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IT Monitoring Changing in 2018

Managing emerging technologies such as Cloud, microservices and containers and SDx are driving organizations to redefine their IT monitoring strategies, according to a new study titled 17 Areas Shaping the Information Technology Operations Market in 2018 from Digital Enterprise Journal (DEJ).

Additionally, the study based on insights from more than 2,500 organizations shows the increased importance of AI-enabled IT Operations, machine learning, and advanced analytics as companies deal with key performance challenges.

DEJ's Top Performing Organizations (TPO) Maturity framework shows that, in terms of IT Operations performance, the top 20% of organizations are experiencing significant operational and business benefits such as:

■ 2016 minutes less spent for Mean Time to Resolution (MTTR) per incident as compared to all other organizations

■ 2.5 times more IT resources available for transformation, growth and innovation for TPO in IT Operations

■ Percent of performance issues that are proactively detected: 76% - TPO; 52% - All others

Further Key Highlights:

■ 71% of organizations reported that their IT performance data is not actionable.

■ 79% reported that adding more IT staff to address IT incident management is not an effective strategy.

Overall, DEJ's research shows that the road to becoming a digital business runs through IT Operations, but IT Operations needs to be modernized to enable digital transformation.

“As new technologies are entering the enterprise at a rate that is much faster than in the past, IT Operations organizations cannot afford to play catch-up and have to develop a mix of capabilities that will allow them to create a competitive advantage for their business organizations,” states Bojan Simic, Founder and Chief Analyst of Digital Enterprise Journal. “These capabilities include providing context behind performance data, strong correlation and automation capabilities and embracing a proactive and service centric approach when managing IT Operations.”

The study also shows the importance of monitoring IT performance from the business perspective and creating a business case for the purchase of IT Operations solutions. 58% of organizations reported that the monitoring of IT performance from a user perspective is a strategic goal for IT transformation, while 47% reported that the inability to build a business case is the key obstacle for investing in IT Operations solutions.

The Latest

Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...

Part 3 reports on the current state of AI observability. Most experts agree: enterprises are moving faster with AI than they are with the operational discipline needed to run it safely ...

When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...

In this extensive 14-part series that will post over the next three weeks, experts across observability and AI will provide insight and opinions on the need for AI Observability, the challenges, the benefits, the current state, and predictions for the future ...

Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...

AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...

For more than a decade, the default infrastructure play has been simple. Move more workloads to the cloud, retire on-premises gear and treat the data center as a cost to shrink. That logic held while public cloud offered near-limitless capacity at predictable prices, and AI demand is now testing both halves of that assumption ...

Most enterprise IT leaders can tell you exactly how many applications are running across their organization. They can surface a dashboard showing telecom spend by region, pull a report on SaaS license utilization, or call up a real-time view of mobile device inventory. The data is there, and IT leaders have largely delivered on the promise of visibility. Yet, in most organizations, that visibility has not translated into business value ...

Government agencies are largely misjudging their level of AI governance as the technology permeates their organization, according to Racing to Deploy: How Public Sector AI Adoption is Moving Faster Than the Foundations Needed to Support It, a new report from SolarWinds ...

IT Monitoring Changing in 2018

Managing emerging technologies such as Cloud, microservices and containers and SDx are driving organizations to redefine their IT monitoring strategies, according to a new study titled 17 Areas Shaping the Information Technology Operations Market in 2018 from Digital Enterprise Journal (DEJ).

Additionally, the study based on insights from more than 2,500 organizations shows the increased importance of AI-enabled IT Operations, machine learning, and advanced analytics as companies deal with key performance challenges.

DEJ's Top Performing Organizations (TPO) Maturity framework shows that, in terms of IT Operations performance, the top 20% of organizations are experiencing significant operational and business benefits such as:

■ 2016 minutes less spent for Mean Time to Resolution (MTTR) per incident as compared to all other organizations

■ 2.5 times more IT resources available for transformation, growth and innovation for TPO in IT Operations

■ Percent of performance issues that are proactively detected: 76% - TPO; 52% - All others

Further Key Highlights:

■ 71% of organizations reported that their IT performance data is not actionable.

■ 79% reported that adding more IT staff to address IT incident management is not an effective strategy.

Overall, DEJ's research shows that the road to becoming a digital business runs through IT Operations, but IT Operations needs to be modernized to enable digital transformation.

“As new technologies are entering the enterprise at a rate that is much faster than in the past, IT Operations organizations cannot afford to play catch-up and have to develop a mix of capabilities that will allow them to create a competitive advantage for their business organizations,” states Bojan Simic, Founder and Chief Analyst of Digital Enterprise Journal. “These capabilities include providing context behind performance data, strong correlation and automation capabilities and embracing a proactive and service centric approach when managing IT Operations.”

The study also shows the importance of monitoring IT performance from the business perspective and creating a business case for the purchase of IT Operations solutions. 58% of organizations reported that the monitoring of IT performance from a user perspective is a strategic goal for IT transformation, while 47% reported that the inability to build a business case is the key obstacle for investing in IT Operations solutions.

The Latest

Part 4 outlines the challenges enterprise face when adopting AI observability. The main challenge is that AI complexity compounds at every stage of maturity. LLM-based applications introduce new behavior, dependencies, and quality considerations, while Agentic AI adds further failure modes as systems make decisions and take actions ...

Part 3 reports on the current state of AI observability. Most experts agree: enterprises are moving faster with AI than they are with the operational discipline needed to run it safely ...

When discussing AI Observability, one of the first questions that arises: Is this just an extension of traditional observability or is this a whole new type of tool? Part 2 compares traditional observability with AI observability ...

In this extensive 14-part series that will post over the next three weeks, experts across observability and AI will provide insight and opinions on the need for AI Observability, the challenges, the benefits, the current state, and predictions for the future ...

Amid rising complexity, organizations are moving quickly toward agent-driven operations: AgenticOps, according to The Impact of Agentic AI on Network Operations, a new report from Cisco ...

AI, automation, and enterprise software give organizations an extraordinary amount of leverage. Work that once required hours can happen in minutes. Information buried across systems can be analyzed almost instantly. Complex workflows can be coordinated across teams with far less manual intervention. That leverage creates a temptation to start with the technology ...

Everyone wants to talk about models. Compute clusters. Benchmark scores that climb a fraction of a point and make headlines anyway. It's an easy conversation to have because it's measurable. But it's also increasingly beside the point ...

For more than a decade, the default infrastructure play has been simple. Move more workloads to the cloud, retire on-premises gear and treat the data center as a cost to shrink. That logic held while public cloud offered near-limitless capacity at predictable prices, and AI demand is now testing both halves of that assumption ...

Most enterprise IT leaders can tell you exactly how many applications are running across their organization. They can surface a dashboard showing telecom spend by region, pull a report on SaaS license utilization, or call up a real-time view of mobile device inventory. The data is there, and IT leaders have largely delivered on the promise of visibility. Yet, in most organizations, that visibility has not translated into business value ...

Government agencies are largely misjudging their level of AI governance as the technology permeates their organization, according to Racing to Deploy: How Public Sector AI Adoption is Moving Faster Than the Foundations Needed to Support It, a new report from SolarWinds ...