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Outages Related to Machine Identity on the Rise

Because CIOs often have limited visibility into the number of machine identities on their networks and these critical security assets are not prioritized in IAM and security budgets, CIOs should expect to see a sharp increase in machine identity related outages and security breaches, according to a new study of 1,000 CIOs conducted by Venafi.


Machine identities enable secure connection and authentication for every part of IT infrastructure, from physical, virtual servers and IoT devices to software applications, APIs and containers. Any time two machines need to authenticate each other a machine identity is required.

100% of CIOs say that digital transformation is driving a dramatic increase in the number of machine identities their organizations require. Without an automated machine identity management program, organizations suffer from outages caused by expired machine identities and breaches caused by machine identity misuse or compromise.

According to the study, the average organization used nearly a quarter of a million (250,000) machine identities at the end of 2021. This is a startling number when you consider that organizations initially underestimate machine identity populations by 50% or more because they have extremely limited visibility into the machine identities their organization requires.

At current rates of growth, these same organizations can expect their machine identity inventory to more than double to at least 500,000 by 2024.

Moreover, three-quarters of surveyed CIOs said that they expect digital transformation initiatives to increase the number of machine identities in their organizations by 26% — with more than one-quarter (27%) citing a percentage of higher than 50%.

Key survey findings include:

■ 83% of organizations suffered a machine identity related outage during the last 12 months; over a quarter (26%) say critical systems were impacted.

■ 57% of organizations experienced at least one data breach or security incident related to compromised machine identities (including TLS, SSH keys and code signing keys and certificates) during the same time period.

"The realities of digital transformation mean that every business is now a software company. This means IAM priorities need to shift to protect the machine identities required for digital transformation initiatives because these initiatives are the engines of innovation and growth," said Kevin Bocek, VP of Security Strategy and Threat Intelligence at Venafi. "The unfortunate reality is that most organizations are not prepared to manage all the machines identities they need. This rapidly growing gap has opened a new attack surface – from software build pipelines to Kubernetes clusters – that is very attractive to attackers."

The rise in the number of machines on enterprise networks is exposing outdated machine identity management practices. Nearly two-thirds (64%) of CIOs say that rather than using a comprehensive machine identity management solution, their organizations combine multiple solutions and processes, including point solutions from certificate authorities (CAs) and public cloud providers, homegrown solutions and manual processes. This approach does not provide enterprise-wide view of all machine identities or provide the mechanisms needed to enforce configuration or policy requirements.

"Machine identity management is in the early stages of adoption. It's very similar to what happened with customer and workforce identity a few years ago, but it's orders of magnitude larger in scale and change is happening much faster," Bocek continued. "The challenges connected with human identity management pale in contrast to the challenges of managing machine identities. This research underscores the urgent need for every organization to evaluate their machine identity management program in order to protect their digital transformation initiatives."

Methodology: Conducted by Coleman Parkes Research, Venafi's survey evaluated the opinions of 1000 CIOs across six countries/regions: United States, United Kingdom, France, DACH (Germany, Austria, Switzerland), Benelux (Belgium, Netherlands, Luxembourg) and Australasia (Australia, New Zealand).

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Outages Related to Machine Identity on the Rise

Because CIOs often have limited visibility into the number of machine identities on their networks and these critical security assets are not prioritized in IAM and security budgets, CIOs should expect to see a sharp increase in machine identity related outages and security breaches, according to a new study of 1,000 CIOs conducted by Venafi.


Machine identities enable secure connection and authentication for every part of IT infrastructure, from physical, virtual servers and IoT devices to software applications, APIs and containers. Any time two machines need to authenticate each other a machine identity is required.

100% of CIOs say that digital transformation is driving a dramatic increase in the number of machine identities their organizations require. Without an automated machine identity management program, organizations suffer from outages caused by expired machine identities and breaches caused by machine identity misuse or compromise.

According to the study, the average organization used nearly a quarter of a million (250,000) machine identities at the end of 2021. This is a startling number when you consider that organizations initially underestimate machine identity populations by 50% or more because they have extremely limited visibility into the machine identities their organization requires.

At current rates of growth, these same organizations can expect their machine identity inventory to more than double to at least 500,000 by 2024.

Moreover, three-quarters of surveyed CIOs said that they expect digital transformation initiatives to increase the number of machine identities in their organizations by 26% — with more than one-quarter (27%) citing a percentage of higher than 50%.

Key survey findings include:

■ 83% of organizations suffered a machine identity related outage during the last 12 months; over a quarter (26%) say critical systems were impacted.

■ 57% of organizations experienced at least one data breach or security incident related to compromised machine identities (including TLS, SSH keys and code signing keys and certificates) during the same time period.

"The realities of digital transformation mean that every business is now a software company. This means IAM priorities need to shift to protect the machine identities required for digital transformation initiatives because these initiatives are the engines of innovation and growth," said Kevin Bocek, VP of Security Strategy and Threat Intelligence at Venafi. "The unfortunate reality is that most organizations are not prepared to manage all the machines identities they need. This rapidly growing gap has opened a new attack surface – from software build pipelines to Kubernetes clusters – that is very attractive to attackers."

The rise in the number of machines on enterprise networks is exposing outdated machine identity management practices. Nearly two-thirds (64%) of CIOs say that rather than using a comprehensive machine identity management solution, their organizations combine multiple solutions and processes, including point solutions from certificate authorities (CAs) and public cloud providers, homegrown solutions and manual processes. This approach does not provide enterprise-wide view of all machine identities or provide the mechanisms needed to enforce configuration or policy requirements.

"Machine identity management is in the early stages of adoption. It's very similar to what happened with customer and workforce identity a few years ago, but it's orders of magnitude larger in scale and change is happening much faster," Bocek continued. "The challenges connected with human identity management pale in contrast to the challenges of managing machine identities. This research underscores the urgent need for every organization to evaluate their machine identity management program in order to protect their digital transformation initiatives."

Methodology: Conducted by Coleman Parkes Research, Venafi's survey evaluated the opinions of 1000 CIOs across six countries/regions: United States, United Kingdom, France, DACH (Germany, Austria, Switzerland), Benelux (Belgium, Netherlands, Luxembourg) and Australasia (Australia, New Zealand).

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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 ...