Modern cloud infrastructure is riddled with inefficiencies that hinder both productivity and cost control.
Provisioning is often treated as the primary objective, yet this narrow focus neglects the complexity involved in orchestrating full environments—composed of interdependent services, configurations, and policies.
When provisioning errors occur, debugging and remediation are often slow and manual, causing delays and downtime that affect application reliability.
Many organizations also struggle with a lack of proactive control over the cost of infrastructure. Without real-time insights or guardrails, teams frequently over-provision or leave unused environments running, leading to unnecessary expenses.
Quali Torque helps our users manage infrastructure more easily by using AI to eliminate manual bottlenecks, streamline environment provisioning, and reduce wasted cloud spend.
This article outlines the common challenges that infrastructure teams face, explains how Torque leverages AI to solve them, and lays out the outcomes that our customers can expect as a result.
The Manual Bottlenecks Slowing Infrastructure Teams
Infrastructure teams face a range of challenges stemming from outdated, manual processes. These issues not only delay innovation but also lead to overprovisioned and underutilized cloud environments. The most common slowdowns include:
- Manual Environment Creation
- Developers must submit tickets for infrastructure teams to deliver non-production environments manually. Even teams with automation tools for provisioning infrastructure still need to orchestrate and validate those resources to deliver a functional environment. We’ve seen cases where these requests take days to weeks to complete, creating a delay that extends timelines for critical processes like application delivery timelines or customer POCs.
- Siloed IaC Assets and Tribal Knowledge
- Infrastructure as Code (IaC) assets such as Terraform files are often fragmented across repositories and maintained by individual engineers with undocumented processes.
- Inconsistent Governance and Compliance
- Enforcing policies such as tagging standards, cost constraints, and role-based access controls often requires manual checks or custom scripts, leading to inconsistencies and delays.
- Limited Visibility Into Environment Usage
- Once environments are provisioned, there is little visibility into usage, performance, or cost, making it difficult to optimize or decommission idle resources.
- Cumbersome Day-2 Operations
- Common maintenance tasks—such as restarting a service, scaling an environment, or rotating secrets—require manual intervention, increasing operational overhead.
These issues combine to form a cycle of inefficiency that hinders both speed and accountability in managing cloud environments.
How Quali Torque Uses AI to Streamline Infrastructure Management
Quali Torque addresses these challenges with an AI-powered platform that automates environment provisioning, policy enforcement, and Day 2 operations. Torque uses machine learning and natural language processing to interpret infrastructure code, orchestrate resources, and continuously optimize cloud environments. Here’s how:
1. AI-Generated Environment Blueprints
Torque discovers the user’s existing infrastructure code (e.g., Terraform) and other resources to generate reusable environment blueprints. These blueprints abstract away the complexity of individual components and allow teams to provision full-stack environments with a single click or API call.
Teams can describe their desired environment in plain language (e.g., “I need a dev environment with a Kubernetes cluster, RDS database, and S3 bucket”) and Torque’s AI will generate the corresponding environment blueprint. This provides an AI assistant-like functionality for IaC that eliminates the need to write and test new code manually.
This brief video shows how it works:
Environment blueprints eliminate the redundancies of building, validating, and provisioning environments manually. This also enables users to streamline the delivery of environments.
For routine, non-production environments supporting large numbers of users daily, Torque can automate the daily provisioning and termination of environments in line with standard working hours. Torque’s native Operation Hub and integrations with CI/CD platforms and other tools distribute access to live environment outputs for developers and engineers who need them. This eliminates routine provisioning processes while also preventing wasted cloud costs due to over-provisioning.
For short-lived, ad hoc environment deployments, Torque provides a native self-service catalog where developers and engineers can click to deploy environments on demand. Admins can set maximum runtimes for these environments, encrypt all secrets required to provision them, and define input parameters so end users can simply click to run the environment they need.
Torque also enforces governance policies at the blueprint level to ensure that all provisioned environments adhere to organizational standards for security, compliance, cost limits, and other requirements. This allows our users to accelerate provisioning of infrastructure while reducing the risk of ungoverned resource deployments.
We’ve seen cases where DevOps and engineering teams have eliminated environment delivery processes that required up to two weeks to complete. When considering the cost of those delays, this combination of AI-generated blueprints and streamlined delivery has eliminated millions of dollars in productivity losses for Torque users.
2. AI Insights to Maintain Environment Uptime
Torque monitors all environments deployed via the platform and automatically triggers notifications about infrastructure errors or configuration drift so infrastructure admins can reconcile them quickly and easily.
To accelerate this process, Torque uses AI to diagnose the root cause of infrastructure errors and provide recommendations for admins to reconcile the issue and get the environment up and running again.
This also helps to prevent productivity losses by reducing downtime that can disrupt the work relying on environments.
3. Ongoing Support for Managing Environments
Torque provides access to a persistent AI Copilot that can answer user questions and generate resources to help our users’ lives easier.
This level of support can range from serving answers to questions about the platform from documentation to the creation of code for new environments or policy files.
This helps to reduce the learning curve needed to contribute to the delivery and maintenance of infrastructure so our users can prevent operational bottlenecks from slowing their teams down.
4. AI-Generated Cloud Cost Optimization Recommendations
As part of Torque’s ability to monitor the state of all environments, that platforms can also identify the capacity in use among live infrastructure deployed to support those environments.
This provides valuable insight to determine whether actively deployed cloud resources are actively supporting users, or sitting idle and accruing unnecessary costs on the cloud bill.
Torque’s AI tools automatically flag any resource that appears to be idle, estimates the cost savings from terminating them, and compiles them in a dashboard for administrators to review. This includes the estimated cost, the user who provisioned the resource, and access to all details for the environment it supports so administrators can evaluate and communicate with their teams before making these decisions.
Torque administrators can also set workflows to automate the termination of cloud resources that Torque’s AI has identified as idle, thereby preventing wasted cloud costs proactively.
These insights have helped Torque users save more than 50% on cloud costs for some of their non-production environments. In one case, Torque’s AI insights found that more than 80% of cloud infrastructure costs were waste.
When combined with the impact on productivity, these AI capabilities have eliminated millions of dollars in wasted operational costs for our customers.
To learn more, watch a brief demo of Torque:
