Public Helm Chart

A Helm chart is a package that contains all the resources required to deploy an application to a Kubernetes cluster. Helm is a package manager for Kubernetes. Popular open-source Helm chart repositories are Artifact Hub, Bitnami Charts, etc. With Kapstan, you can easily deploy a helm chart.

Create a Public Helm Chart

1. Click on "+" in the top-right corner, and then select "Public helm chart".
2. Configuring the application:

• Name: Provide a name for your application. E.g., nginx-server.
• Public repository URL: The URL of the repository where the helm chart is hosted. E.g. https://charts.bitnami.com/bitnami, oci://registry-1.docker.io/bitnamicharts, etc.
• Chart Name: The name of the helm chart you want to deploy. E.g., nginx.
• Chart Version: The version of the helm chart you want to deploy.
• Chart Values: Provide an override YAML configuration for the helm chart. For example:

replicaCount: 2
image:
  repository: nginx
  tag: 1.19.10
  pullPolicy: IfNotPresent
service:
  type: LoadBalancer
  port: 80
  targetPort: 80

3. Click on "Confirm" to create the application. You will then be redirected to the application overview page where you can deploy the application.

Configuration

• Go to the "Config" tab and click on "Edit".
• Update the values as required and click on "Save".

Deploy

Go to deployment and event history to learn more about deploying the application and viewing the event history.

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Support for Public Helm Charts

Here are some example categories of public Helm charts that Kapstan supports to help you get started quickly. This is not a comprehensive list, Kapstan can support any public Helm chart.

Databases and Storage

Deploy robust databases and storage solutions with minimal configuration:

• MongoDB: NoSQL database known for scalability and flexibility.
• PostgreSQL: Relational database with advanced SQL capabilities.
• Redis: In-memory data store for caching and real-time analytics.
• Elasticsearch: Distributed search engine for structured and unstructured data. (Elastic)

Big Data, Machine Learning and Workflow Engines

Leverage big data processing and ML frameworks for advanced analytics:

• Apache Airflow: Workflow orchestration tool for scheduling and monitoring data pipelines. (Apache)
• Apache Spark: Cluster-computing system for big data processing.
• JupyterHub: Multi-user Jupyter notebook platform for collaborative data science.
• Argo Workflows: Kubernetes-native workflow orchestration tool for ML pipelines.

Application Servers and Frameworks

Streamline the deployment of application frameworks and services:

• Nginx: High-performance HTTP server and reverse proxy.
• Cert Manager: Automate the management and issuance of TLS certificates.
• Apache Kafka: Distributed event streaming platform for high-throughput messaging.
• Keycloak: Identity and access management solution for modern applications.

Training Orchestration

• Polyaxon: Orchestration and distributed training platform for ML workloads.

Vector Databases

• qdrant: Vector Database for the next generation of AI applications.
• Weaviate: Vector database optimized for semantic search in AI applications.

Monitoring and Observability

Monitor and troubleshoot your applications effortlessly:

• Prometheus: Metrics-based monitoring system and alerting toolkit. (Prometheus Community)
• Grafana: Visualization and analytics platform for monitoring dashboards. (Grafana Labs)
• Loki: Log aggregation system optimized for efficiency.

DevOps Tools

Automate and manage Kubernetes workloads with Helm charts for CI/CD and other tools:

• Jenkins: Automation server for building, deploying, and automating projects. (Jenkins CI)
• ArgoCD: Continuous delivery tool for deploying and managing applications.
• HashiCorp Vault: Securely store and manage sensitive data.

Kapstan simplifies the deployment of these charts, enabling teams to focus on development and innovation without worrying about manual setup or configurations.