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Datadog Releases Live Debugger in Beta

Datadog announced the launch of Live Debugger, a new tool that enables developers to step through code in production environments and find the exact root cause of coding errors.

Live Debugger requires no downtime and enables developers to work directly in production environments instead of spending countless hours of trial and error to reproduce production issues in development environments.

Live Debugger aggregates the necessary information from the live production environment and integrating it directly into the user’s Integrated Development Environment (IDE). The product accelerates root-cause analysis with AI-generated exception summaries and one-click test creation to accurately reproduce all bug conditions based on production data. Using Live Debugger not only improves the developer experience, it also dramatically reduces the time it takes to resolve issues, freeing up engineers to spend more time delivering business value.

“Debugging can be a slow and inefficient process which requires extensive manual data collection and the ability to reproduce bugs in perfectly reconstructed conditions. These constraints negatively impact developer productivity and, ultimately, the end user experience,” said Hugo Kaczmarek, Director of Product at Datadog. “With today’s launch, we are taking the guesswork out of debugging, minimizing the friction experienced by developers and creating a tool that inherently supports rapid issue resolution while maintaining the highest standards of code quality and security.”

Features of Live Debugger include:

- Exception Replay: Developers can step through the execution flow of their code and see local variable values that were captured live when the exception was thrown—all without needing to run code.

- Powerful Visualizations and Context: Datadog’s unified platform delivers the observability context needed to troubleshoot issues quickly and provides an AI-powered summary of the code’s executional context, a starting hypothesis for the root cause of the issue, and visualizations of data flows between services and where the interaction between them occurred in the code.

- Integrated AI-Generated Tests: Teams can quickly and accurately reproduce issues by using production data to mock all relevant values across dependent microservices. Tests can then be run directly in the customer’s IDE with just one click.

Live Debugger is available in beta now.

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Datadog Releases Live Debugger in Beta

Datadog announced the launch of Live Debugger, a new tool that enables developers to step through code in production environments and find the exact root cause of coding errors.

Live Debugger requires no downtime and enables developers to work directly in production environments instead of spending countless hours of trial and error to reproduce production issues in development environments.

Live Debugger aggregates the necessary information from the live production environment and integrating it directly into the user’s Integrated Development Environment (IDE). The product accelerates root-cause analysis with AI-generated exception summaries and one-click test creation to accurately reproduce all bug conditions based on production data. Using Live Debugger not only improves the developer experience, it also dramatically reduces the time it takes to resolve issues, freeing up engineers to spend more time delivering business value.

“Debugging can be a slow and inefficient process which requires extensive manual data collection and the ability to reproduce bugs in perfectly reconstructed conditions. These constraints negatively impact developer productivity and, ultimately, the end user experience,” said Hugo Kaczmarek, Director of Product at Datadog. “With today’s launch, we are taking the guesswork out of debugging, minimizing the friction experienced by developers and creating a tool that inherently supports rapid issue resolution while maintaining the highest standards of code quality and security.”

Features of Live Debugger include:

- Exception Replay: Developers can step through the execution flow of their code and see local variable values that were captured live when the exception was thrown—all without needing to run code.

- Powerful Visualizations and Context: Datadog’s unified platform delivers the observability context needed to troubleshoot issues quickly and provides an AI-powered summary of the code’s executional context, a starting hypothesis for the root cause of the issue, and visualizations of data flows between services and where the interaction between them occurred in the code.

- Integrated AI-Generated Tests: Teams can quickly and accurately reproduce issues by using production data to mock all relevant values across dependent microservices. Tests can then be run directly in the customer’s IDE with just one click.

Live Debugger is available in beta now.

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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 ... 

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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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