Overview
DinoCloud is an AWS Premier Partner that helps customers migrate, modernize, and operate confidently on AWS. Founded by technologists and driven by innovation, DinoCloud delivers agility, speed, and long-term value through deep technical expertise and enduring partnerships. Headquartered in Latin America and serving mid-market and enterprise clients globally, DinoCloud delivers end-to-end cloud transformations from initial migration to modernization, GenAI innovation, and managed operations. As DinoCloud expanded its managed services practice, the company sought to scale its operations with AI-powered CloudOps for MSPs, while staying true to its founding mission: being a trusted, long-term partner that helps customers innovate faster and operate smarter on AWS.
Challenge | Building a Centralized Operations Hub
As DinoCloud matured its managed services practice, the team faced increasing operational complexity. The company was supporting customers around the clock managing FinOps, security posture, and day-to-day operations but relied on multiple specialized tools to deliver these services. Each vendor focused on a narrow slice of the problem, creating silos and slowing down customer onboarding.
“We started with partners that focused mainly on FinOps,” explained Franco Salonia, CEO of DinoCloud. “As our practice grew, we had to integrate several different companies, each with their own tools and processes. That created complexity in how we onboarded and managed new customers.”
To scale effectively, DinoCloud needed an “operations hub” or a single platform where the team could centralize data, standardize workflows, and execute reviews more efficiently.
Historically, many established MSPs had solved this by building internal platforms, but DinoCloud wanted to move faster. “We didn’t want to spend years developing our own tool,” said Salonia. “We wanted a generalist operations hub that could deliver value immediately while still letting us plug in specialized ISVs as needed.”
Before adopting MontyCloud, even core processes like AWS Well-Architected Reviews required manual interviews and multi-hour meetings, delaying customer onboarding and slowing relationship building. DinoCloud needed a way to automate and centralize those steps, turning hours of manual work into minutes.
Solution | Automating CloudOps with MontyCloud and AI
Once DinoCloud onboarded its first managed-services customer into MontyCloud, the impact was immediate. For the first time, the team could view each customer’s entire cloud footprint, pinpoint pain points, and access all operational insights without switching contexts or navigating across multiple AWS accounts.
“That was the moment we said, this is the hub we need,” said Salonia. “We could see everything—incidents, logs, cost data—in one place and make faster, smarter decisions.”
MontyCloud became the central operations hub for DinoCloud’s MSP practice, enabling engineers to manage multiple environments, run AWS Well-Architected Reviews in minutes, and take corrective actions directly from a single pane of glass.
Building on that foundation, DinoCloud launched Rex, its proprietary AI agent designed to deliver instant, conversational CloudOps support. Rex responds to questions from customers in Slack surfacing recommendations, generating insights, and even triggering automated actions through MontyCloud’s Model Context Protocol (MCP) Server integration.
“Customer behavior is changing,” explained Salonia. “They don’t want endless dashboards. They want answers, immediately.”
With MontyCloud acting as the first MCP integrated into Rex’s ecosystem, DinoCloud can extend its AI agent beyond AWS data alone. When a customer asks about security posture, performance, or cost anomalies, Rex uses MontyCloud as its intelligence layer, retrieving and contextualizing the right data automatically.
This collaboration represents the next evolution of AI-powered managed services: a single conversational interface that connects to multiple MCPs, including MontyCloud, to provide unified, actionable insights across the cloud.
Results | Faster, Smarter and More Cost-Efficient Operations
By implementing MontyCloud and AI-driven automation, DinoCloud achieved measurable impact across both operational efficiency and customer value:
- 30–50% Faster Mean Time to Resolution (MTTR): Using Rex to surface incidents and recommendations directly in Slack reduced MTTR by up to half.
- 10–25% AWS Cost Reduction: Automated detection of idle or mis-sized resources helped customers proactively optimize costs across their environments.
- 70% Fewer AWS Console Logins: Teams now operate through conversational workflows, minimizing context switching and dashboard fatigue.
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FAQs
Q: What is AI-powered CloudOps for MSPs? A: AI-powered CloudOps for MSPs refers to the use of AI agents and automation to manage cloud operations, including incident response, cost optimization, and security posture monitoring, from a centralized platform. Rather than relying on multiple specialized tools and manual workflows, MSPs use AI to surface insights and trigger actions in real time, reducing resolution times and operational overhead.
Q: How did DinoCloud improve mean time to resolution (MTTR) using MontyCloud? A: DinoCloud integrated MontyCloud as its central operations hub and built Rex, an AI agent that surfaces incidents and recommendations directly in Slack. By connecting Rex to MontyCloud’s MCP Server, the team reduced MTTR by 30 to 50% by eliminating the need to manually navigate multiple dashboards or switch between tools.
Q: What is an MSP operations hub and why does it matter? A: An MSP operations hub is a single platform where managed service providers centralize customer cloud data, automate workflows, and execute reviews across all environments. Without one, MSPs typically rely on multiple point solutions for FinOps, security, and operations, which creates silos, slows onboarding, and increases complexity as the customer base grows.
Q: How can MSPs reduce AWS costs for customers using automation? A: MSPs can use automated tools to continuously detect idle or mis-sized resources across customer environments and surface recommendations in real time. DinoCloud achieved a 10 to 25% reduction in AWS costs for customers by using MontyCloud’s AI-powered CloudOps platform to flag and act on optimization opportunities without requiring manual analysis.
Q: What is an AI agent for CloudOps? A: A CloudOps AI agent is a conversational AI that connects to cloud operations platforms to answer questions, surface insights, and trigger automated actions, directly in tools like Slack. DinoCloud’s Rex agent uses MontyCloud as its intelligence layer via Model Context Protocol (MCP), allowing customers to ask about security posture, costs, or performance and receive actionable answers without logging into the AWS console.