detects the man and poodle in the road, but a glitch prevents it from taking any action. The poodle gets run over.

How developers go about solving what went wrong requires the developers to do the painstaking task of recreating the entire scenario: the time of day, the road condition, the weather conditions, the height and weight of both the poodle and the man, the pair's movements across the road. It's nearly impossible.

In real life, investigations are still on-going for two Boeing 737 Max crashes in Indonesia and Ethiopia. The Max software has been implicated in the crashes.

In aviation disasters, investigators always look to recover the black box onboard. But a black box can only tell you that the plane crashed because of a software problem. It can't tell you why the software did what it did to lead up to the crash.

Judgment Day

In the Terminator movie franchise, Skynet was the autonomous AI antagonist we never saw.

While the movies are science fiction, the reality today is that AI and machine learning are becoming more common in multiple industries.

Software is making decisions and we need the ability to know what it did, preferably before it asks for your clothes, your boots, and your motorcycle.

Barry Morris is CEO of Undo

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Retail Armageddon is the Least of Our Worries

Target's tech troubles cost them business, but what’s at stake when mission-critical software decides to wreak havoc on our transportation, finances, and healthcare?
Barry Morris
Undo

In a post-apocalyptic world, shopping carts filled with items sit motionless in aisles, left abandoned by the humans who have mysteriously disappeared. At least that's the cliche scene depicted by sci-fi filmmakers over the past two decades. The audience is left to wonder what happened to force people to stop what they were doing and leave everything behind.

If this past weekend was any indication, Armageddon begins when Target's cash registers shut down.

Armageddon begins when Target's cash registers shut down

We have come to expect technology to just, well, work. It has become so integrated into our everyday lives that we hardly give any thought as to what it actually takes to make the complicated code do the things we want it to. We let technology take the wheel even though it's capable of driving us off a cliff.

The Target Corporation endured two days of checkout chaos. Target lost millions of dollars in revenue but received millions of dollars in bad publicity. Its stock fell. People notice disasters, even minor ones.

While Twitter users described #targetdown as "frustrating," "chaotic," and "Armageddon," imagine the potentially life-altering effects of technology failure in other areas we've given it power:

■ Self-driving cars

■ Analysis in medical data

■ Assessment in academics

■ AI-based legal preparation

■ Algorithms determining online loan approval

■ Algorithms for news feeds

What Happened: Is It the Software or Hardware?

Target said the weekend register outages were two separate issues: on Saturday it was an "internal technology issue," and on Sunday, a problem at one of the data centers belonging to Target's payment vendor NCR. They could mean anything, but Target was quick to point out that it wasn't a security issue or data breach — which was the case in 2013 when a data breach exposed millions of customers' credit and debit card information.

Large system outages that last a long time are usually not software issues, or at least not bugs. Sometimes they are of course, but more often it's either a single point of hardware failure or a cascading systematic failure. So some initial digging to discover whether this is a software thing is the first step.

Solving a hardware problem would be easier. Disaster recovery plans are almost always about physical or virtual infrastructure, but this misses where most of today's real disasters happen: in the software.

An Undiagnosed Software Defect Is Like a Ticking Bomb

Companies that were not software companies 10 years ago are now software companies.

Take Target for example. Traditional brick and mortar retailers are constantly warding off threats from e-commerce (specifically Amazon) and relying on software to give them a leg up. More software systems and more points of sale put them at greater risk of failures.

If one point fails it impacts customer sentiment across the entire chain.

The fact therefore is this: as more infrastructure issues become software, and as more systems become interconnected, the cause of disasters is moving around the stack making them much harder to find.

An undiagnosed software defect is like a ticking time bomb. Now imagine that bomb is in your car.

The AI Car vs. the Poodle

Software autonomy in transportation is a much bigger problem that runs the risk of being deadly.

Imagine a Tesla driving on autopilot and a man walking his poodle across the roadway a few feet ahead. The AI vehicle software detects the man and poodle in the road, but a glitch prevents it from taking any action. The poodle gets run over.

How developers go about solving what went wrong requires the developers to do the painstaking task of recreating the entire scenario: the time of day, the road condition, the weather conditions, the height and weight of both the poodle and the man, the pair's movements across the road. It's nearly impossible.

In real life, investigations are still on-going for two Boeing 737 Max crashes in Indonesia and Ethiopia. The Max software has been implicated in the crashes.

In aviation disasters, investigators always look to recover the black box onboard. But a black box can only tell you that the plane crashed because of a software problem. It can't tell you why the software did what it did to lead up to the crash.

Judgment Day

In the Terminator movie franchise, Skynet was the autonomous AI antagonist we never saw.

While the movies are science fiction, the reality today is that AI and machine learning are becoming more common in multiple industries.

Software is making decisions and we need the ability to know what it did, preferably before it asks for your clothes, your boots, and your motorcycle.

Barry Morris is CEO of Undo

Related Links

Hot Topics

The Latest

When the Database Is the Problem, Is APM Enough?

Production incidents rarely announce themselves as database problems. They appear as slow transactions, timeouts, rising response times, or an application struggling under a workload it previously handled. APM provides an essential starting point. It can identify a slow transaction path, highlight an affected service, and show that a database dependency is consuming more time than expected. But identifying the database as part of the problem is not the same as explaining what is happening inside it ...

From Cleanup to Prevention: The Future of Cloud-Native Cost Optimization

Cloud teams are under constant pressure to reduce spend without slowing development or increasing operational risk. They are deploying autoscalers, rightsizing workloads, enforcing resource requests, reviewing utilization dashboards, and building FinOps processes around cloud-native environments. Yet the results often disappoint ...

The Real Enterprise AI Risk Isn't Hallucinations

Ask most IT leaders about their biggest concern with AI and you'll hear the same answer: hallucinations ... Today, however, the conversation has shifted ... As organizations move beyond chatbots and experiments, they are increasingly deploying AI agents that perform multi-step tasks. These systems retrieve documents, query databases, call APIs, generate reports, write code, and make recommendations. The issue is not whether the model can reason. The issue is whether the organization can see, verify, and govern the decisions being made along the way ...

Beyond Buy vs. Build: The New Playbook for Data Pipelines

While organizations want to take control of their telemetry, building telemetry pipelines from scratch can be a very daunting, complicated task, even when leveraging open-source standards like OpenTelemetry. It requires specialized knowledge across distributed systems, data engineering, and security. This fragmented approach across systems causes higher operational costs; it puts a strain on resources and reduces efficiency as teams have to work with different interfaces and processes ...

The Corporate Network Is Fading - Here's What Replaces It

For decades, enterprise networks were designed around a simple assumption: work happened inside the office. Applications lived in centralized data centers, employees connected through internal infrastructure, and security focused on protecting the perimeter that surrounded everything ... But the way organizations operate today bears little resemblance to that environment. Cloud platforms host critical applications, employees connect from homes and airports as often as they do from offices, and partners collaborate through shared systems that exist far beyond corporate walls. In short, the corporate network no longer resembles the environment it was designed to protect ...