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GKE Autopilot Reference Architecture
Google Kubernetes Engine (GKE) Autopilot is a fully-managed Kubernetes service offered by Google Cloud that simplifies the deployment, scaling, and management of containerized applications. It is designed to provide an optimized, secure, and cost-effective platform for running Kubernetes workloads, allowing organizations to focus on application development and management.
For the Public Health Agency of Canada, adopting GKE Autopilot can help streamline the management of containerized applications, improve resource utilization, and enhance security and compliance. This reference architecture provides an overview of GKE Autopilot and outlines best practices for implementing and managing GKE Autopilot clusters in the context of the Public Health Agency of Canada's cloud infrastructure.
GKE Autopilot automates the management of Kubernetes clusters, handling tasks such as provisioning, scaling, and upgrading nodes. It abstracts away the underlying infrastructure, allowing cloud experts at the Public Health Agency of Canada to focus on deploying and managing containerized applications. The high-level architecture of a GKE Autopilot cluster consists of the following components:
The Kubernetes control plane is responsible for managing the overall state of the cluster, including API server, etcd datastore, and other control components. In GKE Autopilot, the control plane is fully managed by Google Cloud.
GKE Autopilot provisions and manages the worker nodes, which run containerized applications. Nodes are grouped into regional or zonal node pools, with each node running a predefined set of components, such as container runtime and kubelet.
GKE Autopilot utilizes VPC-native clusters, which provide native support for Google Cloud networking features, such as Alias IP ranges and Shared VPC.
Persistent storage for containerized applications can be provisioned using Google Cloud Persistent Disks, which can be automatically created and managed through Kubernetes Persistent Volumes and Persistent Volume Claims.
To reduce dependency on shared infrastructure and increase fault tolerance, it's recommended to create multiple GKE Autopilot clusters, each serving a specific purpose or application workload. This approach provides better isolation between workloads and allows for independent scaling and management.
The following components and services play a critical role in a GKE Autopilot implementation:
GKE Autopilot is built on Kubernetes, an open-source container orchestration platform. Kubernetes provides the core functionality for deploying, scaling, and managing containerized applications.
Google Cloud Container Registry is a private container registry that stores and manages container images. It integrates with GKE Autopilot, allowing you to easily deploy container images stored in the registry to your clusters.
GKE Autopilot integrates with Google Cloud Load Balancing, providing a scalable and highly available load balancing solution for containerized applications.
GKE Autopilot integrates with Google Cloud's Stackdriver Monitoring and Logging services, providing visibility into the performance and logs of your Kubernetes clusters and containerized applications.
To ensure a successful implementation of GKE Autopilot for the Public Health Agency of Canada, follow these best practices:
Consider creating a separate cluster for each application to reduce dependency on shared infrastructure, improve fault tolerance, and enable better isolation between workloads. With this approach, the Public Health Agency of Canada can:
- Minimize the risk of issues propagating across environments by isolating development, staging, and production workloads in separate clusters.
- Increase fault tolerance by reducing the blast radius of potential infrastructure failures and ensuring that an issue in one cluster does not affect other applications.
- Improve resource utilization and management by allowing each cluster to scale independently according to the needs of the specific application it serves.
- Enhance security by isolating sensitive workloads and enabling more fine-grained access control within each cluster.
When choosing between a multi-cluster design or a cluster per application, consider factors such as application requirements, resource usage patterns, and management overhead. Additionally, use regional clusters to ensure high availability and fault tolerance. Regional clusters distribute nodes across multiple zones within a region, reducing the risk of zone-level failures impacting your applications.
Use VPC-native clusters and configure appropriate network policies to secure and isolate your workloads. Leverage Google Cloud's networking features, such as Shared VPC and Cloud NAT, to simplify network management and improve security.
Enable features such as Shielded GKE Nodes and Workload Identity to enhance the security of your clusters. Implement Kubernetes RBAC for access control and use Google Cloud's Managed SSL Certificates for secure communication.
