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New Relic Announces Kiro Integration

New Relic announced the integration of its Model Context Protocol (MCP) Server with Kiro, Amazon Web Services' (AWS) AI-native, agentic development environment. 

The one-click integration enriches agentic coding workflows with real-time observability insights, closing the feedback loop between planning, shipping, and validating to boost developer velocity, improve code quality, and reduce mean time to resolution (MTTR) of performance issues.

With the New Relic integration for Kiro, engineers can query live metrics, events, logs, and traces in natural language, bringing New Relic AI directly into Kiro's spec-driven workflow — no context-switching required.

“As organizations navigate this agentic transformation, they face a critical and immediate need to safely unify AI coding agents and live business data,” said New Relic Chief Product Officer Brian Emerson. “By integrating our MCP Server with Kiro, we are combining the rigorous, spec-driven development on AWS with New Relic’s deep operational insights. The result is a seamless, one-click solution that empowers developer teams to confidently ship quality code with minimal operational friction and toil.”

The integration enables Developers, DevOps engineers, and SREs who use Kiro to:

  • Surface real-time production context inside Kiro's spec-driven development cycle: Developers can query New Relic's full-stack telemetry directly inside Kiro to validate code performance against technical specs. This unifies planning and execution, ensuring AI-generated code changes are operationally validated before shipping, while keeping developers focused within the integrated development environment (IDE).
  • Unify agentic development workflows with observability for AI: By feeding New Relic’s observability insights directly to Kiro’s agents, teams can shift from manual troubleshooting to AI-assisted investigation. As a result, developers can rapidly identify root causes and implement precise code fixes for performance bottlenecks, significantly slashing MTTR.
  • Enable instant observability with one-click implementation: Built as a Kiro power, the integration enables one-click deployment that eliminates the need for complex, manual configuration. This allows engineering teams to immediately access rich observability insights, accelerating their transition to spec-driven, AI-native development.

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New Relic Announces Kiro Integration

New Relic announced the integration of its Model Context Protocol (MCP) Server with Kiro, Amazon Web Services' (AWS) AI-native, agentic development environment. 

The one-click integration enriches agentic coding workflows with real-time observability insights, closing the feedback loop between planning, shipping, and validating to boost developer velocity, improve code quality, and reduce mean time to resolution (MTTR) of performance issues.

With the New Relic integration for Kiro, engineers can query live metrics, events, logs, and traces in natural language, bringing New Relic AI directly into Kiro's spec-driven workflow — no context-switching required.

“As organizations navigate this agentic transformation, they face a critical and immediate need to safely unify AI coding agents and live business data,” said New Relic Chief Product Officer Brian Emerson. “By integrating our MCP Server with Kiro, we are combining the rigorous, spec-driven development on AWS with New Relic’s deep operational insights. The result is a seamless, one-click solution that empowers developer teams to confidently ship quality code with minimal operational friction and toil.”

The integration enables Developers, DevOps engineers, and SREs who use Kiro to:

  • Surface real-time production context inside Kiro's spec-driven development cycle: Developers can query New Relic's full-stack telemetry directly inside Kiro to validate code performance against technical specs. This unifies planning and execution, ensuring AI-generated code changes are operationally validated before shipping, while keeping developers focused within the integrated development environment (IDE).
  • Unify agentic development workflows with observability for AI: By feeding New Relic’s observability insights directly to Kiro’s agents, teams can shift from manual troubleshooting to AI-assisted investigation. As a result, developers can rapidly identify root causes and implement precise code fixes for performance bottlenecks, significantly slashing MTTR.
  • Enable instant observability with one-click implementation: Built as a Kiro power, the integration enables one-click deployment that eliminates the need for complex, manual configuration. This allows engineering teams to immediately access rich observability insights, accelerating their transition to spec-driven, AI-native development.

The Latest

The enterprises that will define the next decade are not the ones that deployed the most technology. They are the ones who understood what their technology was actually doing. That distinction is not a philosophical point. It is the central operational challenge facing every organization that has spent the last five years modernizing at speed ...

AI is becoming the operating system of the enterprise. It acts as an invisible coordination layer that understands intent, connects systems, and executes work across complex SaaS environments. Previously, employees had to click through multiple systems — CRM, ERP, support tools, collaboration platforms — to complete a single task. Now, instead of navigating each application manually, they can simply state what they need to accomplish ...

In 2026, the cost of downtime or an outage is no longer just a technical inconvenience; it's a $600 billion wake up call for global businesses. As our digital ecosystems become  more interconnected, each touchpoint introduces new risks and multiplies the consequences when things go wrong. And the data is clear: aggregate downtime costs  for Global 2,000 companies have surged 50% since 2024, reaching a staggering $600 billion ...

Deloitte found that 74% of enterprises expect to deploy agentic AI solutions in the next 24 months. However, the rush to deployment is outpacing foundational work, though. Only 21% of enterprises have fully formed agent governance models in place. The result? AI agents deployed without guidance or governance begin to function as fragmented islands of complexity ...

Cloud spending is no longer viewed as a passthrough IT expense, but as a strategic financial lever that directly impacts innovation capacity, profitability and enterprise resilience, according to the CFO Cloud Cost Optimization Report from Azul ...

As AI moves from generating responses to performing actions, the need for trust increases exponentially. And as organizations enlist AI agents for increasingly sophisticated business processes, trust is going to be the single most important theme for spurring adoption. What can organizations do to build trustworthy AI agents? ...

I've spent a lot of time in the channel, and one thing I keep coming back to is this: a partner program is only as good as what it looks like in the field. Many programs look great on paper, but when a partner is in front of a customer navigating a complex hybrid environment or trying to make the case for AI-powered observability, the gap between what a vendor promises and what it actually delivers becomes very clear, very fast ...

Enterprises today operate in a real-time environment where uninterrupted access to trusted data has become a baseline expectation for users, applications and automated systems. Traditional DataOps models, built on manual effort and human triage, cannot keep pace with this always active demand. AI agents are emerging as the operational backbone, ensuring consistent data availability, reinforcing trustworthiness and enabling a level of scale that manual processes cannot achieve ...

For decades, trust in the digital workplace rested on familiar signals. We trusted faces on video calls, voices on the phone, and emails that appeared to come from people we knew. These cues felt human and intuitive. They anchored how decisions were made, approvals were granted, and access was authorized. AI-powered deepfakes have quietly broken that model ...

Cloud migration was supposed to be a one-way door. For most enterprises, it turns out it isn't. Cloud data repatriation is a real and growing trend. A new survey ... finds that 89% of organizations plan to expand their on-premises infrastructure footprint over the next two years — and 75% have already moved at least some workloads back from public cloud in the past 24 months. The findings point to a broad rethinking of where data belongs ...