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Flying Blind — The 2013 IT Operations Quotient Report

Sasha Gilenson

IT Operations is now overwhelmed — by the volume, velocity and variety of change and configuration data, lacking insight or actionable information, all making change and configuration problems a chronic pain.

As shown by recent surveys at the Gartner Data Center Summit and ServiceNow Knowledge13 conferences, where Evolven surveyed over 300 IT Operations professionals asking questions critical to IT operations management, 84% of IT professionals said that they want to significantly improve their IT operations management.

The 2013 IT OQ (Operations Quotient) Report provides a good indication to IT executives as to whether IT ops investments have yielded desired results, using the IT Operations Quotient (OQ), a metric for evaluating operational ability to support existing business services and incoming business requirements.

When an Incident Occurs, Can You Quickly Know What Changed?

Only 7% of the professionals surveys indicated that, using their current IT management tools, they could quickly identify what changed in order to respond to problems and incidents.

The first question IT operations asks themselves when an incident occurs is "what changed?" Due to the complexity and dynamics taking place in the modern data center, with overwhelming configuration data and frequent changes, this question has become quite formidable.

Between applications, environments, and individual instances, mistakes and unauthorized changes happen, demanding that IT ops spend significant amounts of time managing configuration values.

Traditional IT management tools were not designed to deal with the complexity and dynamics of the modern data center. These tools have not been automated to collect data down to granular details, analyzing all changes and consolidating information to extract meaningful information from the sea of raw change and configuration data.

Without systems to manage and organize this growth, IT will drown in its own data.

Can You Automatically Validate that Your Release Deployed Accurately?

Only 8% of the participants surveyed agreed that they could currently automatically validate the accuracy of their deployments. Available release management tools are unprepared for one-off changes or changes that do not follow policy.

IT organizations regularly transition changes to production environments, checking changes throughout a set of pre-production environments.

Now IT is under even more pressure. To meet business requirements, application deployments have accelerated and software deployment schedules have driven up high-paced change activity. The increasingly agile nature of application and infrastructure change requests, leaves IT operations at a loss as they are inundated by change requests that run the gamut from the critical and high priority to the minor and unimportant.

With a typical environment having thousands of different system configuration parameters, any little change can impact performance. So it’s not surprising to see many companies going through painful stabilization periods after a release, as well as production outages.

Even when using automated tools for deployment, the lack of detailed visibility into the release means IT ops can’t ensure accurate, error-free deployments.

Can You Quickly Identify the Incident’s Root Cause?

As shown in this survey, the vast majority of IT professionals surveyed concurred that they lack the capabilities to quickly identify an incident’s root cause. IT organizations find themselves challenged when assessing system failure and tracking down the root cause, such as if a patch wasn't deployed or a server failed.

Any minute misconfiguration or omission of a single configuration parameter can quickly lead to an incident with high impact. With an infinite number of these configuration parameters in play when an environment incident hits, finding the root cause consumes both precious time and manpower, making MTTR woefully high in most organizations.

The root cause of downtime and incidents often start at the most granular level of configuration changes where today's configuration management and change management tools don't provide visibility. The different groups in organizations, like IT Development, Support, and Operations, tend to point the finger of blame for issues, and fail to diagnose or deal with the root cause of the problem.

After a major incident, root cause analysis should focus on root cause of the failure in order to not only resolve the incident but to head off a recurrence. Even when IT teams manage to suppress a failure, and operations can return to "normal", the true root cause may still remain unresolved, leaving the organization exposed to further chaos.

Can You Automatically Verify the Consistency of Your Environments?

From our survey, only 5% of the respondents felt that currently they can automatically verify the consistency of their environments, where they need to go into the fine, granular details and identify the make-up of even minor changes, having to process the enormous amounts of configuration data, for verifying the consistency between servers and environments.

As IT organizations regularly transition changes to production environments, IT teams need to check changes throughout a set of pre-production environments that can include system test, performance test, UAT, staging, etc (changes are also mirrored in a Disaster Recovery environment). IT has sought to diversify their workloads, spreading deployments over multiple IT environments to mitigate risk, yet also doubling complexity.

