Skip to main content

Taking Action Against the Data You Have

Adam Frank
Moogsoft

Move fast and break things: A phrase that has been a rallying cry for many SREs and DevOps practitioners. After all, these teams are charged with delivering rapid and unceasing innovation to wow customers and keep pace with competitors.

But today's society doesn't tolerate broken things (aka downtime). So, what if you can move fast and not break things? Or at least, move fast and rapidly identify or even predict broken things?

It's high time to rethink the old rallying cry, and with AI and observability working in tandem, it's possible.

Applying AI to observability data turns mountains of telemetry data, regardless of the relative size of the mountain to your business, into actionable information, playing a critical role in how quickly an organization can innovate. Let's explore why these solutions are so essential.

How AI and Observability Converge to Help

DevOps practitioners strive to provide superior digital experiences by continuously delivering and integrating features, fixes and functionalities for immersive experiences. This constant behind-the-scenes innovation is at odds with customers' expectations for 100% availability. Today's consumer expects to purchase, transact, interact and access on-demand digital services with zero downtime.

SREs and DevOps teams need AI-driven observability to monitor system performance or innovation and productivity plummets. Teams spend entire days managing alerts and fighting fires. And even with an infinite amount of time to shift through data, today's distributed IT systems, virtual computing and ephemeral machines are simply too complex and interdependent for the human mind to monitor manually.

Only automated intelligence can constantly verify and restore digital products and services in modern IT architectures. And only AI and ML can create a continual learning cycle, understanding more from the data gathered across infrastructures, applications and services. These insights build more system reliability, but because nothing can fully protect against outages happening, they also allow IT teams to resolve incidents rapidly when they do occur.

SREs, DevOps Practitioners ... and Astronauts?

When incidents arise and systems fail, the stakes are high for SREs and DevOps practitioners to right the ship — and fast. For every minute of downtime, businesses suffer exponential losses, like tanking stocks, tarnished reputations and disillusioned customers. But teams also need to remain cool under mounting pressure to work efficiently.

How? In one word: knowledge.

I recently read Chirs Hadfield's book An Astronaut's Guide to Life on Earth. Although I only wish people thought of IT teams as superheroes, the author's advice resonated:

"People tend to think astronauts have the courage of a superhero — or maybe the emotional range of a robot. But in order to stay calm in a high-stress, high-stakes situation, all you really need is knowledge."

Under pressure to tackle a challenging system failure, knowledge also allows SREs and DevOps teams to overcome emotions and find solutions. And that's precisely where intelligent observability comes in: it gathers data produced from apps and services, adds context and turns volumes of information into actionable knowledge.

Automate the Cognitive Load

The benefits of automation don't stop at speedy fixes. Automating the toil out of observability provides economic value by freeing teams to accelerate innovation and provide measurable value. Teams can focus more on development and less on ops with little mundane work to accomplish.

Intelligent observability also reduces stress and burnout prevalent among IT teams. AI-driven observability platforms reduce alert noise and focus teams on the incidents that matter for triage and remediation.

And, for businesses, intelligent observability assures the quality of the customer experience, which is ultimately what matters most.

Welcome to the era of move fast and break things infrequently. Although less catchy than the original, it's more reflective of the automated intelligence today's software-defined world needs to deliver superior customer experiences. Every business's revenue, reputation and growth depend on it.

Adam Frank is VP, Product & Design, at Moogsoft

Hot Topics

The Latest

According to Auvik's 2025 IT Trends Report, 60% of IT professionals feel at least moderately burned out on the job, with 43% stating that their workload is contributing to work stress. At the same time, many IT professionals are naming AI and machine learning as key areas they'd most like to upskill ...

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

Image
Cloudbrink's Personal SASE services provide last-mile acceleration and reduction in latency

In MEAN TIME TO INSIGHT Episode 13, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud networking strategy ... 

In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance. This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks ...

In 2025, enterprise workflows are undergoing a seismic shift. Propelled by breakthroughs in generative AI (GenAI), large language models (LLMs), and natural language processing (NLP), a new paradigm is emerging — agentic AI. This technology is not just automating tasks; it's reimagining how organizations make decisions, engage customers, and operate at scale ...

In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...

In today's fast-paced and increasingly complex network environments, Network Operations Centers (NOCs) are the backbone of ensuring continuous uptime, smooth service delivery, and rapid issue resolution. However, the challenges faced by NOC teams are only growing. In a recent study, 78% state network complexity has grown significantly over the last few years while 84% regularly learn about network issues from users. It is imperative we adopt a new approach to managing today's network experiences ...

Image
Broadcom

From growing reliance on FinOps teams to the increasing attention on artificial intelligence (AI), and software licensing, the Flexera 2025 State of the Cloud Report digs into how organizations are improving cloud spend efficiency, while tackling the complexities of emerging technologies ...

Taking Action Against the Data You Have

Adam Frank
Moogsoft

Move fast and break things: A phrase that has been a rallying cry for many SREs and DevOps practitioners. After all, these teams are charged with delivering rapid and unceasing innovation to wow customers and keep pace with competitors.

But today's society doesn't tolerate broken things (aka downtime). So, what if you can move fast and not break things? Or at least, move fast and rapidly identify or even predict broken things?

It's high time to rethink the old rallying cry, and with AI and observability working in tandem, it's possible.

Applying AI to observability data turns mountains of telemetry data, regardless of the relative size of the mountain to your business, into actionable information, playing a critical role in how quickly an organization can innovate. Let's explore why these solutions are so essential.

