How the ASI Biont AI Agent and Terraform Turn DevOps into a Dialogue: A Step-by-Step Guide to Automating Infrastructure through Natural Language

Introduction

Managing cloud infrastructure is one of the most time-consuming tasks for DevOps engineers. Terraform (official documentation — terraform.io/docs) has become the standard for Infrastructure as Code (IaC), but mastering it requires time: you need to write HCL configurations, remember the syntax of resources, providers, and modules. Even experienced specialists spend hours creating VPCs, configuring load balancers, or auditing state. What if these tasks could be solved with simple phrases in natural language: "deploy a VPC in AWS," "scale the cluster to 5 nodes," "find configuration drift"?

That's exactly how the integration of the ASI Biont AI agent with Terraform works. You give a command in the chat — the agent writes, tests, and applies Terraform configurations itself. No control panels, "add integration" buttons, or waiting for patches from developers. All connection happens through dialogue: you provide the API key from your provider (AWS, GCP, Azure), and ASI Biont generates integration code on the fly for your API. This is not a hypothetical concept — it is a working tool available right now at asibiont.com. In this article, we will look at how to set up the integration, what scenarios it covers, and why it saves time and money.

What is Terraform and why connect it to an AI agent?

Terraform is a tool from HashiCorp for managing infrastructure through declarative configuration files (HCL). You describe the desired state of resources — virtual machines, networks, load balancers, databases — and Terraform brings your infrastructure to that state. IaC (Infrastructure as Code) allows you to version changes, automate deployments, and avoid "manual drift." However, even in 2026, writing correct configurations remains a bottleneck: you need to understand hundreds of providers, remember resource attributes, and handle dependencies properly.

The ASI Biont AI agent removes this barrier. It acts as an interpreter between your natural language and the Terraform API. You no longer need to open documentation to remember how to declare a security group or configure an S3 bucket. You tell the agent what you want — and it generates a ready main.tf, runs terraform plan and terraform apply (with your permission). This is especially valuable for:
- Teams without a dedicated DevOps engineer — startups, small departments.
- Complex multi-cloud environments — a single interface for AWS, GCP, and Azure.
- Quick prototypes and test environments — deploy infrastructure in minutes.

How the integration works: architecture and the "connection through dialogue" principle

The key difference between ASI Biont and traditional low-code platforms is the absence of pre-installed connectors. You won’t find a "Add Terraform Integration" button in the interface. Instead, you simply write in the chat: "Connect Terraform to my AWS account." The AI agent requests API keys or an access token (e.g., Access Key ID and Secret Access Key for AWS). After you provide the keys, ASI Biont dynamically writes integration code using the Terraform provider for your cloud and the API documentation.

This approach is based on the agent's ability to analyze OpenAPI specifications and provider documentation in real-time. It does not use pre-made templates — each time it adapts to the provider version and region. Thus, you can connect not only popular clouds but also any services with a REST API (e.g., Cloudflare, DigitalOcean, Yandex Cloud, Linode). The only requirement is an API key.

Here's a simplified workflow:
1. The user sends a request in natural language: "Create a VPC in AWS with CIDR 10.0.0.0/16."
2. ASI Biont parses the intent, determines the provider (AWS), region (default us-east-1 or user-specified), and resource (aws_vpc).
3. The agent generates a main.tf file with the necessary blocks (provider, resource), as well as variables.tf and outputs.tf.
4. If you have already provided keys, the agent runs terraform init and terraform plan.
5. It returns the check result: "Plan: 1 resource will be created. Apply?"
6. Upon your confirmation — terraform apply. You receive the ID of the created resource.

All actions are logged, and you can always request an audit of the current state: "Show me the list of all EC2 instances" — ASI Biont will execute terraform state list and display the result.

Specific use cases

1. Deploying a VPC via Telegram

Task: A startup team needs to quickly create an isolated network for a new microservice in AWS. Previously, a DevOps engineer would write the configuration manually, taking about 40 minutes including searching for the correct syntax for aws_vpc, aws_subnet, aws_internet_gateway.

Solution with ASI Biont:
- The user writes in the Telegram bot (or web chat): "Create a VPC named 'prod-vpc', CIDR 10.0.0.0/16, with two public and two private subnets in us-west-2. Set up an Internet Gateway and route tables."
- The AI agent generates about 50 lines of HCL code in seconds, checks for syntax errors, and outputs the plan.
- After confirmation — the infrastructure is ready in 2 minutes.

