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Getting to Zero Unplanned Downtime with AIOps

Andy Thurai
The Field CTO

Most business executives are worried about the competition taking them down. What they don't realize is, their own IT can do an equal amount of damage. Imagine this: if your rideshare app is constantly down, would you rather wait for it to come back up, or would you use the "other app?" Without realizing this fact, most organizations are one high-profile incident away from losing a lot of their customers.

A Silent Business Killer

With "digital native" businesses' complete reliance on IT, whether it is private data centers or cloud-based solutions, any long, unplanned downtime can kill a business quickly. The unplanned IT downtime is costing their businesses more than they think and the business executives are not fully aware of this.

Unplanned downtime can kill a business quickly

In a recent (2019) survey of 1000 businesses, ITIC estimated that for 86% of businesses, an hour of downtime will cost the business close to $300k an hour. And, for nearly 1/3 of the businesses, it will cost them between $1 million to $5 million. On average, an unplanned service outage lasts for four hours. And, on average, two outages are expected per enterprise, per year. All this means is that an enterprise can expect to lose between $2.5 to $40 million per year when the work stops due to an unplanned IT outage. And these numbers are going up by 30% YOY.

While these numbers (which are purely based on opportunity lost, lost employee productivity, and IT recovery and restoration costs) are mind-boggling, it doesn't even include any litigation, fines, penalties, non-compliance issues by regulatory bodies or even the brand hit, lost loyalty, or customer sat/attrition issues any enterprises will take due to unplanned downtime.

While large enterprises have specialized SWAT teams to reduce this impact, the smaller enterprises feel the brunt when such an event happens. When SRE teams, NOC/SOC teams and engineering teams are pulled into war rooms to solve the problem, the development/innovation and sometimes critical operational work come to a standstill. CIOs and other IT executives get involved until critical P1s are resolved, taking their time away from other strategic work.

Components of an IT Issue Resolution

Fixing any unplanned downtime consists of three major components:

1. Identifying the problem

2. Fixing the problem

3. Get the systems back up and running

While #2 can be minimized by having skilled IT staff, and #3 can be solved by a combination of automation and skilled IT staff, #1 is part art and part science. For most organizations, this is the hardest part and the silent killer. They spend too much time trying to find out the root cause of the problem. If you can't find the problem, you can't fix it. The very thought of having long, drawn-out war-room meetings, for critical P1 issues, should be any CIO's nightmare.

The efficiency of any ITOps team is measured by two major KPIs: MTBF (mean time between failures) and MTTR (mean time to repair). MTBF is a measure of how reliable your systems are, and MTTR is the true measure of how long your service is down, costing your business. The faster you find the problem, the faster you can solve it.

Is the "Zero-Downtime Unicorn" Just a Fantasy?

Zero unplanned downtime conversation has made its way to the board rooms now. According to the Vanson Bourne/ServiceMax survey of 450 IT decision-makers, zero unplanned downtime has become the top priority for 72% of the organizations. More importantly, boards are willing to approve additional funding, outside of the IT budget, to make this happen due to the pressure from business executives. But, just having the funding is not going to solve the problem. You need the right tools to help with that process.

In order to close the downtime gap, you need to know when your services will be going down or find out what is causing the problem as soon as a service goes down. The existing tools and data collection are mostly reactive measures, so the teams scramble after the service goes down. I discussed the need for root cause analysis and identifying issues before they happen in my earlier Forbes blog.

Why is it Complicated?

There are a few critical reasons why a lot of organizations are struggling with identifying the root cause of a problem:

1. IT has gotten more complex

2. IT budgets are getting crushed

3. Most IT organizations are siloed

4. There are not enough skilled IT personnel

5. Only reactive indicators are measured by ITOps teams

While all of the above is true, it doesn't have to be complicated. Implementing a properly designed AIOps solution can solve most of this. Keep in mind, having a good monitoring solution is not the same as having an AIOps solution. One is a reactive measure and the other is a proactive measure. Monitoring can tell you what went wrong, AIOps can potentially indicate something is about to go wrong.

