Skip to main content

Why Visibility is Critical for DevOps Teams

Michael Segal

According to recent reports, the majority of businesses now use cloud computing in one form or another. Innovation and agility are key to success in today's fast-moving, competitive environment, and with many legacy systems no longer able to keep up with the demands of digital transformation, it's little surprise that more than two thirds of enterprise workloads are now reported to be in the cloud.

As businesses look to capitalize on the benefits offered by the cloud, we've seen the rise of the DevOps practice which, in common with the cloud, offers businesses the advantages of greater agility, speed, quality and efficiency.

However, achieving this agility requires end-to-end visibility based on continuous monitoring of the developed applications as part of the software development life cycle (SDLC) in order to achieve a common situational awareness; without which, DevOps teams can find themselves hindered, causing innovation to stall.

Reaching Maturity

In simple terms, the role of DevOps is to produce new software, based on business needs, at very high speed, and of the highest possible quality of user experience given the constraints under which they operate. A continuous delivery pipeline, for example, could mean as many as several releases a day, each of which requires code to be built, tested, and integrated before being deployed, and each of which must deliver a responsive, reliable service with virtually no downtime.

The functionality of a DevOps team can be impacted by the level of its maturity, however, which can be influenced by two factors. The first of these is the cultural dimension; the team's ability to collaborate effectively, owning the overall DevOps mission as opposed to meeting specific objectives of the individual teams that comprise the whole, such as Operations or QA.

Before mastering this aspect, developers tend to be focused on the speed of software delivery, QA tends to focus on testing predefined use cases, while Operations concentrates on monitoring the production environment. Each team is focused on its own domain and is often siloed off from the others, without utilizing an effective feedback loop and establishing a common situational awareness.

At this stage of organizational maturity, the DevOps team will be focused more on accelerating and optimizing the effectiveness of its individual domains using technologies such as version control management, continuous integration, automated testing, automated deployment and configuration management. Increasing DevOps maturity relies on additional technologies for continuous monitoring, improved visibility, telemetry, feedback loops, and situational awareness. Achieving this, however, can prove challenging.

Visibility and Insights

Consider a situation in which developers build the code for an application, QA tests it based on common use cases, and then the release manager oversees its integration into the mainline and its subsequent deployment. At this point, Operations might find a problem that only manifests at scale, requiring Dev teams to quickly pinpoint the issue and rectify it by developing new code that functions correctly in the product environment.

It's here, then, that visibility is most crucial, providing all parties with common situational awareness. Rather than relying on Ops to highlight issues, in this example Dev teams are able instead to look on the system and see the same situation themselves, and thereby better understand the parameters within which they need to work. Doing so will save time and create more effective feedback loops which would enable to adjust the development and QA processes to detect similar issues early on in the SDLC or even prevent them from occurring altogether.

Achieving this level of visibility requires the use of smart data – metadata based on processing and organizing wire data at the point of collection, and optimizing it for analytics at the highest speed and quality. By analyzing every IP packet that traverses the network during a development cycle and beyond – in real time – smart data delivers meaningful and actionable insights, creating a common situational awareness for all teams. This then enables those teams, from developers through QA to IT Operations, to work together within constantly evolving parameters, avoiding any bottlenecks in the feedback loop.

Opportunity for Innovation

Digital transformation, and the role of the cloud within it, are integral to an organization's innovation. With more applications and services being migrated to the cloud, however, a host of new, unprecedented challenges are emerging.

This is particularly true for DevOps teams, charged with producing quality code at speed. To reach the level of maturity at which they can function most efficiently and effectively requires siloes of work to be broken down across the organization to foster a culture of collaboration and continuous communication. The visibility, insight and common situational awareness offered by smart data can help achieve this, freeing up the potential of DevOps, and affording organizations a greater opportunity for innovation.

The Latest

Significant improvements in operational resilience, more effective use of automation and faster time to market are driving optimism about IT spending in 2025, with a majority of leaders expecting their budgets to increase year-over-year, according to the 2025 State of Digital Operations Report from PagerDuty ...

Image
PagerDuty

Are they simply number crunchers confined to back-office support, or are they the strategic influencers shaping the future of your enterprise? The reality is that data analysts are far more the latter. In fact, 94% of analysts agree their role is pivotal to making high-level business decisions, proving that they are becoming indispensable partners in shaping strategy ...

