Selefra
The open-source policy-as-code software that provides analysis for Multi-Cloud and SaaS environments, you can get insight with natural language (powered by OpenAI).
Category | Compliance & Governance |
---|---|
Community Stars | 526 |
Last Commit | 1 year ago |
Last page update | 19 days ago |
Pricing Details | Free and open-source |
Target Audience | DevOps teams, Cloud architects, Security professionals, FinOps teams. |
Selefra addresses the complex challenge of managing and analyzing multi-cloud and SaaS environments by providing a unified, policy-as-code approach. This open-source software allows for comprehensive analytics across over 30 services, including AWS, GCP, Azure, Alibaba Cloud, Kubernetes, Github, Cloudflare, and Slack.
Technically, Selefra's architecture is built around providers that extract and analyze infrastructure data from various cloud services. Each provider must be configured with the necessary credentials to access and analyze the respective cloud resources. For example, the Azure Provider for Selefra can extract data from many Azure services, while the Github Provider does the same for Github services. This modular approach enables extensive coverage and flexibility in managing diverse cloud environments.
Operationally, Selefra leverages a CLI-based interface for installation, initialization, and application of policies. Users can initialize a project with selefra init
and apply policies using selefra apply
. The tool also integrates with GPT models to analyze cloud resources and provide suggestions for security, cost, and architecture optimizations. However, this integration requires configuring an OpenAI API key, and the analysis is limited by the API's usage limits and performance constraints.
Key operational considerations include the need for proper credential management for each provider and the potential for performance degradation when analyzing large-scale cloud environments. Additionally, the community-driven nature of Selefra means that new features and improvements are continually being developed, but this also implies that some features may still be in development or have varying levels of stability.