A properly implemented AIOps platform can aggregate and analyze data collected by many tools: Application Performance Monitoring (APM), Network Performance Monitoring and Diagnostics (NPMD), Digital Experience Monitoring (DEM), IT Infrastructure Monitoring Tools (ITIM), Security Incident and Event Management (SIEM), and log tools, which make consolidation of events across the enterprise possible.

Avoiding Alert Fatigue

Unfortunately, today's complex IT systems produce a lot of events and alerts. Most organizations also have siloed implementations. For example, it is very common for a cloud implementation to use a different monitoring tool than an on-prem implementation of the same service. This leads to uncoordinated and unrelated alerts from multiple locations for the same incident.

A large enterprise we worked with had an issue of getting over a total of 100k events (alerts, network events, and service tickets) per single logical incident. This created "alert fatigue," with everyone chasing everything until they found the root cause. The first step was to reduce the large stream of low-level system events into a smaller number of logical incidents. With a combination of log structure discovery and parsing, periodicity detection, frequent pattern mining, and applying entropy-based encoding with a combination of temporal association detection and network topology graph analysis (yes, all the geeky stuff), we were able to reduce the volume of the event stream by 98%.

Imagine chasing a P1 in 100,000 single-siloed information pieces vs in 2,000 consolidated, grouped, and related events.


Demand More from Your CIO

The same ITIC survey suggests that 85% of corporations now demand a minimum of "four nines" of uptime (99.99%) for critical applications from their service providers. That is about 52 minutes of acceptable, unplanned downtime per year. Yet most CIOs struggle to provide the same quality of service and SLAs for their services to their businesses.

It is time the business executives demand the same "uptime" for their services from their CIOs that the CIOs demand from their service providers.

Andy Thurai is Founder and Principal of The Field CTO

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Getting to Zero Unplanned Downtime with AIOps

Andy Thurai
The Field CTO

Most business executives are worried about the competition taking them down. What they don't realize is, their own IT can do an equal amount of damage. Imagine this: if your rideshare app is constantly down, would you rather wait for it to come back up, or would you use the "other app?" Without realizing this fact, most organizations are one high-profile incident away from losing a lot of their customers.

A Silent Business Killer

With "digital native" businesses' complete reliance on IT, whether it is private data centers or cloud-based solutions, any long, unplanned downtime can kill a business quickly. The unplanned IT downtime is costing their businesses more than they think and the business executives are not fully aware of this.

Unplanned downtime can kill a business quickly

In a recent (2019) survey of 1000 businesses, ITIC estimated that for 86% of businesses, an hour of downtime will cost the business close to $300k an hour. And, for nearly 1/3 of the businesses, it will cost them between $1 million to $5 million. On average, an unplanned service outage lasts for four hours. And, on average, two outages are expected per enterprise, per year. All this means is that an enterprise can expect to lose between $2.5 to $40 million per year when the work stops due to an unplanned IT outage. And these numbers are going up by 30% YOY.

While these numbers (which are purely based on opportunity lost, lost employee productivity, and IT recovery and restoration costs) are mind-boggling, it doesn't even include any litigation, fines, penalties, non-compliance issues by regulatory bodies or even the brand hit, lost loyalty, or customer sat/attrition issues any enterprises will take due to unplanned downtime.

While large enterprises have specialized SWAT teams to reduce this impact, the smaller enterprises feel the brunt when such an event happens. When SRE teams, NOC/SOC teams and engineering teams are pulled into war rooms to solve the problem, the development/innovation and sometimes critical operational work come to a standstill. CIOs and other IT executives get involved until critical P1s are resolved, taking their time away from other strategic work.