How AI and Observability Converge to Help

DevOps practitioners strive to provide superior digital experiences by continuously delivering and integrating features, fixes and functionalities for immersive experiences. This constant behind-the-scenes innovation is at odds with customers' expectations for 100% availability. Today's consumer expects to purchase, transact, interact and access on-demand digital services with zero downtime.

SREs and DevOps teams need AI-driven observability to monitor system performance or innovation and productivity plummets. Teams spend entire days managing alerts and fighting fires. And even with an infinite amount of time to shift through data, today's distributed IT systems, virtual computing and ephemeral machines are simply too complex and interdependent for the human mind to monitor manually.

Only automated intelligence can constantly verify and restore digital products and services in modern IT architectures. And only AI and ML can create a continual learning cycle, understanding more from the data gathered across infrastructures, applications and services. These insights build more system reliability, but because nothing can fully protect against outages happening, they also allow IT teams to resolve incidents rapidly when they do occur.

SREs, DevOps Practitioners ... and Astronauts?

When incidents arise and systems fail, the stakes are high for SREs and DevOps practitioners to right the ship — and fast. For every minute of downtime, businesses suffer exponential losses, like tanking stocks, tarnished reputations and disillusioned customers. But teams also need to remain cool under mounting pressure to work efficiently.

How? In one word: knowledge.

I recently read Chirs Hadfield's book An Astronaut's Guide to Life on Earth. Although I only wish people thought of IT teams as superheroes, the author's advice resonated:

"People tend to think astronauts have the courage of a superhero — or maybe the emotional range of a robot. But in order to stay calm in a high-stress, high-stakes situation, all you really need is knowledge."

Under pressure to tackle a challenging system failure, knowledge also allows SREs and DevOps teams to overcome emotions and find solutions. And that's precisely where intelligent observability comes in: it gathers data produced from apps and services, adds context and turns volumes of information into actionable knowledge.

Automate the Cognitive Load

The benefits of automation don't stop at speedy fixes. Automating the toil out of observability provides economic value by freeing teams to accelerate innovation and provide measurable value. Teams can focus more on development and less on ops with little mundane work to accomplish.

Intelligent observability also reduces stress and burnout prevalent among IT teams. AI-driven observability platforms reduce alert noise and focus teams on the incidents that matter for triage and remediation.

And, for businesses, intelligent observability assures the quality of the customer experience, which is ultimately what matters most.

Welcome to the era of move fast and break things infrequently. Although less catchy than the original, it's more reflective of the automated intelligence today's software-defined world needs to deliver superior customer experiences. Every business's revenue, reputation and growth depend on it.

Adam Frank is VP, Product & Design, at Moogsoft

Hot Topics

The Latest

According to Auvik's 2025 IT Trends Report, 60% of IT professionals feel at least moderately burned out on the job, with 43% stating that their workload is contributing to work stress. At the same time, many IT professionals are naming AI and machine learning as key areas they'd most like to upskill ...

Businesses that face downtime or outages risk financial and reputational damage, as well as reducing partner, shareholder, and customer trust. One of the major challenges that enterprises face is implementing a robust business continuity plan. What's the solution? The answer may lie in disaster recovery tactics such as truly immutable storage and regular disaster recovery testing ...

IT spending is expected to jump nearly 10% in 2025, and organizations are now facing pressure to manage costs without slowing down critical functions like observability. To meet the challenge, leaders are turning to smarter, more cost effective business strategies. Enter stage right: OpenTelemetry, the missing piece of the puzzle that is no longer just an option but rather a strategic advantage ...

Amidst the threat of cyberhacks and data breaches, companies install several security measures to keep their business safely afloat. These measures aim to protect businesses, employees, and crucial data. Yet, employees perceive them as burdensome. Frustrated with complex logins, slow access, and constant security checks, workers decide to completely bypass all security set-ups ...

Image
Cloudbrink's Personal SASE services provide last-mile acceleration and reduction in latency

In MEAN TIME TO INSIGHT Episode 13, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses hybrid multi-cloud networking strategy ... 

In high-traffic environments, the sheer volume and unpredictable nature of network incidents can quickly overwhelm even the most skilled teams, hindering their ability to react swiftly and effectively, potentially impacting service availability and overall business performance. This is where closed-loop remediation comes into the picture: an IT management concept designed to address the escalating complexity of modern networks ...

In 2025, enterprise workflows are undergoing a seismic shift. Propelled by breakthroughs in generative AI (GenAI), large language models (LLMs), and natural language processing (NLP), a new paradigm is emerging — agentic AI. This technology is not just automating tasks; it's reimagining how organizations make decisions, engage customers, and operate at scale ...

In the early days of the cloud revolution, business leaders perceived cloud services as a means of sidelining IT organizations. IT was too slow, too expensive, or incapable of supporting new technologies. With a team of developers, line of business managers could deploy new applications and services in the cloud. IT has been fighting to retake control ever since. Today, IT is back in the driver's seat, according to new research by Enterprise Management Associates (EMA) ...

In today's fast-paced and increasingly complex network environments, Network Operations Centers (NOCs) are the backbone of ensuring continuous uptime, smooth service delivery, and rapid issue resolution. However, the challenges faced by NOC teams are only growing. In a recent study, 78% state network complexity has grown significantly over the last few years while 84% regularly learn about network issues from users. It is imperative we adopt a new approach to managing today's network experiences ...

Image
Broadcom

From growing reliance on FinOps teams to the increasing attention on artificial intelligence (AI), and software licensing, the Flexera 2025 State of the Cloud Report digs into how organizations are improving cloud spend efficiency, while tackling the complexities of emerging technologies ...