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3 Reasons Why Full-Stack Observability Is Key to Business Growth

Gregg Ostrowski
AppDynamics

The past couple years fostered an unprecedented expansion of digital transformation initiatives and projects across nearly every industry. In order to maintain "business as usual" during the world's transition to being fully remote or hybrid, companies had to implement new digital services, or update existing ones, to allow transactions to take place online versus in person. As a result, companies' digital strategies quickly grew in significance, playing a larger role in the ultimate success of the business.

In a study of 1,200 global IT leaders, Cisco AppDynamics found that as applications have become a critical part of daily life, 98% of technologists believe it is increasingly important to connect visibility across the entire IT stack. With a higher dependency on applications, consumer expectations around the performance, reliability and innovative features of digital experiences have skyrocketed and without tools like full-stack observability in place, companies risk facing competitive disadvantages like spiraling complexity and productivity issues.

This evolution has increased the pressure on brands to make certain their digital services are performing well, and to recognize that downtime is not an option. Meanwhile, through the increased adoption of cloud services, the application topology has grown in complexity. This makes the need to identify and quickly fix anomalies that could lead to poor performance more important than ever. As a consequence, many enterprises are finding that traditional monitoring doesn't go far enough. Full-stack observability is growing in prominence as IT teams seek to easily manage application performance, solve complexity across their entire IT stack, and review each of these functions through a business lens. This article explores three key areas to consider when implementing a full-stack observability solution.

1. Make IT Performance Monitoring Easy

Companies' adoption and expansion of digital services has led to larger, more complex IT stacks, which must be monitored round-the-clock for any changes to performance that could impact customers. While most IT teams have some form of monitoring tools in place to automate this task, increased complexity has created more inefficient procedures and challenges for technologists, making it more difficult to grow the business. In fact, 70 percent of technologists are concerned that their organization is now behind industry peers in implementing observability solutions. It can be difficult to find time to innovate and grow as maintaining the performance of digital services is a full-time job itself.

With full-stack observability, companies don't have to choose between growing or maintaining app performance. Instead, they can take advantage of its sophisticated monitoring to both manage even the most complex stacks and enable room for growth. Full-stack observability automatically centralizes and correlates application performance analytics across the entire IT stack, ultimately providing companies with in-depth visibility into the behavior, performance and health of their digital services. Therefore, companies are not only alleviated of having to strictly manage the monitoring process, but they're also presented with advanced performance data that can inform future innovation and growth plans.  

2. Tackle Discrepancies in the IT Stack

In addition to in-depth insights, full-stack observability provides real-time visibility across the entire IT stack and helps technologists quickly identify and solve any discrepancies in performance, as well as pinpoint the location and cause of any incidents so companies can efficiently address the issue.

93% of technologists recognize that there is more work to be done to deploy full-stack observability within their organization in order to address complexity by easily identifying and fixing root causes of performance issues, such as lags, outages or crashes. With digital services continuing to play a significant role in daily life activities, users are more likely to notice a performance lag or outage. Consumers expect a seamless digital experience and when a company misses the mark, they risk adverse effects on brand loyalty and reputation, with the chance of never getting it back.

By deploying a full-stack observability approach, companies can avoid these strikes against their business and get ahead of performance outages before they directly impact consumers.

3. Put a Business Lens on IT Performance

When looking to maximize business growth and success during this period of heightened digital transformation, companies should implement a digital strategy that can work with, and support business goals. This is why an approach that aligns full-stack observability with business context is key. Having a business lens enables technologists to understand what the desired business outcome is and where to effectively prioritize their efforts to what impacts the bottom line.

The ever-increasing amount of data that can be collected when using full-stack observability might seem daunting to make sense of. However, full-stack observability can be combined with real-time business metrics to translate what was once an overwhelming amount of data into comprehensible KPIs. In other words, full-stack observability with business context enables companies to digest the IT performance through a business lens so they can easily prioritize performance areas that are directly impacting their bottom line.

Today, the role digital services play in navigating daily life continues to be on an upward trajectory. In order for companies to drive growth and success across their business, their tech and business strategies need to be tightly aligned and focused on a common goal. As companies continue to be tasked with maintaining the performance of digital services, while also being expected to come up with new, innovative ways to grow the business, there is an eminent need for a holistic approach. Full-stack observability with business context is a clear solution that is key for overall business growth and success, as it enables companies to monitor performance across the IT stack and easily identify and address any performance anomalies, all while tying back to and encouraging growth for a company's bottom line.

