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Replace Infisical product name, email addresses, domain names, and file names with Hanzo KMS equivalents across docs, templates, tests, and configuration. Functional references to upstream packages (@infisical/quic, artifacts-cli.infisical.com, CLI binary) are preserved with clarifying comments since they reference actual upstream software dependencies.
59 lines
2.6 KiB
Plaintext
59 lines
2.6 KiB
Plaintext
---
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title: "Docker"
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description: "Learn how to run KMS with Docker."
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---
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Prerequisites:
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- Basic knowledge of [Docker](https://www.docker.com/)
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- Have Docker installed on your system. If not, follow the installation guide [here](https://docs.docker.com/get-docker/).
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KMS is available as a single Docker image to ease deployment.
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This Docker image only includes the application code, meaning you must supply a connection to a Postgres database and a Redis instance.
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The following guide provides a detailed step-by-step walkthrough on how you can deploy KMS with Docker.
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<Steps>
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<Step title="Pull the KMS Docker image">
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Visit [Docker Hub](https://hub.docker.com/r/ghcr.io/hanzoai/kms/tags) and select a version of KMS image you would like to deploy.
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Then run the following command in your terminal to pull the specific KMS Docker image.
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```
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docker pull ghcr.io/hanzoai/kms:<version>
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```
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Remember to replace `<version>` with the docker image tag of your choice.
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</Step>
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<Step title="Start KMS">
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For a minimal installation of KMS, you must configure `ENCRYPTION_KEY`, `AUTH_SECRET`, `DB_CONNECTION_URI`, `SITE_URL`, and `REDIS_URL`. [View all available configurations](/self-hosting/configuration/envars).
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We recommend using Cloud-based Platform as a Service (PaaS) solutions for PostgreSQL and Redis to ensure high availability.
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Once you have added the required environment variables to your docker run command, execute it in your terminal to get KMS up and running.
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For example:
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```bash
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docker run -p 80:8080 \
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-e ENCRYPTION_KEY=f40c9178624764ad85a6830b37ce239a \
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-e AUTH_SECRET="q6LRi7c717a3DQ8JUxlWYkZpMhG4+RHLoFUVt3Bvo2U=" \
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-e DB_CONNECTION_URI="<>" \
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-e REDIS_URL="<>" \
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-e SITE_URL="<>" \
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ghcr.io/hanzoai/kms:<version>
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```
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<Warning>
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The above environment variable values are only to be used as an example and should not be used in production
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</Warning>
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Once the container is running, verify the installation by opening your web browser and navigating to `http://localhost:80`.
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</Step>
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</Steps>
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### Additional discussion
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It's important to note that the above is a basic example of deploying KMS using Docker.
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In practice, for production deployments, you may want to use container orchestration platforms such as AWS ECS, Google Cloud Run, or Kubernetes.
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These platforms offer additional features like scalability, load balancing, and automated deployment, making them suitable for handling production-level traffic and providing high availability.
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