Components of an IT Issue Resolution

Fixing any unplanned downtime consists of three major components:

1. Identifying the problem

2. Fixing the problem

3. Get the systems back up and running

While #2 can be minimized by having skilled IT staff, and #3 can be solved by a combination of automation and skilled IT staff, #1 is part art and part science. For most organizations, this is the hardest part and the silent killer. They spend too much time trying to find out the root cause of the problem. If you can't find the problem, you can't fix it. The very thought of having long, drawn-out war-room meetings, for critical P1 issues, should be any CIO's nightmare.

The efficiency of any ITOps team is measured by two major KPIs: MTBF (mean time between failures) and MTTR (mean time to repair). MTBF is a measure of how reliable your systems are, and MTTR is the true measure of how long your service is down, costing your business. The faster you find the problem, the faster you can solve it.

Is the "Zero-Downtime Unicorn" Just a Fantasy?

Zero unplanned downtime conversation has made its way to the board rooms now. According to the Vanson Bourne/ServiceMax survey of 450 IT decision-makers, zero unplanned downtime has become the top priority for 72% of the organizations. More importantly, boards are willing to approve additional funding, outside of the IT budget, to make this happen due to the pressure from business executives. But, just having the funding is not going to solve the problem. You need the right tools to help with that process.

In order to close the downtime gap, you need to know when your services will be going down or find out what is causing the problem as soon as a service goes down. The existing tools and data collection are mostly reactive measures, so the teams scramble after the service goes down. I discussed the need for root cause analysis and identifying issues before they happen in my earlier Forbes blog.

Why is it Complicated?

There are a few critical reasons why a lot of organizations are struggling with identifying the root cause of a problem:

1. IT has gotten more complex

2. IT budgets are getting crushed

3. Most IT organizations are siloed

4. There are not enough skilled IT personnel

5. Only reactive indicators are measured by ITOps teams

While all of the above is true, it doesn't have to be complicated. Implementing a properly designed AIOps solution can solve most of this. Keep in mind, having a good monitoring solution is not the same as having an AIOps solution. One is a reactive measure and the other is a proactive measure. Monitoring can tell you what went wrong, AIOps can potentially indicate something is about to go wrong.

A properly implemented AIOps platform can aggregate and analyze data collected by many tools: Application Performance Monitoring (APM), Network Performance Monitoring and Diagnostics (NPMD), Digital Experience Monitoring (DEM), IT Infrastructure Monitoring Tools (ITIM), Security Incident and Event Management (SIEM), and log tools, which make consolidation of events across the enterprise possible.

Avoiding Alert Fatigue

Unfortunately, today's complex IT systems produce a lot of events and alerts. Most organizations also have siloed implementations. For example, it is very common for a cloud implementation to use a different monitoring tool than an on-prem implementation of the same service. This leads to uncoordinated and unrelated alerts from multiple locations for the same incident.

A large enterprise we worked with had an issue of getting over a total of 100k events (alerts, network events, and service tickets) per single logical incident. This created "alert fatigue," with everyone chasing everything until they found the root cause. The first step was to reduce the large stream of low-level system events into a smaller number of logical incidents. With a combination of log structure discovery and parsing, periodicity detection, frequent pattern mining, and applying entropy-based encoding with a combination of temporal association detection and network topology graph analysis (yes, all the geeky stuff), we were able to reduce the volume of the event stream by 98%.

Imagine chasing a P1 in 100,000 single-siloed information pieces vs in 2,000 consolidated, grouped, and related events.


Demand More from Your CIO

The same ITIC survey suggests that 85% of corporations now demand a minimum of "four nines" of uptime (99.99%) for critical applications from their service providers. That is about 52 minutes of acceptable, unplanned downtime per year. Yet most CIOs struggle to provide the same quality of service and SLAs for their services to their businesses.

It is time the business executives demand the same "uptime" for their services from their CIOs that the CIOs demand from their service providers.

Andy Thurai is Founder and Principal of The Field CTO

Hot Topics

The Latest

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 ...

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...