
New Relic expanded its Instant Observability ecosystem of integrations, tools, and pre-built observability resources by nearly 20% in six months, and added enhancements to the product experience to empower every engineer to get started with observability in minutes.
As part of New Relic’s commitment to make observability an open, data-driven and daily engineering practice, the catalog now offers more than 470 integrations with cloud services, open source tools, and enterprise technologies, contributed and maintained by the community. This release features contributions from partners such as Akamai, Atlassian, CircleCI, Cloudflare, Netlify, PagerDuty, and Postman. Instant Observability is available as part of New Relic’s generous free pricing tier to help every engineer get started without talking to sales or providing a credit card.
New Relic introduced Instant Observability in October 2021 with a mission to make it easy for every engineer to get started with observability and data-driven engineering by codifying the collective experience of the world’s observability experts. Since then, Instant Observability has helped tens of thousands of engineers get started with observability, reporting improvements in uptime, reliability, and operational efficiency to deliver better customer experiences that fuel innovation and growth.
"We launched Instant Observability last year with a mission to make it easy for every engineer to get started with observability in five minutes. Since then, we've seen tremendous demand from customers to add observability into every stage of the software lifecycle," said Peter Pezaris, New Relic SVP, Strategy and User Experience. "We are thrilled to continue working with an industry-leading group of partners to extend New Relic's use cases and honor our commitment to help engineers share data in context and grow observability into an open, data-driven practice for all."
The latest enhancements to Instant Observability include a new guided user onboarding interface, support for a wider range of instrumentation methods, and a richer, more connected platform experience. As a result, engineers gain the flexibility to seamlessly instrument and monitor their stack, regardless of whether their applications are running on hosts, in Docker containers, or other environments. In addition, it’s even easier for engineers to get more value from their data, with connected instrumentation flows that automatically take users to the most relevant New Relic product experiences such as application management, log management, or infrastructure monitoring.
In addition to user experience improvements, Instant Observability has expanded its ecosystem of integrations to help extend the value of observability to teams who rely on many tools to monitor the health of their systems. With integrations made in partnership with leading technology companies, Instant Observability combats tool sprawl and data silos by empowering engineers with a single unified platform to monitor their entire stack, regardless of where their data comes from.
New partner quickstarts include:
- CI/CD and DevOps platforms that allow developers to gain visibility into the performance and health of their continuous integration and deployment pipelines, APIs, and web application development workflows. With these quickstarts, users can view New Relic observability data alongside their release pipelines to help users boost release velocity and quality. Key contributors include Atlassian, CircleCI, Postman, Netlify, Delphix, ReleaseIQ, and more.
- Content delivery network (CDN) platforms that help engineers improve service reliability, protect customer applications, and ensure optimal online experiences for their end users. With these quickstarts, users can get faster log delivery and eliminate cloud storage middleware costs by sending data directly to New Relic. They also provide insight into key metrics around web traffic such as saved bandwidth, alerts on cyberattacks, and slow loading pages. Key contributors include Cloudflare, Akamai, and Fastly.
- Artificial intelligence (AI) and machine learning (ML) platforms that allow engineers and data scientists to send model performance telemetry data into New Relic. With these quickstarts, data and DevOps teams have one place to monitor and visualize critical signals like recall, precision, and model accuracy alongside their apps and infrastructure. Key contributors include Algorithmia, Amazon SageMaker, Aporia, Comet, DagsHub, Mona Labs, Superwise, and Truera.
New Relic Instant Observability is generally available to all engineers as part of the New Relic platform.
The Latest
In the world of digital-first business, there is no tolerance for service outages. Businesses know that outages are the quickest way to lose money and customers. For smaller organizations, unplanned downtime could even force the business to close ... A new study from PagerDuty, The State of AI-First Operations, reveals that companies actively incorporating AI into operations now view operational resilience as a growth driver rather than a cost center. But how are they achieving it? ...
In live financial environments, capital markets software cannot pause for rebuilds. New capabilities are introduced as stacked technology layers to meet evolving demands while systems remain active, data keeps moving, and controls stay intact. AI is no exception, and its opportunities are significant: accelerated decision cycles, compressed manual workflows, and more effective operations across complex environments. The constraint isn't the models themselves, but the architectural environments they enter ...
Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...
In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ...
Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...
Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...
Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...
The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...
The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...
In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...