Today's enterprises exist in rapidly growing, complex IT landscapes that can inadvertently create silos and lead to the accumulation of disparate tools. To successfully manage such growth, these organizations must realize the requisite shift in corporate culture and workflow management needed to build trust in new technologies. This is particularly true in cases where enterprises are turning to automation and autonomic IT to offload the burden from IT professionals. This interplay between technology and culture is crucial in guiding teams using AIOps and observability solutions to proactively manage operations and transition toward a machine-driven IT ecosystem ...

Gartner identified the top data and analytics (D&A) trends for 2025 that are driving the emergence of a wide range of challenges, including organizational and human issues ...

Traditional network monitoring, while valuable, often falls short in providing the context needed to truly understand network behavior. This is where observability shines. In this blog, we'll compare and contrast traditional network monitoring and observability — highlighting the benefits of this evolving approach ...

A recent Rocket Software and Foundry study found that just 28% of organizations fully leverage their mainframe data, a concerning statistic given its critical role in powering AI models, predictive analytics, and informed decision-making ...

What kind of ROI is your organization seeing on its technology investments? If your answer is "it's complicated," you're not alone. According to a recent study conducted by Apptio ... there is a disconnect between enterprise technology spending and organizations' ability to measure the results ...

In today’s data and AI driven world, enterprises across industries are utilizing AI to invent new business models, reimagine business and achieve efficiency in operations. However, enterprises may face challenges like flawed or biased AI decisions, sensitive data breaches and rising regulatory risks ...

In MEAN TIME TO INSIGHT Episode 12, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses purchasing new network observability solutions.... 

There's an image problem with mobile app security. While it's critical for highly regulated industries like financial services, it is often overlooked in others. This usually comes down to development priorities, which typically fall into three categories: user experience, app performance, and app security. When dealing with finite resources such as time, shifting priorities, and team skill sets, engineering teams often have to prioritize one over the others. Usually, security is the odd man out ...

Image
Guardsquare

Why Visibility is Critical for DevOps Teams

Michael Segal

According to recent reports, the majority of businesses now use cloud computing in one form or another. Innovation and agility are key to success in today's fast-moving, competitive environment, and with many legacy systems no longer able to keep up with the demands of digital transformation, it's little surprise that more than two thirds of enterprise workloads are now reported to be in the cloud.

As businesses look to capitalize on the benefits offered by the cloud, we've seen the rise of the DevOps practice which, in common with the cloud, offers businesses the advantages of greater agility, speed, quality and efficiency.

However, achieving this agility requires end-to-end visibility based on continuous monitoring of the developed applications as part of the software development life cycle (SDLC) in order to achieve a common situational awareness; without which, DevOps teams can find themselves hindered, causing innovation to stall.

Reaching Maturity

In simple terms, the role of DevOps is to produce new software, based on business needs, at very high speed, and of the highest possible quality of user experience given the constraints under which they operate. A continuous delivery pipeline, for example, could mean as many as several releases a day, each of which requires code to be built, tested, and integrated before being deployed, and each of which must deliver a responsive, reliable service with virtually no downtime.

The functionality of a DevOps team can be impacted by the level of its maturity, however, which can be influenced by two factors. The first of these is the cultural dimension; the team's ability to collaborate effectively, owning the overall DevOps mission as opposed to meeting specific objectives of the individual teams that comprise the whole, such as Operations or QA.

Before mastering this aspect, developers tend to be focused on the speed of software delivery, QA tends to focus on testing predefined use cases, while Operations concentrates on monitoring the production environment. Each team is focused on its own domain and is often siloed off from the others, without utilizing an effective feedback loop and establishing a common situational awareness.

At this stage of organizational maturity, the DevOps team will be focused more on accelerating and optimizing the effectiveness of its individual domains using technologies such as version control management, continuous integration, automated testing, automated deployment and configuration management. Increasing DevOps maturity relies on additional technologies for continuous monitoring, improved visibility, telemetry, feedback loops, and situational awareness. Achieving this, however, can prove challenging.