The high volumes of changes means that not all changes consistently make their way to all environments (pre-prod, prod, DR). The configuration parameters must be validated for consistency in real-time.

IT Operations Analytics Helps

With performance at risk from any disruptions to stability, IT teams need to know exactly what has changed in an environment.

Managing IT environments with intelligent automated analytics will drive more sophisticated proactive processes like comparing environment states, validating releases, and verifying consistency of changes,helping to prevent or identify critical issues. So rather than continue to feed bloated system tools, IT Operations should strive to simplify and implement configuration management based on IT Operations Analytics, and turn the situation around from what can’t be managed to being what can be done about performance and availability.

Sasha Gilenson is the Founder and CEO of Evolven Software.

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Flying Blind — The 2013 IT Operations Quotient Report

Sasha Gilenson

IT Operations is now overwhelmed — by the volume, velocity and variety of change and configuration data, lacking insight or actionable information, all making change and configuration problems a chronic pain.

As shown by recent surveys at the Gartner Data Center Summit and ServiceNow Knowledge13 conferences, where Evolven surveyed over 300 IT Operations professionals asking questions critical to IT operations management, 84% of IT professionals said that they want to significantly improve their IT operations management.

The 2013 IT OQ (Operations Quotient) Report provides a good indication to IT executives as to whether IT ops investments have yielded desired results, using the IT Operations Quotient (OQ), a metric for evaluating operational ability to support existing business services and incoming business requirements.

When an Incident Occurs, Can You Quickly Know What Changed?

Only 7% of the professionals surveys indicated that, using their current IT management tools, they could quickly identify what changed in order to respond to problems and incidents.

The first question IT operations asks themselves when an incident occurs is "what changed?" Due to the complexity and dynamics taking place in the modern data center, with overwhelming configuration data and frequent changes, this question has become quite formidable.

Between applications, environments, and individual instances, mistakes and unauthorized changes happen, demanding that IT ops spend significant amounts of time managing configuration values.

Traditional IT management tools were not designed to deal with the complexity and dynamics of the modern data center. These tools have not been automated to collect data down to granular details, analyzing all changes and consolidating information to extract meaningful information from the sea of raw change and configuration data.

Without systems to manage and organize this growth, IT will drown in its own data.

Can You Automatically Validate that Your Release Deployed Accurately?

Only 8% of the participants surveyed agreed that they could currently automatically validate the accuracy of their deployments. Available release management tools are unprepared for one-off changes or changes that do not follow policy.

IT organizations regularly transition changes to production environments, checking changes throughout a set of pre-production environments.

Now IT is under even more pressure. To meet business requirements, application deployments have accelerated and software deployment schedules have driven up high-paced change activity. The increasingly agile nature of application and infrastructure change requests, leaves IT operations at a loss as they are inundated by change requests that run the gamut from the critical and high priority to the minor and unimportant.

With a typical environment having thousands of different system configuration parameters, any little change can impact performance. So it’s not surprising to see many companies going through painful stabilization periods after a release, as well as production outages.

Even when using automated tools for deployment, the lack of detailed visibility into the release means IT ops can’t ensure accurate, error-free deployments.

Can You Quickly Identify the Incident’s Root Cause?

As shown in this survey, the vast majority of IT professionals surveyed concurred that they lack the capabilities to quickly identify an incident’s root cause. IT organizations find themselves challenged when assessing system failure and tracking down the root cause, such as if a patch wasn't deployed or a server failed.

Any minute misconfiguration or omission of a single configuration parameter can quickly lead to an incident with high impact. With an infinite number of these configuration parameters in play when an environment incident hits, finding the root cause consumes both precious time and manpower, making MTTR woefully high in most organizations.

The root cause of downtime and incidents often start at the most granular level of configuration changes where today's configuration management and change management tools don't provide visibility. The different groups in organizations, like IT Development, Support, and Operations, tend to point the finger of blame for issues, and fail to diagnose or deal with the root cause of the problem.

