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New Relic Introduces New Integrations with GitHub

New Relic announced three new integrations with GitHub that boost developer productivity and experience to accelerate innovation. 

The innovations, led by a new AI integration that automatically correlates software vulnerabilities and implements fixes, deliver intelligent observability insights where developers already work. Together, the longtime partners are helping GitHub Copilot’s more than 20 million users fast-track development, reduce downtime, and simplify workflows through automation.

“Agentic AI is everywhere, but developers aren’t yet seeing the productivity results they expected,” said New Relic Head of AI Camden Swita. “To unlock AI’s full potential, development teams need intelligent observability in the tools they use everyday. With our latest integrations with GitHub, we are continuing to deliver on our vision of bringing intelligent observability across the tech ecosystem.”

With the New Relic Security RX integration for GitHub Copilot, development teams can gather runtime and build time context of software vulnerabilities to understand the risks of both the security issue and the potential fix. Providing security in context helps distinguish real-world exposure from noise, gives a better understanding of the scope of the problem, and reduces manual research and triaging to prioritize fixing issues that could pose a real risk that's live in production versus what's merely sitting in a repository. The analysis generated via the New Relic Security RX integration for GitHub Copilot can then help create a clear remediation plan that will automatically initiate a GitHub issue containing impact details, testing and verification steps, and acceptance criteria. GitHub Copilot then generates a pull request with all necessary context for engineers, providing insights for faster resolution and reduced toil for developers.

New Relic’s new instrumentation assistant makes GitHub Copilot a more holistic and trustworthy solution-builder. The solution detects and resolves missing instrumentation at deployment by calling GitHub Copilot to implement full coverage directly in pull requests. The integration helps GitHub Copilot users generate more complete solutions. Instead of just a functional code snippet, the user would receive a more fully-realized service that includes observability. When creating or updating a service, GitHub Copilot doesn't just write the backend logic - it instruments the full-stack by including APM, custom attributes for business logic, a GitHub Action for Change Tracking integration with New Relic, and even the Browser agent for front-end visibility.

With the integration between New Relic Service Architecture Intelligence and GitHub, developers can import rich data from GitHub accounts directly into New Relic. The functionality helps developers improve velocity and automate configuration setup. 

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New Relic Introduces New Integrations with GitHub

New Relic announced three new integrations with GitHub that boost developer productivity and experience to accelerate innovation. 

The innovations, led by a new AI integration that automatically correlates software vulnerabilities and implements fixes, deliver intelligent observability insights where developers already work. Together, the longtime partners are helping GitHub Copilot’s more than 20 million users fast-track development, reduce downtime, and simplify workflows through automation.

“Agentic AI is everywhere, but developers aren’t yet seeing the productivity results they expected,” said New Relic Head of AI Camden Swita. “To unlock AI’s full potential, development teams need intelligent observability in the tools they use everyday. With our latest integrations with GitHub, we are continuing to deliver on our vision of bringing intelligent observability across the tech ecosystem.”

With the New Relic Security RX integration for GitHub Copilot, development teams can gather runtime and build time context of software vulnerabilities to understand the risks of both the security issue and the potential fix. Providing security in context helps distinguish real-world exposure from noise, gives a better understanding of the scope of the problem, and reduces manual research and triaging to prioritize fixing issues that could pose a real risk that's live in production versus what's merely sitting in a repository. The analysis generated via the New Relic Security RX integration for GitHub Copilot can then help create a clear remediation plan that will automatically initiate a GitHub issue containing impact details, testing and verification steps, and acceptance criteria. GitHub Copilot then generates a pull request with all necessary context for engineers, providing insights for faster resolution and reduced toil for developers.

New Relic’s new instrumentation assistant makes GitHub Copilot a more holistic and trustworthy solution-builder. The solution detects and resolves missing instrumentation at deployment by calling GitHub Copilot to implement full coverage directly in pull requests. The integration helps GitHub Copilot users generate more complete solutions. Instead of just a functional code snippet, the user would receive a more fully-realized service that includes observability. When creating or updating a service, GitHub Copilot doesn't just write the backend logic - it instruments the full-stack by including APM, custom attributes for business logic, a GitHub Action for Change Tracking integration with New Relic, and even the Browser agent for front-end visibility.

With the integration between New Relic Service Architecture Intelligence and GitHub, developers can import rich data from GitHub accounts directly into New Relic. The functionality helps developers improve velocity and automate configuration setup. 

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Every digital customer interaction, every cloud deployment, and every AI model depends on the same foundation: the ability to see, understand, and act on data in real time ... Recent data from Splunk confirms that 74% of the business leaders believe observability is essential to monitoring critical business processes, and 66% feel it's key to understanding user journeys. Because while the unknown is inevitable, observability makes it manageable. Let's explore why ...

Organizations that perform regular audits and assessments of AI system performance and compliance are over three times more likely to achieve high GenAI value than organizations that do not, according to a survey by Gartner ...

Kubernetes has become the backbone of cloud infrastructure, but it's also one of its biggest cost drivers. Recent research shows that 98% of senior IT leaders say Kubernetes now drives cloud spend, yet 91% still can't optimize it effectively. After years of adoption, most organizations have moved past discovery. They know container sprawl, idle resources and reactive scaling inflate costs. What they don't know is how to fix it ...

Artificial intelligence is no longer a future investment. It's already embedded in how we work — whether through copilots in productivity apps, real-time transcription tools in meetings, or machine learning models fueling analytics and personalization. But while enterprise adoption accelerates, there's one critical area many leaders have yet to examine: Can your network actually support AI at the speed your users expect? ...

The more technology businesses invest in, the more potential attack surfaces they have that can be exploited. Without the right continuity plans in place, the disruptions caused by these attacks can bring operations to a standstill and cause irreparable damage to an organization. It's essential to take the time now to ensure your business has the right tools, processes, and recovery initiatives in place to weather any type of IT disaster that comes up. Here are some effective strategies you can follow to achieve this ...

In today's fast-paced AI landscape, CIOs, IT leaders, and engineers are constantly challenged to manage increasingly complex and interconnected systems. The sheer scale and velocity of data generated by modern infrastructure can be overwhelming, making it difficult to maintain uptime, prevent outages, and create a seamless customer experience. This complexity is magnified by the industry's shift towards agentic AI ...

In MEAN TIME TO INSIGHT Episode 19, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA explains the cause of the AWS outage in October ... 

The explosion of generative AI and machine learning capabilities has fundamentally changed the conversation around cloud migration. It's no longer just about modernization or cost savings — it's about being able to compete in a market where AI is rapidly becoming table stakes. Companies that can't quickly spin up AI workloads, feed models with data at scale, or experiment with new capabilities are falling behind faster than ever before. But here's what I'm seeing: many organizations want to capitalize on AI, but they're stuck ...

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