Overview
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Chat UI
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OVERVIEW
AGENTIC STAR is an AI agent platform delivered as an AWS CloudFormation stack. It automates the deployment and configuration of an integrated environment for building, managing, and running AI agents, including Kubernetes infrastructure, data services, authentication, LLM routing, logging, and monitoring.
AGENTIC STAR is designed for platform engineering, ML, and DevOps teams that want to reduce the manual effort required to integrate and operate multiple AI infrastructure components.
WHY AGENTIC STAR Simplified Infrastructure Integration: Provisions and configures Amazon EKS, databases, vector search, LLM routing, authentication, networking, and observability components through a coordinated deployment. AWS Integration with LLM Flexibility: Routes inference through LiteLLM with AWS Bedrock support. Integration with other model providers available through LiteLLM is subject to configuration and provider compatibility. Integrated Operational Capabilities: Includes components for IAM-based access control, VPC-integrated networking, authentication, monitoring, metrics, and logging. USE CASE EXAMPLE
Example use case: An enterprise knowledge assistant.
A team can deploy AGENTIC STAR and configure an internal support agent that uses company documentation for semantic search and retrieval workflows. Qdrant and PostgreSQL with pgvector provide vector data capabilities, while queries can be routed through AWS Bedrock using LiteLLM.
The Chat UI provides a web interface for employees to interact with the agent. Keycloak supports authentication and team-based access control, while Prometheus, Grafana, Loki, and related monitoring components provide visibility into application and infrastructure health.
KEY FEATURES Automated Deployment: Provisions Amazon EKS, Amazon RDS for PostgreSQL, Amazon S3 storage, VPC networking, and Kubernetes applications through nested AWS CloudFormation templates AI-Ready Data Stack: Includes Qdrant and PostgreSQL with pgvector for vector search, embeddings, and retrieval workflows Chat UI: Provides a web interface for chat, agent configuration, and team management Integrated Observability: Includes Prometheus, Grafana, Loki, Alloy, and Amazon CloudWatch Container Insights Enterprise Security Components: Includes IAM roles, VPC-integrated networking, Keycloak authentication, NGINX Ingress, and cert-manager LLM Routing: Routes inference through LiteLLM with AWS Bedrock support and configurable integration with other compatible model providers Optional Datadog Integration: Provides an optional integration for application performance monitoring and observability WHAT GETS DEPLOYED
AWS Infrastructure:
Amazon EKS cluster with system and user node groups Auto Scaling configuration for EKS node groups Amazon RDS for PostgreSQL with the pgvector extension and Multi-AZ configuration Amazon S3 storage for application data and static content VPC networking with public and private subnets NAT Gateway and Elastic IP IAM roles and policies Bootstrap Amazon EC2 instance for automated Helm installation
Kubernetes Applications and Supporting Components:
Agent Executor AgenticAI Admin AgenticAI ExtAPI Agent Sandbox Controller Chat Chat Auth with Keycloak Keycloak Extensions Qdrant kube-prometheus-stack Prometheus Adapter Loki Alloy Kubernetes Monitoring AgenticAI Observability NGINX Ingress cert-manager ExtAuth Service Gate Services DB Migration Init Platform PVC Lifecycle Manager AgenticAI Datadog Upgrade Controller PRICING
This product uses metered pricing through AWS Marketplace. AWS infrastructure costs, including Amazon EKS, Amazon RDS, Amazon EC2, NAT Gateway, and Amazon S3 usage, are billed separately by AWS based on resource consumption.
PREREQUISITES An AWS account with the IAM permissions required to create the AWS resources used by the product Sufficient Amazon EC2 vCPU service quotas for the Amazon EKS node groups Appropriate service quotas for Amazon EKS, Amazon RDS, Amazon VPC, and Amazon EC2 Access to an LLM endpoint, with AWS Bedrock recommended for use through the LiteLLM gateway EXTERNAL DEPENDENCIES
This product downloads the following external dependencies during deployment:
kubectl from kubernetes.io Helm from helm.sh yq from the mikefarah/yq GitHub repository Helm charts and installer packages from seller-managed object storage Container images from a seller-managed container registry
SoftBank Corp. manages the availability, security, and integrity of artifacts hosted on SoftBank-managed infrastructure. Third-party dependencies are governed by their respective providers.
GETTING STARTED
To learn more about AGENTIC STAR or request a guided deployment walkthrough, contact SoftBank Corp. through the official inquiry form.
