Best DevOps Software for Terraform - Page 2

Kubiya is an AI-powered internal developer platform that leverages conversational AI to streamline DevOps processes. By integrating with existing tools and platforms, Kubiya enables developers to interact with their systems using natural language, reducing the time-to-automation and enhancing productivity. The platform offers AI teammates capable of handling routine tasks such as managing Jira queues, provisioning infrastructure, and enforcing just-in-time cloud permissions, allowing engineering teams to focus on higher-value activities. Kubiya's agentic-native design ensures predictable and secure operations, with enterprise-grade security measures and compliance with organizational policies. The platform integrates seamlessly into communication workflows, supporting tools like Slack and Microsoft Teams, to provide a conversational interface for task delegation and automation.

Galgos AI is your AI DevOps Assistant for cloud infrastructure, enabling you to generate compliant, secure infrastructure-as-code from simple natural-language prompts. It integrates AI-guided DevOps best practices to automatically produce Terraform, CloudFormation, and Kubernetes manifests that adhere to organizational compliance policies and security standards. By requesting resources in plain English—such as network configurations, identity and access management settings, encryption, logging, and monitoring- you accelerate cloud provisioning while benefiting from built-in modules for cost optimization and industry-standard frameworks (CIS, NIST, PCI DSS). It keeps its policy library up to date, performs real-time validation with remediation suggestions, and offers drift detection with auto-generated fixes. Generated code can be previewed, versioned, and integrated into existing CI/CD pipelines via API or CLI, with support for GitHub Actions, Jenkins and HashiCorp Vault.

CtrlStack manages a wide variety of operational activities and sources of changes to reduce risks, track change impact, and find root causes of production issues fast. Relationship mapping in observability is finding meaningful connections and interactions between the data – metrics, events, logs, and traces. We use a native graph database to represent this “data between the data” at speed and scale. Get an end-to-end visibility of all changes across commits, configuration files, and feature flags in one click. Capture all the context of an incident at the moment it occurs, and at any time during diagnosis and resolution, to avoid reverting each other’s changes. Get insights into what, when, and who made the change, and how it impacts operations. Collaborate across teams with shared data knowledge through a DevOps graph.