Source code for Google Cloud Marketplace Click to Deploy solutions, enabling one-click deployment of popular applications.
Click to Deploy is a collection of source code for the deployment solutions featured on the Google Cloud Marketplace. It provides the infrastructure-as-code templates that enable users to deploy popular open-source applications like Elasticsearch, Kafka, and Magento onto Google Cloud Platform with minimal configuration. The project solves the problem of manually setting up complex software stacks by offering pre-configured, one-click deployments.
Cloud engineers, DevOps professionals, and developers who want to quickly deploy and manage popular applications on Google Cloud Platform without deep infrastructure expertise.
Developers choose this for its seamless integration with Google Cloud services, reliable pre-configured templates, and active maintenance for security vulnerabilities, reducing deployment time and complexity.
Source for Google Click to Deploy solutions listed on Google Cloud Marketplace.
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Provides deployment scripts for popular apps like Elasticsearch and Kafka, reducing setup time from hours to minutes by leveraging tested templates.
Supports both Virtual Machines and Google Kubernetes Engine, allowing users to choose the infrastructure that best fits their application needs.
Maintained to address vulnerabilities, as evidenced by ongoing efforts to patch log4j issues, ensuring deployments stay secure over time.
Integrates with Google Cloud Build for CI/CD and other GCP services, simplifying automation and management within the Google ecosystem.
Some solutions, like Elasticsearch and Magento, are still listed as vulnerable to log4j CVEs, indicating delays in critical security patches.
Marked as not an officially supported Google product, which may lead to slower bug fixes and less reliable long-term maintenance.
Tightly coupled with Google Cloud Platform, making it difficult to migrate deployments to other clouds or on-premises environments.
Designed for standard deployments; modifying templates for unique requirements can be challenging and may require deep infrastructure knowledge.