After a major incident, root cause analysis should focus on root cause of the failure in order to not only resolve the incident but to head off a recurrence. Even when IT teams manage to suppress a failure, and operations can return to "normal", the true root cause may still remain unresolved, leaving the organization exposed to further chaos.

Can You Automatically Verify the Consistency of Your Environments?

From our survey, only 5% of the respondents felt that currently they can automatically verify the consistency of their environments, where they need to go into the fine, granular details and identify the make-up of even minor changes, having to process the enormous amounts of configuration data, for verifying the consistency between servers and environments.

As IT organizations regularly transition changes to production environments, IT teams need to check changes throughout a set of pre-production environments that can include system test, performance test, UAT, staging, etc (changes are also mirrored in a Disaster Recovery environment). IT has sought to diversify their workloads, spreading deployments over multiple IT environments to mitigate risk, yet also doubling complexity.

The high volumes of changes means that not all changes consistently make their way to all environments (pre-prod, prod, DR). The configuration parameters must be validated for consistency in real-time.

IT Operations Analytics Helps

With performance at risk from any disruptions to stability, IT teams need to know exactly what has changed in an environment.

Managing IT environments with intelligent automated analytics will drive more sophisticated proactive processes like comparing environment states, validating releases, and verifying consistency of changes,helping to prevent or identify critical issues. So rather than continue to feed bloated system tools, IT Operations should strive to simplify and implement configuration management based on IT Operations Analytics, and turn the situation around from what can’t be managed to being what can be done about performance and availability.

Sasha Gilenson is the Founder and CEO of Evolven Software.

Hot Topics

The Latest

AI is the catalyst for significant investment in data teams as enterprises require higher-quality data to power their AI applications, according to the State of Analytics Engineering Report from dbt Labs ...

Misaligned architecture can lead to business consequences, with 93% of respondents reporting negative outcomes such as service disruptions, high operational costs and security challenges ...

A Gartner analyst recently suggested that GenAI tools could create 25% time savings for network operational teams. Where might these time savings come from? How are GenAI tools helping NetOps teams today, and what other tasks might they take on in the future as models continue improving? In general, these savings come from automating or streamlining manual NetOps tasks ...

IT and line-of-business teams are increasingly aligned in their efforts to close the data gap and drive greater collaboration to alleviate IT bottlenecks and offload growing demands on IT teams, according to The 2025 Automation Benchmark Report: Insights from IT Leaders on Enterprise Automation & the Future of AI-Driven Businesses from Jitterbit ...

A large majority (86%) of data management and AI decision makers cite protecting data privacy as a top concern, with 76% of respondents citing ROI on data privacy and AI initiatives across their organization, according to a new Harris Poll from Collibra ...

According to Gartner, Inc. the following six trends will shape the future of cloud over the next four years, ultimately resulting in new ways of working that are digital in nature and transformative in impact ...

2020 was the equivalent of a wedding with a top-shelf open bar. As businesses scrambled to adjust to remote work, digital transformation accelerated at breakneck speed. New software categories emerged overnight. Tech stacks ballooned with all sorts of SaaS apps solving ALL the problems — often with little oversight or long-term integration planning, and yes frequently a lot of duplicated functionality ... But now the music's faded. The lights are on. Everyone from the CIO to the CFO is checking the bill. Welcome to the Great SaaS Hangover ...

Regardless of OpenShift being a scalable and flexible software, it can be a pain to monitor since complete visibility into the underlying operations is not guaranteed ... To effectively monitor an OpenShift environment, IT administrators should focus on these five key elements and their associated metrics ...

An overwhelming majority of IT leaders (95%) believe the upcoming wave of AI-powered digital transformation is set to be the most impactful and intensive seen thus far, according to The Science of Productivity: AI, Adoption, And Employee Experience, a new report from Nexthink ...

Overall outage frequency and the general level of reported severity continue to decline, according to the Outage Analysis 2025 from Uptime Institute. However, cyber security incidents are on the rise and often have severe, lasting impacts ...