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Full-Stack Observability in 2024 and the Importance of End-to-End Visibility for IT Teams

Full-stack observability is key to deliver a seamless digital experience and here's why
Gregg Ostrowski
AppDynamics

Applications and digital services have become a core to how we live, work and play, providing more convenient and intuitive solutions for tedious tasks. However, end user expectations have accelerated over the past two years, putting pressure on IT teams to develop and maintain seamless, always on services.

In our latest research, Cisco's The App Attention Index 2023: Beware the Application Generation, 62% of consumers report their expectations for digital experiences are far higher than they were two years ago, and 64% state they are less forgiving of poor digital services than they were just 12 months ago. People have enjoyed the benefits of the most innovative, seamless and secure applications and digital services available and will no longer tolerate poor performance.

In today's competitive digital marketplace, IT teams need a multi-purpose solution to help optimize the digital experience. By taking this modern approach to application performance, IT teams will be equipped to quickly detect and resolve possible bottlenecks across even the most complex and fragmented IT environments before the end user is impacted.

The Focus Has Shifted from Quantity to Quality

77% have stopped using digital services or deleted applications from their devices because of a performance issue

The research revealed the digital experience is now imperative for business success, as people's reactions to failed or underperforming applications has grown stronger. Over the last 12 months, 77% have stopped using digital services or deleted applications from their devices because of a performance issue. Consumers are also more likely to share their negative experiences, with 67% saying they would warn others about applications that fail to perform. This intel alone shows positive digital experiences are now a business imperative.

But, just as expectations for seamless digital experiences are rising, instances of digital disruption are also becoming more frequent. As many as 88% of consumers report they have experienced performance issues when using applications over the past 12 months, which is a significant increase from the 81% recorded in 2021. The introduction of more complex cloud environments, increased security risks, and growing user numbers are likely all factors contributing to the rise in digital disruption. And for many IT teams, the task of optimizing application availability, performance and security to address these concerns is easier said than done.

Full-Stack Observability: The Multi-Purpose Solution for IT Teams

IT teams are hindered by increasingly complex and fragmented environments. With the widespread adoption of cloud native technologies, IT teams have had to manage broader, more intricate application infrastructures spanning across both cloud and on-premises. For most, this has been a rapid transformation, leaving IT teams without all the necessary tools and insights needed to optimize application performance in a hybrid environment.

The more complexity you introduce, the harder it is to have complete visibility. IT teams are struggling with cloud native technologies such as Kubernetes, and they can't get a clear line of sight for applications where components are running across hybrid environments. This has made it near impossible for them to quickly identify and fix performance and security issues in real time, before they impact the end user experience.

Full-stack observability can help technology leaders and their teams overcome these challenges by generating full and unified visibility. As cloud adoption and optimization continues to trend in 2024, we should similarly expect observability to be a critical part of modern business strategies. With full-stack observability, IT teams can receive performance updates in real time, so they can rapidly detect problems, understand what's causing them and avoid downtime.

Another key advantage of full-stack observability is the ability to correlate the application performance and security data with key business metrics. Over the last year, telemetry data has emerged as an invaluable instrument to extract, collate and analyze performance data at every layer of a distributed system. It's a component of observability we expect will further mature in 2024, as this data can help IT teams identify, prioritize, and most importantly, take action on the issues that will have the biggest impact on digital experience. Rather than firefighting an overwhelming number of alerts, IT teams can take a more proactive, thoughtful approach, focused on what will deliver the biggest impact to customers and the business.

There is an appetite for applications and digital services to deliver the best performance, but modern IT environments are getting more complex. IT teams need a unified solution that can centralize and correlate availability, performance and security data from across hybrid infrastructures. With full-stack observability, technology leaders can equip their teams with the tools and insights needed to meet this soaring demand for increasingly intuitive, seamless and secure digital experiences.

Gregg Ostrowski is CTO Advisor at Cisco AppDynamics

The Latest

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

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 ...

