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The Role of Distributed Tracing in Quick Problem Solving

Ranjani
Site24x7

Microservices have become the go-to architectural standard in modern distributed systems. According to a recent report by Market Research Future, the industry shift towards adopting microservices is growing at 17 percent annually. Considering how microservices enable rapid application prototyping and faster deployments by reducing dependencies between individual components and services, this isn't all that surprising.

This independence of individual components is achieved by implementing proper interfaces via APIs to ensure that the system functions holistically. While there are plenty of tools and techniques to architect, manage, and automate the deployment of such distributed systems, issues during troubleshooting still happen at the individual service level, thereby prolonging the time taken to resolve an outage. 

The Challenges

Troubleshooting is always taxing, but microservices make it even more cumbersome, as developers have to correlate logs, metrics, and other diagnostic information from multiple lines of services. The higher the number of services in the system, the more complex diagnosis is.


In the unfortunate event of an outage, the microservices environment poses two main challenges: the primary one is fixing the issue and bringing services back online, which, by itself, is a tedious and time-consuming process that involves correlating large amounts of service-level data and coordinating with various tools. But the far greater challenge is narrowing down the problematic service among the myriad of interconnected ones. 

This is where distributed tracing comes into play. This mechanism enables DevOps teams to pinpoint the problem by skimming through the entire system for issues instead of tracing within the boundary of a service.

Causation and Not Just Correlation

Distributed tracing enables IT teams to visualize the flow of transactions across services written in multiple languages hosted across multiple data centers and application frameworks. This gives quick insight into anomalous behaviors and performance bottlenecks, and makes it easy even for a novice to understand the intricacies of the system.

In short, distributed tracing saves a lot of overhead in DevOps by presenting both a bird's-eye view of the system and the capability to zero in on the root cause of an issue.


The World Wide Web Consortium (W3C) is working on a standard that bridges the gap in providing a unified solution for distributed tracing. Very soon, distributed tracing will be an inevitable part in monitoring microservices.

The Road Ahead

Looking at the bigger picture, analyzing the massive sets of distributed traces would equip IT teams with more information than they usually get from mere troubleshooting. You can actually identify application behavior in various scenarios and derive actionable insights by studying these traces.

Soon, distributed tracing will not be considered as a mere problem solving tool; instead, it will take on an indispensable role in operational decision-making.

Ranjani is a Product Analyst at Site24x7

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The Role of Distributed Tracing in Quick Problem Solving

Ranjani
Site24x7

Microservices have become the go-to architectural standard in modern distributed systems. According to a recent report by Market Research Future, the industry shift towards adopting microservices is growing at 17 percent annually. Considering how microservices enable rapid application prototyping and faster deployments by reducing dependencies between individual components and services, this isn't all that surprising.

This independence of individual components is achieved by implementing proper interfaces via APIs to ensure that the system functions holistically. While there are plenty of tools and techniques to architect, manage, and automate the deployment of such distributed systems, issues during troubleshooting still happen at the individual service level, thereby prolonging the time taken to resolve an outage. 

The Challenges

Troubleshooting is always taxing, but microservices make it even more cumbersome, as developers have to correlate logs, metrics, and other diagnostic information from multiple lines of services. The higher the number of services in the system, the more complex diagnosis is.


In the unfortunate event of an outage, the microservices environment poses two main challenges: the primary one is fixing the issue and bringing services back online, which, by itself, is a tedious and time-consuming process that involves correlating large amounts of service-level data and coordinating with various tools. But the far greater challenge is narrowing down the problematic service among the myriad of interconnected ones. 

This is where distributed tracing comes into play. This mechanism enables DevOps teams to pinpoint the problem by skimming through the entire system for issues instead of tracing within the boundary of a service.

Causation and Not Just Correlation

Distributed tracing enables IT teams to visualize the flow of transactions across services written in multiple languages hosted across multiple data centers and application frameworks. This gives quick insight into anomalous behaviors and performance bottlenecks, and makes it easy even for a novice to understand the intricacies of the system.

In short, distributed tracing saves a lot of overhead in DevOps by presenting both a bird's-eye view of the system and the capability to zero in on the root cause of an issue.


The World Wide Web Consortium (W3C) is working on a standard that bridges the gap in providing a unified solution for distributed tracing. Very soon, distributed tracing will be an inevitable part in monitoring microservices.

The Road Ahead

Looking at the bigger picture, analyzing the massive sets of distributed traces would equip IT teams with more information than they usually get from mere troubleshooting. You can actually identify application behavior in various scenarios and derive actionable insights by studying these traces.

Soon, distributed tracing will not be considered as a mere problem solving tool; instead, it will take on an indispensable role in operational decision-making.

Ranjani is a Product Analyst at Site24x7

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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 ...

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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 ...

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