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2nd Watch and New Relic Join Forces to Optimize AWS Environments

2nd Watch and New Relic have teamed up to help large companies tune the performance of the enterprise applications they have running on Amazon Web Services (AWS) infrastructure.

Through an agreement, 2nd Watch Managed Services, which offers 24/7/365 support for AWS workloads, will now include New Relic application performance data as part of the 2nd Watch Managed Services offering. The new partnership enables 2nd Watch Managed Services to use New Relic's pure-SaaS service to enhance the performance of their clients' modern software, reducing management complexity and providing greater satisfaction of their end user customers' experiences.

2nd Watch is among a small group of AWS Premier Consulting Partners. Its Managed Services offering for AWS users includes Service Level Agreements (SLA), high availability and billing management. 2nd Watch has over 60,000 AWS instances under management for brands such as Adobe Business Catalyst and Red Lion Hotels. Through a combination of software and services, 2nd Watch is known to save clients up to 70% on average AWS deployments.

"Many of our largest AWS customers want to simplify management of their cloud infrastructure,," says Bill Lapcevic, VP of Business Development and Customer Success at New Relic. "2nd Watch has developed the industry's most comprehensive Managed Services program for AWS deployments. We're excited to partner with 2nd Watch to help enterprises improve how they build and run modern software, using our SaaS solution as another great way to eliminate unnecessarily complex and expensive infrastructure."

"By partnering with New Relic, our customers have greater visibility into their AWS environments, from infrastructure metrics to application performance without any additional cost or complexity,," says Joel Rosenberger, EVP of Managed Services at 2nd Watch. "We continuously look for opportunities to improve our already robust Managed Services offering for the enterprise by including industry leading tools like New Relic for our customers."

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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 ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...

2nd Watch and New Relic Join Forces to Optimize AWS Environments

2nd Watch and New Relic have teamed up to help large companies tune the performance of the enterprise applications they have running on Amazon Web Services (AWS) infrastructure.

Through an agreement, 2nd Watch Managed Services, which offers 24/7/365 support for AWS workloads, will now include New Relic application performance data as part of the 2nd Watch Managed Services offering. The new partnership enables 2nd Watch Managed Services to use New Relic's pure-SaaS service to enhance the performance of their clients' modern software, reducing management complexity and providing greater satisfaction of their end user customers' experiences.

2nd Watch is among a small group of AWS Premier Consulting Partners. Its Managed Services offering for AWS users includes Service Level Agreements (SLA), high availability and billing management. 2nd Watch has over 60,000 AWS instances under management for brands such as Adobe Business Catalyst and Red Lion Hotels. Through a combination of software and services, 2nd Watch is known to save clients up to 70% on average AWS deployments.

"Many of our largest AWS customers want to simplify management of their cloud infrastructure,," says Bill Lapcevic, VP of Business Development and Customer Success at New Relic. "2nd Watch has developed the industry's most comprehensive Managed Services program for AWS deployments. We're excited to partner with 2nd Watch to help enterprises improve how they build and run modern software, using our SaaS solution as another great way to eliminate unnecessarily complex and expensive infrastructure."

"By partnering with New Relic, our customers have greater visibility into their AWS environments, from infrastructure metrics to application performance without any additional cost or complexity,," says Joel Rosenberger, EVP of Managed Services at 2nd Watch. "We continuously look for opportunities to improve our already robust Managed Services offering for the enterprise by including industry leading tools like New Relic for our customers."

The Latest

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 ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...