Visibility and Insights

Consider a situation in which developers build the code for an application, QA tests it based on common use cases, and then the release manager oversees its integration into the mainline and its subsequent deployment. At this point, Operations might find a problem that only manifests at scale, requiring Dev teams to quickly pinpoint the issue and rectify it by developing new code that functions correctly in the product environment.

It's here, then, that visibility is most crucial, providing all parties with common situational awareness. Rather than relying on Ops to highlight issues, in this example Dev teams are able instead to look on the system and see the same situation themselves, and thereby better understand the parameters within which they need to work. Doing so will save time and create more effective feedback loops which would enable to adjust the development and QA processes to detect similar issues early on in the SDLC or even prevent them from occurring altogether.

Achieving this level of visibility requires the use of smart data – metadata based on processing and organizing wire data at the point of collection, and optimizing it for analytics at the highest speed and quality. By analyzing every IP packet that traverses the network during a development cycle and beyond – in real time – smart data delivers meaningful and actionable insights, creating a common situational awareness for all teams. This then enables those teams, from developers through QA to IT Operations, to work together within constantly evolving parameters, avoiding any bottlenecks in the feedback loop.

Opportunity for Innovation

Digital transformation, and the role of the cloud within it, are integral to an organization's innovation. With more applications and services being migrated to the cloud, however, a host of new, unprecedented challenges are emerging.

This is particularly true for DevOps teams, charged with producing quality code at speed. To reach the level of maturity at which they can function most efficiently and effectively requires siloes of work to be broken down across the organization to foster a culture of collaboration and continuous communication. The visibility, insight and common situational awareness offered by smart data can help achieve this, freeing up the potential of DevOps, and affording organizations a greater opportunity for innovation.

The Latest

Significant improvements in operational resilience, more effective use of automation and faster time to market are driving optimism about IT spending in 2025, with a majority of leaders expecting their budgets to increase year-over-year, according to the 2025 State of Digital Operations Report from PagerDuty ...

Image
PagerDuty

Are they simply number crunchers confined to back-office support, or are they the strategic influencers shaping the future of your enterprise? The reality is that data analysts are far more the latter. In fact, 94% of analysts agree their role is pivotal to making high-level business decisions, proving that they are becoming indispensable partners in shaping strategy ...

Today's enterprises exist in rapidly growing, complex IT landscapes that can inadvertently create silos and lead to the accumulation of disparate tools. To successfully manage such growth, these organizations must realize the requisite shift in corporate culture and workflow management needed to build trust in new technologies. This is particularly true in cases where enterprises are turning to automation and autonomic IT to offload the burden from IT professionals. This interplay between technology and culture is crucial in guiding teams using AIOps and observability solutions to proactively manage operations and transition toward a machine-driven IT ecosystem ...

Gartner identified the top data and analytics (D&A) trends for 2025 that are driving the emergence of a wide range of challenges, including organizational and human issues ...

Traditional network monitoring, while valuable, often falls short in providing the context needed to truly understand network behavior. This is where observability shines. In this blog, we'll compare and contrast traditional network monitoring and observability — highlighting the benefits of this evolving approach ...

A recent Rocket Software and Foundry study found that just 28% of organizations fully leverage their mainframe data, a concerning statistic given its critical role in powering AI models, predictive analytics, and informed decision-making ...

What kind of ROI is your organization seeing on its technology investments? If your answer is "it's complicated," you're not alone. According to a recent study conducted by Apptio ... there is a disconnect between enterprise technology spending and organizations' ability to measure the results ...

In today’s data and AI driven world, enterprises across industries are utilizing AI to invent new business models, reimagine business and achieve efficiency in operations. However, enterprises may face challenges like flawed or biased AI decisions, sensitive data breaches and rising regulatory risks ...

In MEAN TIME TO INSIGHT Episode 12, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses purchasing new network observability solutions.... 

There's an image problem with mobile app security. While it's critical for highly regulated industries like financial services, it is often overlooked in others. This usually comes down to development priorities, which typically fall into three categories: user experience, app performance, and app security. When dealing with finite resources such as time, shifting priorities, and team skill sets, engineering teams often have to prioritize one over the others. Usually, security is the odd man out ...

Image
Guardsquare