How to Store CI/CD Build Artifacts Using the Fast.io API

Build artifacts include the compiled files, binaries, container images, and test logs generated during your CI/CD process. Managing these files is necessary to keep delivery pipelines fast and reliable.

When teams rely strictly on the native storage of their CI runner, they often hit retention limits and storage quotas. Test reports and binaries get trapped inside the CI environment. That makes it hard for QA engineers, outside stakeholders, or AI agents to review the outputs without specialized access.

Moving your artifacts to a dedicated workspace decouples the build process from storage. This prevents redundant compilation and speeds up execution. Instead of rebuilding the same dependency tree or binary across multiple stages, your pipeline can pull the verified artifact directly from the workspace. This keeps things consistent across all deployment environments. Centralizing your artifacts also creates a single source of truth for debugging and auditing.

Helpful references: Fast.io Workspaces, Fast.io Collaboration, and Fast.io AI.

Most modern CI/CD platforms include some form of native artifact storage. But these built-in solutions are usually designed for short-term convenience over long-term reliability or advanced workflows. For instance, GitHub Actions artifact storage defaults to a multiple-day retention policy and imposes overall repository storage limits.

If you exceed those limits, your older artifacts are automatically deleted. That becomes a major problem if you need to roll back to a previous software version or investigate an old bug. Sharing these native artifacts also requires granting users access to your version control repository. You cannot easily send a securely linked test log to a contractor without exposing your source code.

The biggest limitation is the lack of intelligence. Native storage solutions act as passive file directories. They do not index the contents of your test logs or make them searchable for automated debugging. As development teams increasingly rely on AI to speed up incident resolution, passive storage creates a bottleneck in the automation loop.

Fast.io offers distinct advantages for teams building complex or agentic workflows, especially compared to the storage bundled with your code repository.

• Built-in Intelligence and RAG: Fast.io serves as an intelligent workspace rather than a passive file directory. When you upload test logs or deployment manifests, Intelligence Mode automatically indexes those files. This built-in Retrieval-Augmented Generation (RAG) means you do not need a separate vector database to make your build data searchable by AI agents.
• Capacity and Persistence: The Fast.io free agent tier includes 50GB of persistent storage, a 1GB maximum file size limit, and 5,000 monthly credits. This handles large compiled binaries and heavy debug logs that would otherwise exhaust native CI quotas.
• Agentic Handoffs and Ownership Transfer: Because Fast.io supports ownership transfer, an automated agent can create a dedicated incident workspace, compile the logs, and then transfer ownership of that workspace to the engineering lead.
• Reactive Webhooks: With built-in webhook support, you can trigger downstream automation the moment a build artifact lands in the workspace.

Give Your AI Agents Persistent Storage

Create an intelligent workspace to store your build outputs, manage pipeline logs, and give your AI agents access to build data. Built for fast api guide artifact storage workflows.

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Before writing your pipeline scripts, you need to decide how to organize your build outputs within the Fast.io workspace. A clear directory hierarchy makes it easier for both humans and AI agents to locate the right files.

We recommend using a pattern that incorporates the repository name, branch, and commit hash. For example, a reliable directory path might look like /builds/api-service/main/a1b2c3d4/. Organizing your uploads with dynamic variables like the Git commit hash keeps a clean and traceable history of every pipeline execution.

For release candidates, you can adopt a semantic versioning structure like /releases/v1.2.4/. This separation keeps ephemeral pull request artifacts from cluttering the directory of production-ready binaries. Fast.io's API allows you to push files directly to these specific folders dynamically, keeping your storage architecture aligned with your branching strategy.

To configure your pipeline, you need to establish secure programmatic access to your Fast.io workspace. The platform uses standard HTTP protocols, making it compatible with any environment that supports web requests.

First, generate an API key from your workspace settings. You will need to store this token securely within your CI platform's secret manager, such as GitHub Secrets or GitLab CI/CD variables. Never commit this token directly into your version control system, as it grants write access to your workspace.

The Fast.io API uses standard REST conventions. To upload an artifact, you send a multipart form data request to the file upload endpoint. You need to include your API key in the authorization header and specify the target path within the workspace. Because the API uses Streamable HTTP, it handles large file uploads reliably without timing out. This helps when transferring heavy container images or database snapshots.

