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Why Full-Stack Observability Should Be a Priority This Year

Angie Mistretta
AppDynamics

One year ago, the world shifted as a result of the COVID-19 pandemic, sending companies into rapid digital transformation in order to adapt to the "next normal." Technologists were placed at the forefront of sustaining their companies' business, which ultimately put them under a considerable amount of strain as they navigated how to implement and maintain technologies, while facing increased demand from end users.

As we move into another year, technologists are concerned this rise in IT complexity will continue to pose significant challenges. In fact, our 2021 edition of the Agents of Transformation report found that 75 percent of global technologists believe the pandemic created more IT complexity than ever before and they are struggling to manage overwhelming "data noise."


Gaining Visibility into the IT Estate with Full-Stack Observability

After making a quick pivot to increase focus on their digital strategies, companies are now looking for ways to improve efficiency and ensure their organization's long-term success. Notably, full-stack observability has been a common need across the industry — our report uncovered about three quarters of technologists recognize that the inability to connect full-stack observability with business outcomes will be detrimental to their business in 2021.

The benefit of full-stack observability is that it allows IT teams to monitor an entire IT stack, including everything from customer-facing applications to core network and infrastructure. This approach ensures your organization will have full visibility into all your applications, teams and tools, and that you can quickly identify and address performance issues before they negatively impact end users.

But, full-stack observability alone doesn't give your teams everything they need to be successful. They also need to know how all of the data they are now receiving impacts the business. Adding business context enables your team to observe what matters most and prioritize resources accordingly.

Contextualizing IT Performance Insights with Real-Time Business Data

As we saw with the pandemic, when consumer demand is unexpectedly high and requires an instant response, implementing a "quick fix" such as moving all of the company's extra data to the cloud can sometimes be the best, or only, solution at that time. However, without monitoring or automation tools to support these moves, the fix will likely provide only short-term success and eventually put additional pressure on IT teams who are monitoring applications' performances on their own.

As discovered in our report, 76 percent of technologists acknowledge that since they are now experiencing heightened levels of complexity, they can no longer afford to rely on gut instinct with technology performance, they need accurate, real-time data. The lack of support can also lead to a gap in how a company manages its IT insights versus its business insights. To foster long-term success, companies should look into gaining full visibility across the business so any decisions made on the IT side are targeted at improving both the IT team and overall business performance.

The last year presented many new challenges for business and IT teams and showed everyone the importance of being able to quickly and decisively make adjustments to their digital strategy while also being able to identify, understand and resolve bottlenecks before customers are affected. Nearly 96 percent of technologists today recognize the significance of full-stack observability and its direct link to business performance and consider it essential to deliver first-class digital experiences. To support technologists working behind the scenes, companies should implement full-stack observability sooner rather than later to improve customer experiences and overall business performance.

Angie Mistretta is CMO of AppDynamics, a part of Cisco

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Why Full-Stack Observability Should Be a Priority This Year

Angie Mistretta
AppDynamics

One year ago, the world shifted as a result of the COVID-19 pandemic, sending companies into rapid digital transformation in order to adapt to the "next normal." Technologists were placed at the forefront of sustaining their companies' business, which ultimately put them under a considerable amount of strain as they navigated how to implement and maintain technologies, while facing increased demand from end users.

As we move into another year, technologists are concerned this rise in IT complexity will continue to pose significant challenges. In fact, our 2021 edition of the Agents of Transformation report found that 75 percent of global technologists believe the pandemic created more IT complexity than ever before and they are struggling to manage overwhelming "data noise."


Gaining Visibility into the IT Estate with Full-Stack Observability

After making a quick pivot to increase focus on their digital strategies, companies are now looking for ways to improve efficiency and ensure their organization's long-term success. Notably, full-stack observability has been a common need across the industry — our report uncovered about three quarters of technologists recognize that the inability to connect full-stack observability with business outcomes will be detrimental to their business in 2021.

The benefit of full-stack observability is that it allows IT teams to monitor an entire IT stack, including everything from customer-facing applications to core network and infrastructure. This approach ensures your organization will have full visibility into all your applications, teams and tools, and that you can quickly identify and address performance issues before they negatively impact end users.

But, full-stack observability alone doesn't give your teams everything they need to be successful. They also need to know how all of the data they are now receiving impacts the business. Adding business context enables your team to observe what matters most and prioritize resources accordingly.

Contextualizing IT Performance Insights with Real-Time Business Data

As we saw with the pandemic, when consumer demand is unexpectedly high and requires an instant response, implementing a "quick fix" such as moving all of the company's extra data to the cloud can sometimes be the best, or only, solution at that time. However, without monitoring or automation tools to support these moves, the fix will likely provide only short-term success and eventually put additional pressure on IT teams who are monitoring applications' performances on their own.

As discovered in our report, 76 percent of technologists acknowledge that since they are now experiencing heightened levels of complexity, they can no longer afford to rely on gut instinct with technology performance, they need accurate, real-time data. The lack of support can also lead to a gap in how a company manages its IT insights versus its business insights. To foster long-term success, companies should look into gaining full visibility across the business so any decisions made on the IT side are targeted at improving both the IT team and overall business performance.

The last year presented many new challenges for business and IT teams and showed everyone the importance of being able to quickly and decisively make adjustments to their digital strategy while also being able to identify, understand and resolve bottlenecks before customers are affected. Nearly 96 percent of technologists today recognize the significance of full-stack observability and its direct link to business performance and consider it essential to deliver first-class digital experiences. To support technologists working behind the scenes, companies should implement full-stack observability sooner rather than later to improve customer experiences and overall business performance.

Angie Mistretta is CMO of AppDynamics, a part of Cisco

Hot Topics

The Latest

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 ...

Many organizations assumed their infrastructure strategy was settled. It had been implemented, optimized and built into long-term plans. Recent changes in technology and vendor consolidation are forcing a second look. Cloud outages and licensing changes have exposed how much dependency exists on a small number of platforms. As a result, organizations are reevaluating whether those decisions still hold up under current conditions ...

Edge AI is strategically embedded in core IT and infrastructure spending across industries, according to the 2026 Edge AI Survey from ZEDEDA. The research shows that 83% of C-suite and IT executive respondents say edge AI is important to their core business strategy ...