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Embracing Automation to Prevent Network Downtime

Craig McDonald
BackBox

According to Gartner, IT system downtime causes an average loss of $300,000 per hour. Unfortunately, even highly skilled IT teams can make configuration mistakes or other errors, especially when dealing with the disarray that comes along with having a plethora of different device types and vendors across hybrid cloud and on-premises environments that compile today's modern networks and support mission-critical applications.

Networks need to be up and running for businesses to continue operating and sustaining customer-facing services. Streamlining and automating network administration tasks enable routine business processes to continue without disruption, eliminating any network downtime caused by human error or other system flaws.

Causes for Downtime

While network downtime can be caused by many factors from manual configuration errors to cyberattacks from threat actors, the bottom line is that outages are frustrating for teams unable to do their daily tasks and can lead to loss of confidence from customers and partners — not to mention the potential for significant revenue loss. Organizations dealing with today’s complicated network environments should be aware of a few leading causes of outages:

1. Increasing Complexity: The sharp increase in a distributed workforce spurred by the pandemic has led to an increase in network complexity. Because organizations' employees are now often based all over the world, there is an increase in hybrid network environments and the diversity of device types as well as different vendors of those devices that compile a network, which only grows increasingly complex as a business scales.

2. Human Error: The ongoing skills gap in the IT industry has a significant impact on network outages. As companies look to fill open roles for their IT teams, IT teams struggle with endless manual tasks they are expected to do at all hours of the day. So many manual processes coupled with smaller teams means configuration errors are easily introduced, patch management falls behind and it becomes increasingly difficult to keep up with best practices for routine network backups. Additionally, the manual effort surrounding script maintenance could be disrupted if the resources with relevant scripting knowledge leave the organization. Backfilling for these skills can take months, leaving the network vulnerable and putting the organization in a more difficult position to restore the network when an outage does occur.

Cyberattacks: Cyberattacks that leverage network vulnerabilities can cause significant downtime for businesses, with the outages following a ransomware attack averaging about 23 days. Cyber threats like ransomware, phishing and denial of service attacks are designed to push networks offline, taking down mission-critical applications. Some attackers even deliberately delete or compromise backups in an attempt to make it even more difficult for victims to recover and increase the chances of paying a ransom.

Leveraging Network Automation to Reduce Outages

As networks grow in complexity, the demand on networks and the IT teams supporting them to consistently deliver services and maintain a secure posture increases significantly. Organizations must lean on network management strategies that rely heavily on automation to reduce outages and risk.

Automation brings the ability to instill repeatability and consistency across your team and network. With standard processes implemented throughout the network, complex tasks become near-effortless, and potentially troublesome situations within the network infrastructure are avoided. For example, updating all devices to the most current vendor operating systems is a time-consuming and error-prone process when done manually, but is critically important to ensure network security, making it the perfect process to automate.

Automation helps to mitigate the impact of turnover and ongoing skills shortages and enables staff to execute consistently and effectively regardless of seniority or experience. In addition, through automation, IT staff can spend more time on strategic, growth-focused activities instead of administrative work like updating configurations with manual and laborious scripts.

By leveraging automation to reduce the chances of human error in networks, organizations can ensure the dissemination of baseline, gold-standard configurations that will enable teams to securely configure critical devices and remediate even the slightest deviations in configurations that could create a vulnerability and lead to a cyberattack.

With so many of today’s businesses depending on functioning networks to run operations, it is critical for organizations to invest in tools that prevent network outages and the consequences that follow, and automation is key. Having a network automation strategy will drive compelling operational efficiency gains and ensure a better security posture, all while making the life of IT teams easier by ensuring networks outages do not occur.

Craig McDonald is VP of Product Management at BackBox

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Embracing Automation to Prevent Network Downtime

Craig McDonald
BackBox

According to Gartner, IT system downtime causes an average loss of $300,000 per hour. Unfortunately, even highly skilled IT teams can make configuration mistakes or other errors, especially when dealing with the disarray that comes along with having a plethora of different device types and vendors across hybrid cloud and on-premises environments that compile today's modern networks and support mission-critical applications.

Networks need to be up and running for businesses to continue operating and sustaining customer-facing services. Streamlining and automating network administration tasks enable routine business processes to continue without disruption, eliminating any network downtime caused by human error or other system flaws.

Causes for Downtime

While network downtime can be caused by many factors from manual configuration errors to cyberattacks from threat actors, the bottom line is that outages are frustrating for teams unable to do their daily tasks and can lead to loss of confidence from customers and partners — not to mention the potential for significant revenue loss. Organizations dealing with today’s complicated network environments should be aware of a few leading causes of outages:

1. Increasing Complexity: The sharp increase in a distributed workforce spurred by the pandemic has led to an increase in network complexity. Because organizations' employees are now often based all over the world, there is an increase in hybrid network environments and the diversity of device types as well as different vendors of those devices that compile a network, which only grows increasingly complex as a business scales.

2. Human Error: The ongoing skills gap in the IT industry has a significant impact on network outages. As companies look to fill open roles for their IT teams, IT teams struggle with endless manual tasks they are expected to do at all hours of the day. So many manual processes coupled with smaller teams means configuration errors are easily introduced, patch management falls behind and it becomes increasingly difficult to keep up with best practices for routine network backups. Additionally, the manual effort surrounding script maintenance could be disrupted if the resources with relevant scripting knowledge leave the organization. Backfilling for these skills can take months, leaving the network vulnerable and putting the organization in a more difficult position to restore the network when an outage does occur.

Cyberattacks: Cyberattacks that leverage network vulnerabilities can cause significant downtime for businesses, with the outages following a ransomware attack averaging about 23 days. Cyber threats like ransomware, phishing and denial of service attacks are designed to push networks offline, taking down mission-critical applications. Some attackers even deliberately delete or compromise backups in an attempt to make it even more difficult for victims to recover and increase the chances of paying a ransom.

Leveraging Network Automation to Reduce Outages

As networks grow in complexity, the demand on networks and the IT teams supporting them to consistently deliver services and maintain a secure posture increases significantly. Organizations must lean on network management strategies that rely heavily on automation to reduce outages and risk.

Automation brings the ability to instill repeatability and consistency across your team and network. With standard processes implemented throughout the network, complex tasks become near-effortless, and potentially troublesome situations within the network infrastructure are avoided. For example, updating all devices to the most current vendor operating systems is a time-consuming and error-prone process when done manually, but is critically important to ensure network security, making it the perfect process to automate.

Automation helps to mitigate the impact of turnover and ongoing skills shortages and enables staff to execute consistently and effectively regardless of seniority or experience. In addition, through automation, IT staff can spend more time on strategic, growth-focused activities instead of administrative work like updating configurations with manual and laborious scripts.

By leveraging automation to reduce the chances of human error in networks, organizations can ensure the dissemination of baseline, gold-standard configurations that will enable teams to securely configure critical devices and remediate even the slightest deviations in configurations that could create a vulnerability and lead to a cyberattack.

With so many of today’s businesses depending on functioning networks to run operations, it is critical for organizations to invest in tools that prevent network outages and the consequences that follow, and automation is key. Having a network automation strategy will drive compelling operational efficiency gains and ensure a better security posture, all while making the life of IT teams easier by ensuring networks outages do not occur.

Craig McDonald is VP of Product Management at BackBox

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 ...