The Alert Fatigue Antidote: How Astreya is Closing the Cloud Remediation Gap

SAN JOSE, Calif. – November 10, 2026 – The modern enterprise cloud is a noisy place. For the better part of a decade, chief information security officers have poured billions into Cloud Security Posture Management (CSPM) tools. The result? Unprecedented visibility, accompanied by paralyzing alert fatigue. Security tools flag misconfigurations faster than overextended engineering teams can clear them, creating a dangerous backlog of unpatched vulnerabilities sitting in ticketing purgatory.

Today, Astreya—an AI-powered global IT managed services provider and Cognizant company—launched two new solutions designed to bridge this exact gap. Astreya CloudCoach and Astreya CloudCrew aim to consolidate the fractured process of finding a cloud risk and actually shipping the fix.

By pairing continuous posture management with an intent-driven infrastructure engineering platform, Astreya is attempting to solve a fundamental operational bottleneck. It is a bold play that challenges the traditional boundaries between security alerting and platform engineering, signaling a broader market shift from passive visibility to automated execution.

From Visibility to Execution: Closing the Remediation Void

The CSPM market is heavily saturated with pure-play vendors like Wiz, Orca Security, and Palo Alto Networks’ Prisma Cloud. These platforms excel at agentless scanning and deep visibility, mapping complex cloud environments to identify critical risks. However, the operational reality for most enterprises is that finding the vulnerability is only ten percent of the battle. The remaining ninety percent involves determining who owns the resource, deciphering what the fix looks like, and manually writing the infrastructure code to patch it without breaking production.

CloudCoach targets this friction directly. The platform runs more than 520 automated checks across AWS, Azure, Google Cloud, and Kubernetes, mapping assets against CIS, NIST, and over 15 other regulatory frameworks. But rather than simply dumping alerts into a dashboard, it utilizes a guided remediation layer called Coach-AI. This layer contextualizes findings, assigns ownership, and explains the necessary remediation steps directly against the resource in question.

"Enterprises have spent the past several years buying visibility into their cloud spend, and most now have plenty of it—what they still lack is a dependable path from knowing to doing," says Romil Bahl, Chief Executive Officer at Astreya. "With CloudCoach and CloudCrew, we are establishing governed execution across the cloud estate. We have built the assessment layer that ranks genuine risk and the build layer that closes the risks and gaps under the customer's own policy, so every change reaching production is prioritized, approved, and evidenced."

By ranking findings and attaching timestamped audit records, CloudCoach attempts to transform a chaotic alert queue into a prioritized roadmap. Yet, the true differentiator lies in what happens next.

Intent-Driven Infrastructure: Building Compliance into the Code

If CloudCoach is the diagnostician, CloudCrew is the surgeon. Once a risk is identified, or when an engineer simply needs to provision new infrastructure, CloudCrew acts as an intent-driven platform. An engineer describes the required infrastructure outcome in natural language, and CloudCrew translates that intent into pre-validated Terraform or OpenTofu code.

This touches on a critical evolution in Platform Engineering and Infrastructure as Code (IaC). Traditional IaC workflows rely on policy-as-code tools—like HashiCorp Sentinel or Open Policy Agent (OPA)—to validate code after it has been written, acting as a gatekeeper before deployment.

CloudCrew flips this paradigm by enforcing network standards, encryption requirements, and compliance rules during the build phase.

"The market has been moving toward shift-left security for years, but generating code that is inherently compliant from the moment of conception is the holy grail," notes an independent cloud security architect familiar with Astreya's architecture. "If a tool can actually prevent non-compliant infrastructure from existing in the code repository in the first place, you eliminate a massive amount of rework and friction between security and DevOps."

When CloudCrew generates a change, it arrives in the customer's version control ready for human review, complete with a record of every check it passed. If a deployment fails, the AI names the likely cause—such as a missing permission or capacity limit—and proposes a fix. Crucially, every approved pattern is saved in a private library, creating a compounding efficiency effect where subsequent requests become progressively faster.

The MSP Productization Playbook

The launch of CloudCoach and CloudCrew is not just a technology story; it is a strategic maneuver by Astreya and its parent company, Cognizant. Cognizant's acquisition of Astreya, a deal valued at approximately $600 million that closed earlier this year, was explicitly designed to bolster Cognizant's "AI builder" stack.

Historically, Managed Service Providers (MSPs) relied on third-party software to deliver client outcomes. Today, elite MSPs are productizing their own internal operational tooling to compete directly with pure-play SaaS vendors. Astreya's new platforms are prime examples of this trend. Both solutions originated from Astreya's own delivery operations, built by engineers who manage complex multi-cloud environments for demanding technology firms, including several of the "Magnificent Seven."

"These solutions started as tools our own delivery teams built because the work demanded it," says Abhilash Mana, Senior Vice President, Practices and Technology at Astreya. "When you run cloud operations for some of the most demanding technology environments in the world, you learn quickly which guardrails matter and which findings are just noise. Every check in CloudCoach and every pattern in CloudCrew earned its place in a live customer environment first. That is the part you cannot shortcut, and it is why the engineers on the other side of the table trust what comes back."

By bringing battle-tested internal tools to the commercial market, Astreya bypasses the theoretical phase of software development. The integration of these tools into the wider Astreya stack—including AI OpsHub, Pictor, and Lynx—provides Cognizant with a formidable, end-to-end AI infrastructure offering that can be deployed globally.

Trusting AI with the Keys to the Cloud

Despite the compelling value proposition, the integration of generative AI into infrastructure deployment carries inherent risks. The industry is hyper-aware of AI "hallucinations"—instances where models generate factually incorrect or nonsensical outputs. In the context of cloud infrastructure, a hallucination isn't just a bad chatbot response; it could mean provisioning a database with an exposed public IP address or violating strict data residency laws.

To mitigate these risks, Astreya has implemented strict safety guardrails that align with frameworks like CISA’s Secure Software Development Framework (SSDF) and the NIST AI Risk Management Framework.

First, CloudCrew relies heavily on a Human-in-the-Loop (HITL) model. The AI does not unilaterally deploy code to production; rather, it generates reviewable changes that must pass through role-based approvals. "Engineers approve every step," ensuring that human expertise remains the final arbiter of what enters the production environment.

Second, the platform mitigates hallucination risks by orchestrating pre-approved, hardened IaC modules rather than generating code from scratch every time. By assembling trusted components and enforcing policy-as-code during generation, the blast radius of any potential AI misinterpretation is severely restricted.

As enterprise cloud environments grow increasingly complex, the traditional model of relying on disparate tools for visibility, ticketing, and manual code generation is reaching its breaking point. Solutions like CloudCoach and CloudCrew represent the necessary next phase of cloud operations: a closed-loop system where identifying a vulnerability automatically triggers the creation of its governed, compliant fix. For organizations drowning in security alerts, the ability to finally bridge the gap between knowing and doing may be the most valuable capability of all.