Acorn, a company founded to help organisations implement AI-based technology solutions, has recently introduced Clio, an AI-powered command-line assistant designed to help engineers manage DevOps workflows.
In a blog post and a YouTube live stream, Acorn describes Clio as a "slightly grumpy but friendly assistant" which can handle various DevOps-related tasks through natural language interactions. The assistant's capabilities span several key areas of DevOps practice:
- Cloud Resource Management: Clio can interact with major cloud platforms, including AWS, Azure, GCP, and DigitalOcean, to manage infrastructure.
- Kubernetes Operations: Clio can deploy applications and manage clusters using tools like kubectl and helm.
- Docker Management: Clio offers functionality for monitoring container statuses and managing Docker images.
- GitHub Integration: Clio can interact with GitHub for repository management, issue tracking, and pull request handling.
- Internet Search: Clio can perform internet searches to provide relevant answers when additional information is needed.
- Automation and Scripting: The assistant can automate repetitive tasks to improve workflow efficiency.
- Secret Management: Clio provides options for secure storage and managing API keys and secrets.
Clio has a local execution model designed so users maintain control over their systems while also benefiting from AI-driven insights and automation. The assistant runs commands locally and always seeks user permission before acting. Acorn Labs addresses potential privacy and security concerns by stating that Clio does not save data server-side or use it for AI training purposes. Clio represents an application of large language models (LLMs) to DevOps tools. Clio can understand context, provide relevant information, and execute complex tasks by leveraging LLMs.
John Willis, a leading figure in the DevOps community, shared his experiences with Clio in a LinkedIn post. He noted that by using natural language questions, Clio automatically determines the appropriate agent (e.g., AWS, GCP, GitHub). Willis explored various use cases, including managing AWS resources, installing Google Cloud SDK, and interacting with GitHub repositories.
In one example, Willis used Clio to manage Google Cloud Platform resources. After setting up the gcloud CLI, Clio provided information about available GCP services and alerted him to a test instance that had been running for about a week. The assistant then helped stop the unnecessary instance, showing its potential for resource management.
Looking ahead, Willis expressed interest in exploring the integration of agentic processes with tools like Clio and recent SWE-Bench solutions. This suggests potential for further developments in AI-driven DevOps assistance, possibly incorporating more complex decision-making capabilities and predictive analytics.
I imagine a future where we can issue voice commands like Scotty on Star Trek and automate complex tasks with tools like GPTScript and Clio. These tools provide a glimpse into a future where AI streamlines and simplifies workflows, making commands more accessible and intuitive.
- John Willis
A recent article by Nick Hale provides further insights into Clio's practical applications. Hale emphasises Clio's ability to interact with the local filesystem, significantly improving development workflows. This feature reduces the need for constant context switching between terminals, IDEs, and AI assistants, allowing developers to refactor code or identify issues directly within their working environment.
Hale demonstrates Clio's capability to create and refine GitHub workflows by analysing project structures and documentation. In his example, Clio successfully generated a multi-platform build workflow for an Electron app, adapting its output based on additional context from the project's README file. This demonstration shows Clio's ability to understand complex project setups and generate appropriate CI/CD configurations.
The article highlights how Clio can gather contextual information directly from source code, making it easier to build tailored solutions without manually providing extensive context. Hale suggests that Clio can improve development velocity by automating routine tasks and providing intelligent assistance within the developer's existing workflow.
Clio's potential impact on DevOps work includes automating repetitive tasks, providing relevant information, and offering suggestions. Its integration with existing tools and workflows means that teams can potentially adopt Clio without significant disruption to current processes.
A further blog post from Acorn reviews the experience of Atulpriya Sharma, a developer advocate at Acorn, using Clio over a week. The author found Clio helpful in simplifying various tasks across different cloud platforms. However, Sharma did note some areas for improvement:
- Abrupt session interruptions requiring restarts
- Lack of status updates during long-running tasks
- Disappearance of previous prompts after follow-up commands
- Inconsistent handling of parallel tasks across different cloud platforms
Despite these issues, Sharma found Clio to be a valuable tool for streamlining DevOps workflows, particularly praising its ability to retry failed commands and adapt to different situations. The review concludes that while Clio shows promise in integrating AI into DevOps processes, there's room for refinement to enhance the overall user experience.
In conclusion, Clio leverages AI to provide context-aware, conversational support for various tasks, and is an interesting early effort to shape future practices.
Mac users can install Clio via Homebrew using the command: brew install gptscript-ai/tap/clio.