Gregg Ostrowski is CTO Advisor at Cisco AppDynamics

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3 Reasons Why Full-Stack Observability Is Key to Business Growth

Gregg Ostrowski
AppDynamics

The past couple years fostered an unprecedented expansion of digital transformation initiatives and projects across nearly every industry. In order to maintain "business as usual" during the world's transition to being fully remote or hybrid, companies had to implement new digital services, or update existing ones, to allow transactions to take place online versus in person. As a result, companies' digital strategies quickly grew in significance, playing a larger role in the ultimate success of the business.

In a study of 1,200 global IT leaders, Cisco AppDynamics found that as applications have become a critical part of daily life, 98% of technologists believe it is increasingly important to connect visibility across the entire IT stack. With a higher dependency on applications, consumer expectations around the performance, reliability and innovative features of digital experiences have skyrocketed and without tools like full-stack observability in place, companies risk facing competitive disadvantages like spiraling complexity and productivity issues.

This evolution has increased the pressure on brands to make certain their digital services are performing well, and to recognize that downtime is not an option. Meanwhile, through the increased adoption of cloud services, the application topology has grown in complexity. This makes the need to identify and quickly fix anomalies that could lead to poor performance more important than ever. As a consequence, many enterprises are finding that traditional monitoring doesn't go far enough. Full-stack observability is growing in prominence as IT teams seek to easily manage application performance, solve complexity across their entire IT stack, and review each of these functions through a business lens. This article explores three key areas to consider when implementing a full-stack observability solution.

1. Make IT Performance Monitoring Easy

Companies' adoption and expansion of digital services has led to larger, more complex IT stacks, which must be monitored round-the-clock for any changes to performance that could impact customers. While most IT teams have some form of monitoring tools in place to automate this task, increased complexity has created more inefficient procedures and challenges for technologists, making it more difficult to grow the business. In fact, 70 percent of technologists are concerned that their organization is now behind industry peers in implementing observability solutions. It can be difficult to find time to innovate and grow as maintaining the performance of digital services is a full-time job itself.

With full-stack observability, companies don't have to choose between growing or maintaining app performance. Instead, they can take advantage of its sophisticated monitoring to both manage even the most complex stacks and enable room for growth. Full-stack observability automatically centralizes and correlates application performance analytics across the entire IT stack, ultimately providing companies with in-depth visibility into the behavior, performance and health of their digital services. Therefore, companies are not only alleviated of having to strictly manage the monitoring process, but they're also presented with advanced performance data that can inform future innovation and growth plans.  

2. Tackle Discrepancies in the IT Stack

In addition to in-depth insights, full-stack observability provides real-time visibility across the entire IT stack and helps technologists quickly identify and solve any discrepancies in performance, as well as pinpoint the location and cause of any incidents so companies can efficiently address the issue.

93% of technologists recognize that there is more work to be done to deploy full-stack observability within their organization in order to address complexity by easily identifying and fixing root causes of performance issues, such as lags, outages or crashes. With digital services continuing to play a significant role in daily life activities, users are more likely to notice a performance lag or outage. Consumers expect a seamless digital experience and when a company misses the mark, they risk adverse effects on brand loyalty and reputation, with the chance of never getting it back.

By deploying a full-stack observability approach, companies can avoid these strikes against their business and get ahead of performance outages before they directly impact consumers.

3. Put a Business Lens on IT Performance

When looking to maximize business growth and success during this period of heightened digital transformation, companies should implement a digital strategy that can work with, and support business goals. This is why an approach that aligns full-stack observability with business context is key. Having a business lens enables technologists to understand what the desired business outcome is and where to effectively prioritize their efforts to what impacts the bottom line.

The ever-increasing amount of data that can be collected when using full-stack observability might seem daunting to make sense of. However, full-stack observability can be combined with real-time business metrics to translate what was once an overwhelming amount of data into comprehensible KPIs. In other words, full-stack observability with business context enables companies to digest the IT performance through a business lens so they can easily prioritize performance areas that are directly impacting their bottom line.

Today, the role digital services play in navigating daily life continues to be on an upward trajectory. In order for companies to drive growth and success across their business, their tech and business strategies need to be tightly aligned and focused on a common goal. As companies continue to be tasked with maintaining the performance of digital services, while also being expected to come up with new, innovative ways to grow the business, there is an eminent need for a holistic approach. Full-stack observability with business context is a clear solution that is key for overall business growth and success, as it enables companies to monitor performance across the IT stack and easily identify and address any performance anomalies, all while tying back to and encouraging growth for a company's bottom line.

Gregg Ostrowski is CTO Advisor at Cisco AppDynamics

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If AI is the engine of a modern organization, then data engineering is the road system beneath it. You can build the most powerful engine in the world, but without paved roads, traffic signals, and bridges that can support its weight, it will stall. In many enterprises, the engine is ready. The roads are not ...

In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...

In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...

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 ...