GitHub Actions is a common CI platform, and integrating it with Fast.io takes just a few lines of YAML. In this example, we compile a sample application and use a command-line HTTP client to upload the resulting binary to a Fast.io workspace.

This YAML example demonstrates a standard GitHub Actions workflow:

name: Build and Upload Artifact
on:
  push:
    branches: [ main ]
jobs:
  build:
    runs-on: ubuntu-latest
    steps:
      - name: Check out repository
        uses: actions/checkout@v3
      - name: Compile application
        run: |
          mkdir -p build
          echo "Compiled binary data" > build/app-binary.tar.gz
      - name: Upload artifact to Fast.io
        env:
          FASTIO_API_KEY: ${{ secrets.FASTIO_API_KEY }}
          WORKSPACE_ID: ${{ secrets.FASTIO_WORKSPACE_ID }}
          COMMIT_HASH: ${{ github.sha }}
        run: |
          curl -X POST "https://api.fast.io/v1/workspaces/${WORKSPACE_ID}/files" \
            -H "Authorization: Bearer ${FASTIO_API_KEY}" \
            -F "file=@build/app-binary.tar.gz" \
            -F "path=/builds/${COMMIT_HASH}/"

This configuration ensures that every push to the main branch results in a specific folder inside your workspace. You can then retrieve the exact binary corresponding to any commit for testing or rollback. The workflow relies entirely on native shell commands, so you do not need to install custom plugins or dependencies.

If your team uses GitLab CI, the setup is similar. GitLab uses a .gitlab-ci.yml file to define pipeline stages. The following YAML example shows how to package your build output and transfer it securely to Fast.io.

stages:
  - build
  - archive
build_app:
  stage: build
  script:
    - echo "Building the application..."
    - mkdir -p bin
    - echo "Application executable" > bin/release.bin
  artifacts:
    paths:
      - bin/
upload_to_fastio:
  stage: archive
  script:
    - echo "Uploading to Fast.io workspace..."
    - curl -X POST "https://api.fast.io/v1/workspaces/${FASTIO_WORKSPACE_ID}/files" \
      -H "Authorization: Bearer ${FASTIO_API_KEY}" \
      -F "file=@bin/release.bin" \
      -F "path=/releases/${CI_COMMIT_SHORT_SHA}/"
  only:
    - main

In this workflow, the build stage creates the artifact, and the archive stage handles the external transfer. Storing the Fast.io credentials in GitLab's CI/CD variables ensures the pipeline runs securely without exposing sensitive keys. The only: - main directive pushes only production-ready builds to the permanent release folder.

Storing artifacts in Fast.io opens up new workflows because the platform acts as an intelligent workspace where humans and AI collaborate. Fast.io offers 251 MCP tools via Streamable HTTP and SSE, mapping every user interface capability to an agentic tool.

When your pipeline fails, it typically generates hundreds of lines of error logs. By uploading these logs to Fast.io, an AI assistant connected via OpenClaw can review the data right away. You can instruct the agent to analyze the error log, cross-reference it against recent code changes, and summarize the root cause of the failure.

Because Fast.io supports ownership transfer, an automated agent can create a dedicated incident workspace, compile the logs and error reports into a readable summary, and then transfer ownership of that workspace back to the engineering lead. This reduces the time engineers spend hunting for debugging information and speeds up incident resolution. Storing your CI/CD artifacts in Fast.io gives your entire team, human or AI, direct access to build data and deployment logs.

Security is a top priority when handling proprietary source code and deployment binaries. Your artifact storage strategy needs to prevent unauthorized access while remaining open to your deployment scripts.

Fast.io provides granular access controls for complex team structures. You can configure your workspaces so that CI runners have append-only permissions. This means they can upload new artifacts but cannot overwrite or delete historical builds. This immutability helps with auditing and compliance, ensuring that a compromised CI runner cannot alter past releases.

Since Fast.io works securely with enterprise environments, you can invite external QA contractors or security auditors into the workspace without issuing them native CI credentials. They can view the test reports and binaries in an isolated environment. To protect concurrent automated processes, Fast.io features file locks that prevent multiple agents or scripts from attempting to modify the same configuration file at the same time.