Result: Time reduced by 10–20 times. Errors related to typos in resource names are eliminated.

2. Scaling an EKS cluster

Task: Increase the number of worker nodes in an Amazon EKS cluster from 3 to 5 due to increased load. Without automation, you have to edit the aws_eks_node_group configuration and rerun terraform apply.

Solution with ASI Biont:
- Request: "Increase min_size and desired_size in node group 'workers' of cluster 'my-cluster' to 5."
- ASI Biont finds the existing state, generates the changes (diff), and applies them.
- During the process, the agent checks if the size exceeds account limits and warns about possible cost increases.

3. State audit and drift detection

Task: Detect discrepancies between the declared configuration and the real state of the infrastructure (drift detection). Usually terraform plan is run manually, and then changes are analyzed.

Solution with ASI Biont:
- Request: "Conduct a state audit, find configuration drift compared to the last commit."
- The AI agent runs terraform plan -detailed-exitcode, parses the output, and provides a report in natural language: "3 resources modified outside Terraform detected: security group 'web-sg' has an extra rule, S3 bucket 'logs' changed via console."
- You can immediately ask to fix the drift: "Restore the security group according to the configuration."

4. Creating multi-cloud infrastructure

Task: Deploy an application using AWS for compute and GCP for BigQuery. Traditionally, you need to write two sets of configurations and combine them with terraform_remote_state.

Solution with ASI Biont:
- Request: "Create a t3.micro EC2 instance in AWS and a dataset in GCP BigQuery. Link them via IAM."
- The agent independently generates configurations for both providers, manages state files, and outputs a single report.

Step-by-step connection (no control panels)

To get started, you don't need to register in a personal account and look for an "Integrations" section. Everything happens in the chat with the AI agent:

1. Open the chat at asibiont.com or in a connected messenger (Telegram, Slack).
2. Write: "Connect Terraform to my AWS account." ASI Biont will reply: "Okay, I will need AWS Access Key ID and Secret Access Key with permissions to create resources. Please provide them via a secure field." (Keys are transmitted encrypted and not stored in logs.)
3. Provide the keys (or token). If you use GCP — specify the path to the service account JSON.
4. AI writes integration code: the agent downloads the latest version of the Terraform provider (~50 MB) and generates the provider configuration. The whole process takes 10–20 seconds.
5. Done. You can immediately verify: "Show me the list of available regions" or "Create a test resource."

Important: you do not give ASI Biont direct access to your console — it works via the Terraform API using your keys. All changes are confirmed by the user before application (an auto-mode with a set of rules can optionally be enabled).

Why it's beneficial: savings and automation of routine

Time savings. According to ASI Biont user estimates (based on a forum survey), typical infrastructure creation/modification tasks are completed 5–10 times faster. If a DevOps engineer spends 10 hours per week writing configurations, the integration can save up to 8 hours — those hours can be redirected to architecture or CI/CD improvements.

Error reduction. Configuration drift is one of the main causes of incidents. ASI Biont automatically checks each change for correctness (e.g., no duplicate resources, proper dependencies). If a forbidden combination is detected (e.g., a public subnet without an internet gateway), the agent will warn you.

Versatility. ASI Biont connects to any service with a REST API. There is no list of "supported integrations" — if a service has an API, you can manage it through natural language. Terraform is just one example. You can also simultaneously manage Kubernetes (via kubectl), monitoring (Datadog, Grafana), and CI/CD (GitHub Actions, GitLab CI).

Security. Keys are transmitted sessionally and not stored in plain text. The AI agent does not have access to the management console — only to the Terraform state via the API. Additionally, you can always revoke access by deleting the keys at the provider.

Conclusion

The integration of ASI Biont and Terraform is not just automation of routine. It is a paradigm shift: DevOps ceases to be a privilege of engineers who know HCL by heart. Now any team member, from team lead to developer, can deploy a VPC, scale a cluster, or conduct an audit. The AI agent takes on code generation, error checking, and command execution, leaving the human as the strategist.

The main advantage is the absence of limitations. You don't wait for an update from developers to connect a new service. ASI Biont connects to any API through dialogue. Try it yourself: today, open asibiont.com, ask the agent to connect Terraform to your cloud, and give your first command, for example, "Create an S3 bucket for logs." In a few minutes, you'll be amazed at how natural infrastructure management can be.