Use Kubernetes Persistent Volumes and Persistent Volume Claims to provision and manage storage for your containerized applications.
Integrating GKE Autopilot with other systems and services within the Public Health Agency of Canada's infrastructure is essential for seamless operations and leveraging the full capabilities of Google Cloud. Consider the following integration points:
Integrate GKE Autopilot with Google Cloud's IAM to manage access control and permissions for your clusters. Use IAM roles and policies to define the appropriate level of access for users and service accounts.
Connect GKE Autopilot with other Google Cloud data and analytics services, such as BigQuery, Dataflow, and Pub/Sub, to enable data processing and analysis for your containerized applications. Utilize Kubernetes Custom Resource Definitions (CRDs) and Operators to simplify the management and deployment of these services.
Integrate GKE Autopilot with your CI/CD pipeline to automate the deployment and management of containerized applications. Tools like Cloud Build, GitLab, and Jenkins can be used to build, test, and deploy your applications to GKE Autopilot clusters.
Use Google Cloud's Secret Manager or other secret management solutions to securely store and manage sensitive information, such as credentials and API keys. Integrate these solutions with GKE Autopilot to provide secure access to secrets for your containerized applications.
Integrate GKE Autopilot with your existing monitoring and observability tools, such as Grafana, Prometheus, and Jaeger, to provide a comprehensive view of your application's performance and health. Use Stackdriver Monitoring and Logging as a central platform for aggregating metrics and logs from your GKE Autopilot clusters and other Google Cloud services.
Effective monitoring and management of GKE Autopilot clusters are crucial for ensuring the health and performance of your containerized applications. The following tools and practices can be employed to manage GKE Autopilot:
Utilize Google Cloud's Stackdriver Monitoring and Logging services to gain insights into the performance and health of your clusters and applications. Set up alerts and dashboards to proactively monitor key metrics and identify potential issues.
Use the Kubernetes Dashboard, a web-based UI for Kubernetes, to manage and troubleshoot your GKE Autopilot clusters. The dashboard provides an overview of the cluster's health, as well as detailed information about workloads, services, and resources.
Use the kubectl command-line tool to interact with and manage your GKE Autopilot clusters. kubectl provides a wide range of commands for managing resources, debugging issues, and performing administrative tasks.
Enable GKE Autopilot's Autorepair and Auto-upgrade features to ensure the health and up-to-date status of your nodes. Autorepair automatically repairs unhealthy nodes, while Auto-upgrade keeps your nodes up-to-date with the latest Kubernetes version.
GKE Autopilot offers a fully-managed Kubernetes solution that simplifies the deployment and management of containerized applications for the Public Health Agency of Canada. By following the best practices outlined in this reference architecture, cloud experts can ensure a successful implementation of GKE Autopilot that aligns with the organization's goals and requirements. Adopting GKE Autopilot can help improve resource utilization, enhance security and compliance, and enable seamless integration with other systems and services within the Public Health Agency of Canada's infrastructure.
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Under Development
- This wiki and the documents being developed under it are living documents.
- They are all pre-decisional.
- Some of these documents were generated using chatGPT or were developed by other organizations for reuse and adaptation.
- Some of the documents in this wiki are in early early drafts, they make reference to things that do no exist or to process not yet being used.
- The Center of practice(COP) is best effort and will be developed iteratively. This includes the technology supporting the COP
- At the early stages of the COP expect change; short life cycles and rapid changes. Plan accordingly.
- Stability in the COP will materialize over time.
- For immediate reference engage your COP support channel, use the documentation as a secondary source.
- There is reference to the COP and PDCP in the documentation, these are the same entity. We haven't picked a name yet :)
All of the pages in this wiki should be considered draft, underdevelopment and needing review. None of these pages are official documentation. All of the pages are a work in progress and discussion is encouraged via the GitHub issues mechanism.
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