Infrastructure Provisioning cd deploy/terraform/aliyun terraform init terraform plan terraform apply Helm Deployment cd deploy/helm helm install aegis-core ./aegis-core \ --namespace aegis \ --create-namespace \ --set image.repository=<acr-registry>/aegis-core \ --set image.tag=lat
使用Terraform和Helm进行云基础设施部署体现了现代DevOps实践在AI安全平台中的应用。这种基础设施即代码(IaC)方法确保了部署的可重复性和一致性，同时支持阿里云等特定云平台，显示了平台对生产环境的适应性。
Add GCP WebVoyager benchmark runner and worktree tooling - Create benchmarks/infra/setup.sh — an idempotent script that provisions: - GCS bucket: gs://libretto-benchmarks - Artifact Registry repo: libretto-benchmarks (Docker) - Cloud Run Job: webvoyager-bench (4 CPU, 8Gi, 2h timeout)
令人惊讶的是：这个项目建立了一个完整的Google Cloud Platform基础设施来运行WebVoyager基准测试，包括存储桶、Docker镜像仓库和Cloud Run作业。它配置了相当强大的计算资源（4 CPU, 8Gi内存，2小时超时），表明该项目对自动化任务的性能和可扩展性有严格要求。
Routines execute on Anthropic-managed cloud infrastructure, so they keep working when your laptop is closed.
令人惊讶的是：Routines 在 Anthropic 管理的云基础设施上运行，即使你的笔记本电脑关闭，它们也能继续工作。这打破了传统自动化工具通常需要在本地设备上运行的限制，为用户提供了真正的'后台'自动化能力。
Today the move to cloud computing is replicating some of that early rhetoric—except, of course, that companies now reject any analogy with utilities, since that might open up the possibility of a publicly run, publicly controlled infrastructure.
That's a distinct possibility - if the infrastructure could be built with trust. Keep hoping.