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Digital Intelligence - Why Traditional APM Tools Aren't Sufficient

Larry Dragich

The need for an improved end-user-experience starts with Digital Intelligence. That means IT Leaders need to understand and make decisions on what is happening within the ecosystem they support.

Digital Intelligence is the ability to perceive information, (i.e. from monitoring tools) and retain it as knowledge (aka. Big Data) to be applied towards adaptive behaviors (i.e. Machine Learning and/or AI) within the environment (e.g. Prod, Dev, etc.).

Although, using disparate monitoring tools to aggregate application and infrastructure metrics for a correlated end-to-end view can be difficult to manage.

Collecting the alerts and events from multiple tool sets creates a lot of noise for the support staff who then need to make decisions and create some type of repeatable processes for their teams to follow.

These processes can become convoluted and outdated quickly. For Example:

I can recall a time when I was leading a new team and we were all in an intense post mortem meeting looking for root cause from a major event that recently occurred.

While reviewing the IT processes that were in place for all the support teams, it came down to a critical process that we thought was missing. That's when one of my peers spoke up and said with conviction, "We already have a process in place for that!"

"…it's FULLY documented, THOROUGHLY understood, and UNIVERSALLY ignored!"

His witty delivery brought levity to the room, and everyone was able to take a deep breath and relax.

If no one is following a critical IT Process, then maybe it's time for a change

Although, when you think about it on a more serious note it does ring true. If no one is following a critical IT Process, then maybe it's time for a change. The process needs to make sense to the team and become something they can benefit from. The same goes for tool adoption.

Today most savvy IT Leaders are striving to partner with the business and attain complete visibility with the critical business applications they support. At a high level they are looking to collect Digital Intelligence about their business applications and the infrastructure it runs on, whether it's in the cloud or on-prem.

However, meaningful metrics can be difficult to obtain without a specific focus on business impact (transactions) and a concise way to collect them. Since the IT processes wrapped around those metrics are just as critical as the technology itself, it's imperative to have a strategy and communicate it frequently.

Digital Intelligence comes from assimilating multiple Application and Infrastructure events into a cross-domain layer designed for proactive rather than reactive IT Management and Planning. It is also about crafting simple and clean IT support processes with predictable outcomes.

When done correctly with the right tool selection and process development, an Enterprise Monitoring solution using Digital Intelligence can become a communication conduit for supporting the Business, Development and Operations.

Although, keep in mind despite what the most advanced technologies can provide, the best processes in place are the ones that are easy to follow and embraced by the teams that need them, not the ones UNIVERSALLY ignored!

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As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

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 ...

Digital Intelligence - Why Traditional APM Tools Aren't Sufficient

Larry Dragich

The need for an improved end-user-experience starts with Digital Intelligence. That means IT Leaders need to understand and make decisions on what is happening within the ecosystem they support.

Digital Intelligence is the ability to perceive information, (i.e. from monitoring tools) and retain it as knowledge (aka. Big Data) to be applied towards adaptive behaviors (i.e. Machine Learning and/or AI) within the environment (e.g. Prod, Dev, etc.).

Although, using disparate monitoring tools to aggregate application and infrastructure metrics for a correlated end-to-end view can be difficult to manage.

Collecting the alerts and events from multiple tool sets creates a lot of noise for the support staff who then need to make decisions and create some type of repeatable processes for their teams to follow.

These processes can become convoluted and outdated quickly. For Example:

I can recall a time when I was leading a new team and we were all in an intense post mortem meeting looking for root cause from a major event that recently occurred.

While reviewing the IT processes that were in place for all the support teams, it came down to a critical process that we thought was missing. That's when one of my peers spoke up and said with conviction, "We already have a process in place for that!"

"…it's FULLY documented, THOROUGHLY understood, and UNIVERSALLY ignored!"

His witty delivery brought levity to the room, and everyone was able to take a deep breath and relax.

If no one is following a critical IT Process, then maybe it's time for a change

Although, when you think about it on a more serious note it does ring true. If no one is following a critical IT Process, then maybe it's time for a change. The process needs to make sense to the team and become something they can benefit from. The same goes for tool adoption.

Today most savvy IT Leaders are striving to partner with the business and attain complete visibility with the critical business applications they support. At a high level they are looking to collect Digital Intelligence about their business applications and the infrastructure it runs on, whether it's in the cloud or on-prem.

However, meaningful metrics can be difficult to obtain without a specific focus on business impact (transactions) and a concise way to collect them. Since the IT processes wrapped around those metrics are just as critical as the technology itself, it's imperative to have a strategy and communicate it frequently.

Digital Intelligence comes from assimilating multiple Application and Infrastructure events into a cross-domain layer designed for proactive rather than reactive IT Management and Planning. It is also about crafting simple and clean IT support processes with predictable outcomes.

When done correctly with the right tool selection and process development, an Enterprise Monitoring solution using Digital Intelligence can become a communication conduit for supporting the Business, Development and Operations.

Although, keep in mind despite what the most advanced technologies can provide, the best processes in place are the ones that are easy to follow and embraced by the teams that need them, not the ones UNIVERSALLY ignored!

Hot Topics

The Latest

As businesses increasingly rely on high-performance applications to deliver seamless user experiences, the demand for fast, reliable, and scalable data storage systems has never been greater. Redis — an open-source, in-memory data structure store — has emerged as a popular choice for use cases ranging from caching to real-time analytics. But with great performance comes the need for vigilant monitoring ...

Kubernetes was not initially designed with AI's vast resource variability in mind, and the rapid rise of AI has exposed Kubernetes limitations, particularly when it comes to cost and resource efficiency. Indeed, AI workloads differ from traditional applications in that they require a staggering amount and variety of compute resources, and their consumption is far less consistent than traditional workloads ... Considering the speed of AI innovation, teams cannot afford to be bogged down by these constant infrastructure concerns. A solution is needed ...

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 ...