The ChatGPT Moment for Infrastructure: Why I Joined NeuBird

Yesterday’s operational models are breaking under the weight of today’s business demands. Organizations are running more and more workloads across increasingly complex IT environments (with multiple telemetry sources across on-prem and cloud) with teams that haven’t grown proportionally to match this increased complexity. As expectations for always-on applications keep rising, teams simply don’t have the capacity to keep up.

Despite more tools, detecting and resolving issues still takes significant time as teams navigate fragmented signals from disparate logs, metrics, traces and change data. I’ve spent decades building and scaling infrastructure platforms and seen this pattern repeated in one enterprise environment after another. 

The Pressure on Tech Leaders Is Building and Traditional SRE Workflows Can’t Keep Up

For business leaders tasked with protecting the top line, controlling costs to protect the bottom line and delivering great customer experience, reliability is no longer just an operations metric that lives on a spreadsheet. It now has an outsized impact on line-of-business outcomes and customer experience, 24/7/365. With downtime costing Global 2000 companies $400 billion a year¹, any tolerance for extended investigation and recovery times has effectively disappeared.

The heads of platform, engineering and infrastructure teams are expected to innovate faster and support critical app modernization and AI initiatives, while reducing firefighting time and maintaining reliability across increasingly complex IT stacks. Building in the right agentic workflows is key to accelerating time-to-market and staying competitive in the AI era. 

The problem with modern SREOps and incident management is not missing data but the time required to correlate signals and reason over distributed systems under production pressure.

What SRE teams need is leverage, not more alerts. There is a definite need to cut toil, supercharge productivity, give engineers time back for innovation and meaningfully reduce the constant on-call fatigue. Autonomous incident resolution from NeuBird AI makes it possible for engineering, SRE and platform teams to shift their focus from reactive troubleshooting to proactive innovation.

Why Modern Infrastructure Requires a New Approach to SRE and Incident Management

I’ve personally experienced how digital transformation, cloud-native architectures and AI initiatives add layers of complexity that traditional SREOps and incident management workflows weren’t designed to handle. 

Organizations routinely spend hundreds to thousands of hours diagnosing issues, assembling war rooms and manually correlating information that should be available at the start of every investigation. This is not sustainable and it’s not an effective use of highly skilled engineering talent.

As AI has been applied to SRE and incident management, solutions have largely converged around three approaches: automated alert triage and noise reduction, automated RCA, or and incident workflow automation. Each improves a specific part of the incident lifecycle, but none, on its own, fundamentally changes the core work of incident response, which remains largely manual. Humans still do the most tedious work: investigating, reasoning and connecting the dots under pressure.

Teams need a solution built in the AI era for the AI era. 

In my prior role at Pure Storage, I saw the power of NeuBird AI in action and immediately had an epiphany. It felt like a “ChatGPT moment” for infrastructure and reliability engineering. NeuBird doesn’t just tackle one part of the incident management lifecycle, it holistically addresses the entire problem: reducing devops and SRE toil, boosting developer productivity and protecting the business from outage induced downtimes.

After having run large scale production infrastructure and working with customers who run global infrastructure at scale, I firmly believe that world class  incident management and reliability engineering needs the trifecta of core capabilities as listed below. 

1. Automated Alert Triage and Noise Reduction
2. Automated Root Cause Analysis
3. Incident Workflow Automation

Most existing solutions out there, unfortunately, only address one of the above and even that only partially. Let’s unpack this below.

Automated Alert Triage and Noise Reduction –  Reducing alert fatigue is a necessary first step. Filtering non-actionable noise and clustering related alerts helps teams focus, but true incident resolution requires more than suppression. What’s needed is intelligent triage grounded in root cause understanding. 

NeuBird delivers this comprehensively. It doesn’t simply surface information or silence alerts. It goes further by understanding the underlying root cause of failure. Alerts are intelligently grouped  based on correlated signals and context across stacks, tools and clouds, helping teams resolve incidents quickly and eliminate repeat failures across on-prem and multi-cloud environments.

Automated Root Cause Analysis: Effective root cause analysis requires more than summarizing monitoring data or generating an initial hypothesis. Most existing solutions stop there. Comprehensive, actionable RCA demands cross-system reasoning and evidence-backed remediation steps. 

In hybrid and multi-cloud environments, incidents rarely reside within a single tool or stack. Yet many approaches remain confined to a single cloud or a single monitoring ecosystem.

Here is where NeuBird starts to shine. Beyond automated alert triage delivering dramatic reduction in alert fatigue, NeuBird AI builds a working memory and context of the infrastructure, much like an expert SRE embedded in your SRE and Devops teams. It autonomously delivers evidence-backed RCA and remediation steps in real time by analyzing telemetry across disparate systems and vendors. 

More importantly, it continuously learns: each incident strengthens NeuBird AI’s understanding of the environment, reducing toil and preventing repetitive work. 

Incident Workflow Automation: Most existing solutions mostly attempt to automate the operational work of incidents, including ticket creation and status updates. However, they lack deep integrations with monitoring tools and telemetry sources across distributed IT stacks on-premises and across multi-cloud.  Additionally, prior incident learnings are left buried in reports instead of contributing to institutional knowledge, leaving the underlying system unchanged and vulnerable to repeat failures.. 

NeuBird AI takes an end-to-end approach across incident workflows, closing the loop from investigation through resolution and post-incident learning.. It embeds directly into existing operations workflows to understand what happened and why. It then automatically generates context rich diagnoses, ticket updates and post-mortems based on real diagnostic context via integrations with other DevOps and observability tools like Datadog, PagerDuty, ServiceNow, Slack and GitHub and through agent-to-agent collaboration with Azure SRE Agent and Claude Code. Through this approach, NeuBird delivers workflow automation that is cross-system, context-aware, and production-ready.

The Bet I’m Making on NeuBird’s Agentic AI for SRE

As we can see, the NeuBird AI team has built something truly unique: an AI SRE agent built from scratch for modern infrastructure. As a customer, I experienced firsthand how NeuBird AI reduces toil, gives meaningful time back to engineering teams and delivers measurable, tangible ROI to the line of businesses.

Instead of starting from zero after every alert, engineers get early, evidence-backed understanding. Incidents that once required prolonged investigation and cross-functional war rooms are resolved faster and often autonomously with zero human intervention, averting outages and downtime. Seeing NeuBird AI’s impact as a customer made it clear this wasn’t just an incremental improvement, it is a fundamentally better approach to building, managing and running highly available enterprise infrastructure that is highly available with zero downtime 

Having worked with Gou and Vinod in our prior company Portworx, and knowing their passion for making customer lives easy, I couldn’t resist the NeuBird opportunity. NeuBird solves multiple major pain points for enterprise infrastructure teams, serves a very large underserved market that is ripe for disruption, has built a mind blowing product that looks straight out of science fiction and has one of, if not, the best engineering team on the planet in this space. 

I cannot wait to get this in the hands of our customers and partners!

I invite you to experience your own AI SRE epiphany today by signing up for our free trial. 

¹ Splunk, The Hidden Costs of Downtime