In-context performance data to support incident remediation: Instead of siloed, disconnected data across ITSM and several monitoring and observability platforms, New Relic telemetry data and changes flow directly into the Rovo Ops agent. This enables your service agents to quickly detect anomalies and incidents-like a recent commit being modified-without context-switching between multiple tools. AI-suggested fixes based on past incident data:
Advanced debug logging is the cornerstone of high-performance applications. Whether working in cloud-native, microservice or monolithic architecture, strong debug logging practices enable developers to resolve problems, maintain system health and support scalable operations. To succeed in today's fast-paced environment, development teams need modern logging strategies, refined best practices and resilient error-handling techniques. Debug logging refers to the internal operation of an application, generating detailed messages that detect variable states and execution branches.
Observability directly improves system stability and availability. The survey revealed that 75% of businesses report a positive return on their observability investments. Nearly one in five (18%) say they are realizing a 3-10x return on investment. For businesses, the top benefits of observability are: Reduced unplanned downtime (55% of leaders) Improved overall operational efficiency (50%) Reduced security risk (46%) Engineering Efficiency Observability also improves engineering productivity and satisfaction by reducing the time engineers spend on reactive tasks.
Vercel has rolled out the AI Gateway for production workloads. The service provides a single API endpoint for accessing a wide range of large language and generative models, aiming to simplify integration and management for developers. The AI Gateway allows applications to send inference requests to multiple model providers through one endpoint. It supports bring-your-own-key authentication, which means developers can use their own API keys from providers such as OpenAI, Anthropic, or Google without paying an additional token markup.
MCP provides a structured interface for tools and AI agents to query observability data, enabling developers to surface traces, metrics, and logs in their IDE without switching context. This high-level capability is designed to streamline debugging and reduce time spent navigating between systems, while also laying the groundwork for consistent access across AI assistants and integrations. Originally launched as an open source project, MCP is now offered by Honeycomb as a managed service.
In modern, distributed systems, that work is harder than ever. Services depend on other services, deployments happen constantly, and small failures ripple into larger ones. While teams scramble to piece things together, customers are already feeling the impact, and the business is losing money by the minute. For years, the industry used $5,600 per minute as the average cost of an outage as was suggested by Gartner in 2014.
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