In the world of cloud computing, managing costs can feel like a battle against a mythical hydra—for every budget you wrangle, two new unexpected expenses sprout up. It's a relentless, data-heavy task that requires constant vigilance, deep analysis, and a knack for spotting anomalies. For most engineering teams, it's a distraction from their core mission: building great products.
But what if we could delegate this entire function? Not just automate a few reports, but hand over the keys to an autonomous system with a single, high-level objective: "Keep our cloud costs in check."
This isn't science fiction. This is the promise of agentic AI. We decided to run an experiment to answer the question: Can an autonomous digital worker, like ivy.do, effectively manage its own cloud budget?
Before we introduce our AI protagonist, let's appreciate the complexity of the problem. Cloud cost management isn't just about reading a bill. It involves:
This combination of repetitive monitoring and nuanced decision-making makes it a perfect challenge for an autonomous agent.
Enter Ivy, the autonomous digital worker from .do. Unlike a chatbot that simply reacts, Ivy is designed to be a proactive teammate. You assign it complex, long-running business processes, and it executes them as a reliable software service. It's the perfect candidate for our experiment.
Our goal was to create a "Cloud Accountant" agent. Here’s how we designed its mission using the ivy.do platform.
First, we gave our digital worker a clear identity and purpose. It's not just a script; it's a specialist with a role.
An agent is only as good as the tools it can use. We provisioned our Ivy agent with API access to the same services a human FinOps analyst would use:
This is where the magic happens. We didn't write a rigid, line-by-line script. We gave the agent a set of high-level instructions, defining the "what" and letting Ivy handle the "how." This agentic workflow allows for more flexible and intelligent execution than simple AI automation.
Using the .do SDK, the assignment looked like this:
import { ivy } from '@do/sdk';
// Configure our FinOps digital worker
const cloudAccountant = ivy.create('finops-agent-001', {
persona: 'Cloud Cost Analyst'
});
// Assign the continuous budget management task
const job = await cloudAccountant.assign({
task: 'Continuously monitor and manage the cloud budget for project "Phoenix".',
schedule: 'Run every 12 hours.',
budgetThreshold: 5000, // Monthly budget in USD
instructions: [
'Fetch daily cost data from the AWS Cost Explorer API.',
'Identify services with a >20% cost increase week-over-week.',
'Cross-reference high-cost resources with Datadog metrics to find underutilized instances (avg CPU < 10%).',
'If projected monthly spend exceeds budgetThreshold, send a high-priority alert to "eng-leads@example.com" via courier.do.',
'Generate a daily summary report in markdown and post it to the #cloud-spend Slack channel.'
]
});
console.log(`Job ${job.id} assigned. The Cloud Accountant is now on duty.`);
Within the first 48 hours, the agent flagged a staging database that was oversized and running 24/7, despite only being used during work hours. It generated a report showing the high cost and low CPU utilization and sent an alert to the team. A human would have eventually found this, but the agent found it immediately.
The key takeaway wasn't just the money saved. It was the shift in how the team operated.
This experiment proves that business process automation is evolving. We're moving beyond simple scripts and into a world of autonomous, agentic systems that can take ownership of complex business functions.
Managing cloud costs is just one example. Imagine deploying agents to handle customer onboarding, lead qualification, data processing, or support ticket triage. Any complex, long-running workflow is a candidate for an autonomous digital worker.
By giving an AI agent a clear goal, the right tools, and the autonomy to act, you can transform your most challenging business processes into simple, reliable services.
Ready to build your first digital teammate? Visit ivy.do to learn how to deploy an autonomous agent with a simple API.
What is ivy.do?
Ivy is an autonomous digital worker on the .do platform. You can configure and deploy Ivy to perform specific business functions and complex workflows, delivered as a reliable software service.
What kinds of tasks can Ivy perform?
Ivy excels at a wide range of tasks, including data processing, lead qualification, customer onboarding, report generation, and support ticket triage. It can integrate with other APIs and services to execute multi-step workflows.
Is Ivy just another chatbot?
No. While a chatbot reacts to user input in a conversation, Ivy is an autonomous agent that proactively executes complex, long-running business processes in the background. Ivy is a worker, not just a conversationalist.