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IT Burnout is Real - Here's How Full-Stack Observability Can Help

Angie Mistretta
AppDynamics

You might have heard of the phrase "canary in the coal mine," which refers to an indicator of potential danger or failure ahead. In the tech industry, these potential failures could be catastrophic, as anomalies in applications negatively impact the performance, customer experience and business outcomes. As we have seen during this digital transformation boom during the pandemic, technologists are managing more applications and data than ever before, which has led three quarters of technologists to be concerned with increased IT complexity.

Even more significant, 89% admitted to feeling under immense pressure to keep up with the churn, according to the recent AppDynamics Agents of Transformation report. It's clear that the pandemic has pushed many technologists to their breaking point. To help tackle IT burnout, tech professionals need a "canary" to help them streamline and catch the anomalies before they cause any major performance issues.

The Canary is Full-Stack Observability

Businesses have fast-tracked their digital strategies, moving toward technology like cloud computing to meet storage and speed demands. As a result, technologists have not only had to continue to manage their initial applications running the business' digital properties, but now also the new applications from the cloud. For technologists to manage the deluge of data, relieve them from the pressure of having to manually monitor each domain of the IT stack, and catch and fix issues before they disrupt business, they need to consider implementing a full-stack observability strategy.

Full-stack observability enables technologists to have visibility into the full IT estate — current and new, on-prem, hybrid and/or cloud applications — and the ability to connect performance issues or updates directly to their effect on business outcomes. Full-stack observability allows for visibility, understanding, and optimization of what happens inside and beyond architecture.

The advantage of deep business context is that it speeds digital transformation by aligning teams around shared priorities and enables technologists to act with confidence on what matters most. Instead of trying to keep up with the complex and increasing amount of data running through the business' IT stack, technologists can observe everything and understand how what they do directly relates to the bigger picture.

Save Time, Money and Energy

In addition to saving the time that would have been spent on manually monitoring everything, the overview of the IT estate that full-stack observability provides also brings opportunities to save money and energy. When you're looking at your IT stack's infrastructure, network and security domains; you can identify which applications are performing well and the criticality of having access to business context, versus those that are potentially being underutilized or not producing valuable results. This allows you to redirect your finances accordingly, so you are getting your money's worth and optimizing all your applications.

Similarly, your IT team can relocate its energy to supporting the applications that are functioning properly and identify areas where there might be room for the business' digital strategy to innovate or expand.

IT burnout is real and on the heels of the past year's events, it is clear that digital transformation will only continue to evolve going forward. Now that most organizations have had to shift to a digital strategy, they must do more in order to stay competitive, as the bar for digital experiences has increased dramatically.

Give your team the support they deserve and help your business' digital strategy expand by starting the journey with full-stack observability and letting it serve as the "canary in the coal mine," giving teams visibility, correlation back to the app, as well as user and business experience which leads them on their path for success.

Angie Mistretta is CMO of AppDynamics, a part of Cisco

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IT Burnout is Real - Here's How Full-Stack Observability Can Help

Angie Mistretta
AppDynamics

You might have heard of the phrase "canary in the coal mine," which refers to an indicator of potential danger or failure ahead. In the tech industry, these potential failures could be catastrophic, as anomalies in applications negatively impact the performance, customer experience and business outcomes. As we have seen during this digital transformation boom during the pandemic, technologists are managing more applications and data than ever before, which has led three quarters of technologists to be concerned with increased IT complexity.

Even more significant, 89% admitted to feeling under immense pressure to keep up with the churn, according to the recent AppDynamics Agents of Transformation report. It's clear that the pandemic has pushed many technologists to their breaking point. To help tackle IT burnout, tech professionals need a "canary" to help them streamline and catch the anomalies before they cause any major performance issues.

The Canary is Full-Stack Observability

Businesses have fast-tracked their digital strategies, moving toward technology like cloud computing to meet storage and speed demands. As a result, technologists have not only had to continue to manage their initial applications running the business' digital properties, but now also the new applications from the cloud. For technologists to manage the deluge of data, relieve them from the pressure of having to manually monitor each domain of the IT stack, and catch and fix issues before they disrupt business, they need to consider implementing a full-stack observability strategy.

Full-stack observability enables technologists to have visibility into the full IT estate — current and new, on-prem, hybrid and/or cloud applications — and the ability to connect performance issues or updates directly to their effect on business outcomes. Full-stack observability allows for visibility, understanding, and optimization of what happens inside and beyond architecture.

The advantage of deep business context is that it speeds digital transformation by aligning teams around shared priorities and enables technologists to act with confidence on what matters most. Instead of trying to keep up with the complex and increasing amount of data running through the business' IT stack, technologists can observe everything and understand how what they do directly relates to the bigger picture.

Save Time, Money and Energy

In addition to saving the time that would have been spent on manually monitoring everything, the overview of the IT estate that full-stack observability provides also brings opportunities to save money and energy. When you're looking at your IT stack's infrastructure, network and security domains; you can identify which applications are performing well and the criticality of having access to business context, versus those that are potentially being underutilized or not producing valuable results. This allows you to redirect your finances accordingly, so you are getting your money's worth and optimizing all your applications.

Similarly, your IT team can relocate its energy to supporting the applications that are functioning properly and identify areas where there might be room for the business' digital strategy to innovate or expand.

IT burnout is real and on the heels of the past year's events, it is clear that digital transformation will only continue to evolve going forward. Now that most organizations have had to shift to a digital strategy, they must do more in order to stay competitive, as the bar for digital experiences has increased dramatically.

Give your team the support they deserve and help your business' digital strategy expand by starting the journey with full-stack observability and letting it serve as the "canary in the coal mine," giving teams visibility, correlation back to the app, as well as user and business experience which leads them on their path for success.

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 ...