Full-Stack Observability in 2024 and the Importance of End-to-End Visibility for IT Teams

Full-stack observability is key to deliver a seamless digital experience and here's why
Gregg Ostrowski
AppDynamics

Applications and digital services have become a core to how we live, work and play, providing more convenient and intuitive solutions for tedious tasks. However, end user expectations have accelerated over the past two years, putting pressure on IT teams to develop and maintain seamless, always on services.

In our latest research, Cisco's The App Attention Index 2023: Beware the Application Generation, 62% of consumers report their expectations for digital experiences are far higher than they were two years ago, and 64% state they are less forgiving of poor digital services than they were just 12 months ago. People have enjoyed the benefits of the most innovative, seamless and secure applications and digital services available and will no longer tolerate poor performance.

In today's competitive digital marketplace, IT teams need a multi-purpose solution to help optimize the digital experience. By taking this modern approach to application performance, IT teams will be equipped to quickly detect and resolve possible bottlenecks across even the most complex and fragmented IT environments before the end user is impacted.

The Focus Has Shifted from Quantity to Quality

77% have stopped using digital services or deleted applications from their devices because of a performance issue

The research revealed the digital experience is now imperative for business success, as people's reactions to failed or underperforming applications has grown stronger. Over the last 12 months, 77% have stopped using digital services or deleted applications from their devices because of a performance issue. Consumers are also more likely to share their negative experiences, with 67% saying they would warn others about applications that fail to perform. This intel alone shows positive digital experiences are now a business imperative.

But, just as expectations for seamless digital experiences are rising, instances of digital disruption are also becoming more frequent. As many as 88% of consumers report they have experienced performance issues when using applications over the past 12 months, which is a significant increase from the 81% recorded in 2021. The introduction of more complex cloud environments, increased security risks, and growing user numbers are likely all factors contributing to the rise in digital disruption. And for many IT teams, the task of optimizing application availability, performance and security to address these concerns is easier said than done.

Full-Stack Observability: The Multi-Purpose Solution for IT Teams

IT teams are hindered by increasingly complex and fragmented environments. With the widespread adoption of cloud native technologies, IT teams have had to manage broader, more intricate application infrastructures spanning across both cloud and on-premises. For most, this has been a rapid transformation, leaving IT teams without all the necessary tools and insights needed to optimize application performance in a hybrid environment.

The more complexity you introduce, the harder it is to have complete visibility. IT teams are struggling with cloud native technologies such as Kubernetes, and they can't get a clear line of sight for applications where components are running across hybrid environments. This has made it near impossible for them to quickly identify and fix performance and security issues in real time, before they impact the end user experience.

Full-stack observability can help technology leaders and their teams overcome these challenges by generating full and unified visibility. As cloud adoption and optimization continues to trend in 2024, we should similarly expect observability to be a critical part of modern business strategies. With full-stack observability, IT teams can receive performance updates in real time, so they can rapidly detect problems, understand what's causing them and avoid downtime.

Another key advantage of full-stack observability is the ability to correlate the application performance and security data with key business metrics. Over the last year, telemetry data has emerged as an invaluable instrument to extract, collate and analyze performance data at every layer of a distributed system. It's a component of observability we expect will further mature in 2024, as this data can help IT teams identify, prioritize, and most importantly, take action on the issues that will have the biggest impact on digital experience. Rather than firefighting an overwhelming number of alerts, IT teams can take a more proactive, thoughtful approach, focused on what will deliver the biggest impact to customers and the business.

There is an appetite for applications and digital services to deliver the best performance, but modern IT environments are getting more complex. IT teams need a unified solution that can centralize and correlate availability, performance and security data from across hybrid infrastructures. With full-stack observability, technology leaders can equip their teams with the tools and insights needed to meet this soaring demand for increasingly intuitive, seamless and secure digital experiences.

Gregg Ostrowski is CTO Advisor at Cisco AppDynamics

The Latest

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

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 ...