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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

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For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...

40% of organizations deploying AI will implement dedicated AI observability tools by 2028 to monitor model performance, bias and outputs, according to Gartner ...

Until AI-powered engineering tools have live visibility of how code behaves at runtime, they cannot be trusted to autonomously ensure reliable systems, according to the State of AI-Powered Engineering Report 2026 report from Lightrun. The report reveals that a major volume of manual work is required when AI-generated code is deployed: 43% of AI-generated code requires manual debugging in production, even after passing QA or staging tests. Furthermore, an average of three manual redeploy cycles are required to verify a single AI-suggested code fix in production ...

Many organizations describe AI as strategic, but they do not manage it strategically. When AI plans are disconnected from strategy, detached from organizational learning, and protected from serious assumptions testing, the problem is no longer technical immaturity; it is a failure of management discipline ... Executives too often tell organizations to "use AI" before they define what AI is supposed to change. The problem deepens in organizations where strategy isn't well articulated in the first place ...

Across the enterprise technology landscape, a quiet crisis is playing out. Organizations have run hundreds, sometimes thousands, of generative AI pilots. Leadership has celebrated the proof of concept (POCs) ... Industry experience points to a sobering reality: only 5-10% of AI POCs that progress to the pilot stage successfully reach scaled production. The remaining 90% fail because the enterprise environment around them was never ready to absorb them, not the AI models ...

Today's modern systems are not what they once were. Organizations now rely on distributed systems, event-driven workflows, hybrid and multi-cloud environments and continuous delivery pipelines. While each adds flexibility, it also introduces new, often invisible failures. Development speed is no longer the primary bottleneck of innovation. Reliability is ...

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