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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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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 ...

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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 ...

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

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 ...