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* initial version of a FAST pre-install skill * first round of testing * Update fast-0-org-setup-prereqs skill with improved UX and local path handling - Add explicit lockout warning and stop condition if the user is not a member of the provided Admin Principal group. - Streamline bootstrap project selection to only prompt for an override if the active gcloud project is rejected. - Restrict dataset discovery strictly to the `fast/stages/0-org-setup/datasets/` directory. - Improve location handling by referencing `defaults.schema.json` for Standard GCP and auto-configuring fixed regions for GCD. - Add comprehensive `local_path` management: prompt for customization, create directories, move `defaults.yaml` to the local data folder, and symlink `0-org-setup.auto.tfvars` back to the stage directory. * add testing scenarios, implement initial changes for scenario 2 * move skills * move to a skills/fast subfolder * Refactor fast-0-org-setup prereqs skill * Add skill-turn-harness utility tool * Use relative markdown links for skill references * Use descriptive titles for markdown links in skill references * Add descriptions to each phase in the prerequisites workflow map * Use backslash for markdown line breaks in skill map * Update README security warning to mention default .gitignore * shebang * Update fast prereqs skill rules to force sequential question flow and refine harness tool with proper ctrl+c handling and slugified log paths * Move playbook-gcp-dev.yaml to fast/prerequisites/gcp-dev.yaml and update fast prerequisites * docs(skill-turn-harness): detail autonomous pond testing approach * docs(skill-turn-harness): add final_state_checks to pond architecture and update toc * Refine fast prereqs SKILL and gcp-dev playbook to strictly align with one-question-at-a-time rule * feat(skill-turn-harness): update playbook schema for autonomous persona mode * feat(skill-turn-harness): implement autonomous persona testing mode and fallback logic * docs(skill-turn-harness): document the three modes of testing and update ToC * implement timeout, schema validation, configurable cli * chore: remove accidentally committed log files * chore: ignore logs directory * feat(skill-harness): implement tool execution interception, configurable workspace, and modularized validation * feat(skill-harness): add model configuration and update README * fix(skill-harness): automatically inject -y flag to gemini commands * docs(skill-harness): add TODO.md with analysis for skill environment dependencies * feat(skill-harness): add working_dir support and clean up fixtures - Implement working_dir in harness to run tests in specific directories. - Rename test fixtures and playbooks to be more descriptive. - Add E2E test for working_dir. - Apply code quality improvements to harness.py (imports, linting). - Update README with working directory considerations and usage notes. - Update phase3-bootstrap-and-iam.md skill doc to add execution rule against creating temp scripts. * fix: capture customer_id and respect relative paths * Implement isolated temp workspace sandboxing with symlinks in test harness * Configure GCD manual autonomous playbook and align Phase 3/4 steps order * Fix linting and schema tests failures - Add missing license headers to tools/skill-turn-harness files. - Fix trailing spaces and newlines in playbooks. - Ignore tools directory in schema tests workflow. TAG=agy CONV=1bb75453-c3e2-448b-bae9-8e332a068012 * Fix Python formatting with yapf TAG=agy CONV=1bb75453-c3e2-448b-bae9-8e332a068012 * Refactor skill-turn-harness to use Antigravity SDK - Migrated harness from gemini-cli subprocesses to Antigravity SDK. - Implemented real-time step streaming and console logging. - Added color-coded terminal output (dark gray headers, blue inputs, pink outputs). - Collapsed excessive newlines in streamed thoughts. - Excluded harness codebase from workspace copy to prevent agent cheating. - Enabled skills folder copy to resolve agent lookup loops. - Added key validation and CLI --debug flag. * Fix autonomous turn layout: print Turn ID before execution - Moved the [Autonomous Turn X] header print to before running the agent turn. - This groups the real-time thinking and tool calls under the correct Turn ID block, instead of displaying them before the label. * Remove obsolete .log.md from prerequisites skill directory
Terraform Examples and Modules for Google Cloud
This repository provides end-to-end blueprints and a suite of Terraform modules for Google Cloud, which support different use cases:
- organization-wide landing zone toolkit used to bootstrap real-world cloud foundations
- a comprehensive source of lean modules that lend themselves well to changes
The whole repository is meant to be cloned as a single unit, and then forked into separate owned repositories to seed production usage, or used as-is and periodically updated as a complete toolkit for prototyping. You can read more on this approach in our contributing guide, and a comparison against similar toolkits here.
Organization toolkit (Fabric FAST)
Setting up a production-ready GCP organization is often a time-consuming process. Fabric FAST aims to speed up this process via two complementary goals. On the one hand, FAST provides a design of a GCP organization that includes the typical elements required by enterprise customers. Secondly, we provide a reference implementation of the FAST design using Terraform.
Modules
The suite of modules in this repository is designed for rapid composition and reuse, and to be reasonably simple and readable so that they can be forked and changed where the use of third-party code and sources is not allowed.
All modules share a similar interface where each module tries to stay close to the underlying provider resources, support IAM together with resource creation and modification, offer the option of creating multiple resources where it makes sense (eg not for projects), and be completely free of side-effects (eg no external commands).
The current list of modules supports most of the core foundational and networking components used to design end-to-end infrastructure, with more modules in active development for specialized compute, security, and data scenarios.
Currently available modules:
- foundational - billing account, Cloud Identity group, folder, service accounts, logging bucket, organization, project, projects-data-source
- process factories - project factory
- networking - DNS, DNS Response Policy, Cloud Endpoints, address reservation, NAT, VLAN Attachment, External Application LB, External Passthrough Network LB, External Regional Application Load Balancer, Firewall policy, Internal Application LB, Cross-region Internal Application LB, Internal Passthrough Network LB, Internal Proxy Network LB, IPSec over Interconnect, VPC, VPC firewall, VPC peering, VPN dynamic, HA VPN, VPN static, Service Directory, Secure Web Proxy
- compute - VM/VM group, MIG, COS container (coredns, mysql, onprem, squid), GKE cluster, GKE hub, GKE nodepool, GCVE private cloud
- data - AlloyDB instance, Analytics Hub, BigQuery connection, BigQuery dataset, Biglake Catalog, Bigtable instance, Dataplex, Dataplex Aspect Types, Dataplex DataScan, Cloud SQL instance, Spanner instance, Firestore, Data Catalog Policy Tag, Data Catalog Tag, Data Catalog Tag Template, Datafusion, Dataproc, GCS, Pub/Sub, Dataform Repository, Looker Core
- AI - AI Applications, Agent Engine, Agent Gateway
- development - API Gateway, Apigee, Artifact Registry, Cloud Build V2 Connection, Container Registry, Cloud Source Repository, Cloud Deploy, Secure Source Manager instance, Workstation cluster
- security - Binauthz, Certificate Authority Service (CAS), KMS, SecretManager, VPC Service Control, Certificate Manager
- serverless - Cloud Function v1, Cloud Function v2, Cloud Run v2
- other - Backup DR
For more information and usage examples see each module's README file.