Lightrun brings live runtime context to AI site reliability engineering. Lightrun has announced real-time AI SRE built on live, in-line runtime context. This enables AI agents and engineering teams to dynamically generate missing evidence without redeployments, prove root causes with live execution data ("ground truth"), and validate fixes directly in live environments. The mass adoption of AI agents and coding assistants has accelerated code generation, outpacing reliability. This has shifted developer time from writing code to verifying and fixing issues, and moved the development bottleneck to runtime, where behavior is complex and often non-deterministic. As enterprises accelerate investment in AI-driven reliability and autonomous operations, this has created a market for AI SREs valued at billions of dollars. Despite this growth, most available 'AI SRE' tools are optimized for post-incident workflows and limited to relying on traditional, static telemetry that was already captured. When logs are missing, traces are incomplete, or execution context is unclear, teams are left to guess. Engineers are forced into long reactive cycles of redeploys, rollbacks, and manual validation. Lightrun's AI SRE closes this gap by bringing live, code-level runtime context directly into the reliability loop. Instead of passively observing telemetry, the Lightrun AI SRE can safely interact with live systems via Lightrun's Sandbox to create new evidence, test hypotheses, and validate outcomes against real execution behavior. This capability transforms AI SRE from a reactive post-incident advisor into a trusted, runtime-verified autonomous engineer that ensures reliability by design. Built on Lightrun's Runtime Context engine, the AI SRE supports reliability across the entire SDLC, from proactive issue detection during development and testing ("peace time") to autonomous investigation and remediation during live incidents ("war time"). It enables teams to understand how code truly behaves in runtime, close visibility gaps without redeploying, and resolve issues with confidence. Lightrun is designed for every team responsible for the behavior, reliability, or outcomes of running software. "Lightrun addresses a structural visibility gap in the emerging AI site reliability engineering workflows (SRE) market," said Jim Mercer, Program Vice President, Software Development, DevOps, and DevSecOps at IDC. "By integrating dynamic instrumentation into SRE workflows, the company enables validation of root cause and remediation against live execution, reducing reliance on static, pre-instrumented telemetry and strengthening reliability across the software development lifecycle." With Lightrun's AI SRE, engineering and reliability teams benefit from: * Root cause analysis based on new evidence from live environments, without requiring prior instrumentation. * Runtime-validated code changes to eliminate guesswork and reduce rollback-and-redeploy cycles. * Live issue debugging in safe remote sessions with execution-level behavior inspections. * Dynamic telemetry to running systems to fill visibility gaps that traditional observability tools cannot address. * Reduced reliance on expensive war rooms, due to autonomous remediation and the ability to receive a code fix of incidents before escalating to a human. * Resilience to "unknown unknowns" introduced by multiple AI agents across the SDLC. Zahi Kapeluto, AVP Engineering, AT&T, stated, "Modern, AI-driven software reliability depends on connecting telemetry to real execution context. Without understanding how code behaves in live environments, alerts and metrics alone don't tell the full story. Lightrun helps our teams close that gap by exposing runtime behavior directly, enabling faster investigation and more confident remediation." "AI cannot resolve what it cannot see. Lightrun's runtime context engine allows AI to see application behavior at a single line level of granularity, which positions us to streamline remediation for any software issues in real-time," added Ilan Peleg, CEO of Lightrun. "Trusted by Fortune 100 companies and the largest enterprises in the world, Lightrun is proud to lead the way in making self-healing software a reality." More about

Lightrun brings real-world runtime visibility to AI code generation. Software observability startup Lightrun Inc. today launched a new Model Context Protocol solution that offers fully integrated Runtime Context for artificial intelligence code-writing assistants. The new solution is pitched as a "step change" in autonomous code writing that gives tools such as Cursor and GitHub Copilot full visibility into how code behaves after deployment. In doing so, it fills in what Lightrun claims is a missing piece of the AI development ecosystem. The MCP solution seeks to address the issue that AI assistants can generate code rapidly, but, as shown in studies, fail at high rates once exposed to real-world traffic, dependencies and workloads. Added to the mix is that once the code leaves the integrated development environment or IDE, AI cannot see what takes place in staging, preproduction or production, forcing teams to spend lengthy amounts of time debugging and refactoring bad code. Lightrun's Runtime Context directly addresses the problems by bridging the gap between the IDE, the AI assistant and runtime to provide crucial context to the agent and the developer behind it. Using the new solution, developers can ask their coding assistant to check staging traffic before writing a module, investigate a production failure or add the instrumentation needed to validate behavior. Lightrun's MCP acts as a secure bridge to allow AI agents to add logs and traces in real time, capture snapshots, investigate issues safely and even suggest fixes, all without requiring engineers to manually reproduce issues. Developers can then fix the code with a single rebuild and verify immediately, reducing resolution time from days to minutes. "AI has taken over much of the creative part of coding," said co-founder and Chief Executive Ilan Peleg. "However, debugging across environments has remained painfully manual. With Runtime Context, AI can finally participate in the full lifecycle by writing code, validating and debugging it and remediating issues based on real-world behavior." The Runtime Context model enables AI tools to trigger remote debugging sessions across staging, preproduction and production environments, access production-grade telemetry in real time, propose fixes based on actual runtime behavior and deliver code that is reliable, stable and ready for deployment. With the release, Lightrun customers gain access to faster debugging cycles, higher deployment reliability and AI-generated code that better withstands real traffic and dependencies. Lightrun is a venture capital-backed startup that has raised $115 million in funding across four rounds, including rounds of $18 million in July 2024 and $70 million in April. Investors in the company include Insight Partners LP, Glilot Capital Partners LP, GTM Capital, Sorenson Capital, Accel Partners LP and Citigroup Inc. Image: Lightrun. A message from John Furrier, co-founder of SiliconANGLE: Support its mission to keep content open and free by engaging with theCUBE community. Join theCUBE's Alumni Trust Network, where technology leaders connect, share intelligence and create opportunities. * 15M+ viewers of theCUBE videos, powering conversations across AI, cloud, cybersecurity and more * 11.4k+ theCUBE alumni - Connect with more than 11,400 tech and business leaders shaping the future through a unique trusted-based network. SiliconANGLE Media is a recognized leader in digital media innovation, uniting breakthrough technology, strategic insights and real-time audience engagement. As the parent company of SiliconANGLE, theCUBE Network, theCUBE Research, CUBE365, theCUBE AI and theCUBE SuperStudios - with flagship locations in Silicon Valley and the New York Stock Exchange - SiliconANGLE Media operates at the intersection of media, technology and AI. Founded by tech visionaries John Furrier and Dave Vellante, SiliconANGLE Media has built a dynamic ecosystem of industry-leading digital media brands that reach 15+ million elite tech professionals. Its new proprietary theCUBE AI Video Cloud is breaking ground in audience interaction, leveraging theCUBEai.com neural network to help technology companies make data-driven decisions and stay at the forefront of industry conversations.

Israeli startup Lightrun, which has developed solutions for real-time monitoring and correction of code, has announced the completion of a $70 million Series B financing round led by Accel and Insight Partners, with participation from Citi, Glilot Capital, GTM Capital, and Sorenson Capital.