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New Relic Supports Amazon VPC Flow Logs on Amazon Kinesis Data Firehose

New Relic announced support for Amazon Virtual Private Cloud (Amazon VPC) Flow Logs on Amazon Kinesis Data Firehose to reduce the friction of sending logs to New Relic.

Amazon VPC Flow Logs from AWS is a feature that allows customers to capture information about the IP traffic going to and from network interfaces in their Virtual Private Cloud (VPC). With New Relic support for Amazon VPC Flow Logs, both AWS and New Relic customers can quickly gain a clear understanding of a network’s performance and troubleshoot activity without impacting the network throughput or latency.

Network telemetry is challenging even for network engineers. To unlock cloud-scale observability, engineers need to explore VPC performance and connectivity across multiple accounts and regions to understand if an issue started in the network or somewhere else. To solve this, New Relic has streamlined the delivery of Amazon VPC Flow Logs by allowing engineers to send them to New Relic via Kinesis Data Firehose, which reliably captures, transforms, and delivers streaming data to data lakes, data stores, and analytics services. With New Relic’s simple “add data” interface, it only takes moments to configure Amazon VPC Flow Logs using the AWS Command Line Interface (AWS CLI) or an AWS CloudFormation template. Instead of digging through raw logs across multiple accounts, any engineer can begin with an Amazon Elastic Compute Cloud (Amazon EC2) instance they own and begin to explore the data that matters, regardless of the AWS account or AWS Region.

“New Relic continues to invest in our relationship with AWS. Helping customers gain visibility into their cloud networking environment increases their overall application observability,” said Riya Shanmugam, GVP, Global Alliances and Channels at New Relic.

“New Relic’s connected experience for Amazon VPC Flow Logs, paired with the simplicity of using Kinesis Data Firehose, enables our joint customers to easily understand how their networks are performing, troubleshoot networking issues more quickly, and explore their VPC resources more readily.” said Nishant Mehta, Director of PM – EC2 and VPC Networking at AWS.

With the New Relic support for Amazon VPC Flow Logs on Kinesis Data Firehose, customers can:

- Monitor and alert on network traffic from within New Relic.

- Visualize network performance metrics such as bytes and packets per second, as well as accepts and rejects per second across every TCP or UDP port.

- Explore flow log deviations to look for unexpected changes in network volume or health.

- Diagnose overly restrictive security group rules or potentially malicious traffic issues.

The New Relic support for Amazon VPC Flow Logs on Kinesis Data Firehose is available to all New Relic Full Platform users.

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New Relic Supports Amazon VPC Flow Logs on Amazon Kinesis Data Firehose

New Relic announced support for Amazon Virtual Private Cloud (Amazon VPC) Flow Logs on Amazon Kinesis Data Firehose to reduce the friction of sending logs to New Relic.

Amazon VPC Flow Logs from AWS is a feature that allows customers to capture information about the IP traffic going to and from network interfaces in their Virtual Private Cloud (VPC). With New Relic support for Amazon VPC Flow Logs, both AWS and New Relic customers can quickly gain a clear understanding of a network’s performance and troubleshoot activity without impacting the network throughput or latency.

Network telemetry is challenging even for network engineers. To unlock cloud-scale observability, engineers need to explore VPC performance and connectivity across multiple accounts and regions to understand if an issue started in the network or somewhere else. To solve this, New Relic has streamlined the delivery of Amazon VPC Flow Logs by allowing engineers to send them to New Relic via Kinesis Data Firehose, which reliably captures, transforms, and delivers streaming data to data lakes, data stores, and analytics services. With New Relic’s simple “add data” interface, it only takes moments to configure Amazon VPC Flow Logs using the AWS Command Line Interface (AWS CLI) or an AWS CloudFormation template. Instead of digging through raw logs across multiple accounts, any engineer can begin with an Amazon Elastic Compute Cloud (Amazon EC2) instance they own and begin to explore the data that matters, regardless of the AWS account or AWS Region.

“New Relic continues to invest in our relationship with AWS. Helping customers gain visibility into their cloud networking environment increases their overall application observability,” said Riya Shanmugam, GVP, Global Alliances and Channels at New Relic.

“New Relic’s connected experience for Amazon VPC Flow Logs, paired with the simplicity of using Kinesis Data Firehose, enables our joint customers to easily understand how their networks are performing, troubleshoot networking issues more quickly, and explore their VPC resources more readily.” said Nishant Mehta, Director of PM – EC2 and VPC Networking at AWS.

With the New Relic support for Amazon VPC Flow Logs on Kinesis Data Firehose, customers can:

- Monitor and alert on network traffic from within New Relic.

- Visualize network performance metrics such as bytes and packets per second, as well as accepts and rejects per second across every TCP or UDP port.

- Explore flow log deviations to look for unexpected changes in network volume or health.

- Diagnose overly restrictive security group rules or potentially malicious traffic issues.

The New Relic support for Amazon VPC Flow Logs on Kinesis Data Firehose is available to all New Relic Full Platform users.

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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 ...

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