Highlights
- Automate the deployment of an integrated AI agent environment through AWS CloudFormation, including Amazon EKS, Amazon RDS for PostgreSQL, storage, networking, authentication, and observability components.
- Support semantic search and retrieval-augmented generation workflows using Qdrant and PostgreSQL with pgvector, with LLM routing through LiteLLM and AWS Bedrock.
- Operate the platform with IAM roles, VPC-integrated networking, Keycloak authentication, NGINX Ingress, cert-manager, Prometheus, Grafana, Loki, and Amazon CloudWatch Container Insights.
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Delivery details
AGENTIC STAR AMI with CloudFormation (EKS Full Stack)
This delivery option uses nested AWS CloudFormation templates to provision the full AGENTIC STAR platform. The entry-point template (main-template.yaml) orchestrates all nested stacks: VPC with NAT Gateway, Amazon EKS cluster with managed node groups, RDS PostgreSQL 16.6 with Multi-AZ HA, S3 buckets, and an ephemeral Setup Helper EC2 instance that installs 23 Kubernetes microservices via Helm.
A placeholder Marketplace EC2 instance (t3.medium) is provisioned in the public subnet to satisfy AWS Marketplace AMI-based product requirements. This instance does not run any application workload.
External dependencies downloaded at deployment time include Helm binaries and charts from seller-managed object storage, and container images from a seller-managed container registry.
CloudFormation Template (CFT)
AWS CloudFormation templates are JSON or YAML-formatted text files that simplify provisioning and management on AWS. The templates describe the service or application architecture you want to deploy, and AWS CloudFormation uses those templates to provision and configure the required services (such as Amazon EC2 instances or Amazon RDS DB instances). The deployed application and associated resources are called a "stack."
Version release notes
Version 2.6.0 release of AGENTIC STAR on AWS Marketplace.
This release upgrades the bundled Helm installer to version 2.6.0, delivering new platform features through the microservices layer. The AWS CloudFormation templates were updated to upgrade the managed RDS PostgreSQL engine from 16.6 to 16.10; the EKS cluster topology and networking configuration remain consistent with v2.5.0.
Key changes in this release:
- Audit & compliance: added a full-export capability for audit logs
- Abuse prevention: added bot protection at signup using Cloudflare Turnstile
- Security hardening: strengthened verification across authentication / authorization paths and improved protection of confidential information in log output across multiple services
- Accessibility & i18n: comprehensively strengthened accessibility and multilingual support across the Admin / Chat UIs
- Data export: prevented garbled characters in CSV export (UTF-8 BOM) and stabilized sort order
- Platform reliability: optimized container resource settings across services; made database migrations idempotent to avoid registration conflicts on re-run; fixed an ownership-loss issue during Warmpool Sandbox deletion; fixed a false positive in ConfigMap drift detection
All existing components from v2.5.0 (EKS with System/User node groups, RDS PostgreSQL 16.10 with pgvector and Multi-AZ HA, Qdrant, Chat UI with Keycloak, Prometheus/Grafana/Loki/Alloy observability, NGINX Ingress, cert-manager, AWS Bedrock integration, optional Datadog APM) remain included.
Additional details
Usage instructions
LAUNCH INSTRUCTIONS
- Subscribe to AGENTIC STAR on AWS Marketplace and click "Continue to Configuration".
- Select "CloudFormation" as the delivery method, choose your AWS Region, and click "Continue to Launch".
- Click "Launch CloudFormation" the AWS CloudFormation console opens with main-template.yaml pre-loaded.
- Fill in the required parameters: Stack name: choose a unique name (e.g., agentic-star-prod) ImageId: pre-filled by AWS Marketplace - do not change EKS node instance types and scaling limits (default: m5.2xlarge, min 2 nodes each group) RDS instance class and credentials (default identifier: marketplace-db) Admin email and password for the platform Primary language (default: ja)
- Acknowledge that CloudFormation will create IAM resources.
- Click "Create stack". Deployment takes approximately 20~30 minutes.
POST-DEPLOYMENT SETUP
After the stack reaches CREATE_COMPLETE:
- Retrieve the EKS cluster name from the CloudFormation Outputs tab.
- Run the kubectl config command shown in Outputs to authenticate with the cluster.
- Verify all 23 microservices are running: kubectl get pods -A
- Access the Chat UI at the URL shown in Outputs.
- Configure your LLM provider through the LiteLLM multiLLM gateway (e.g., AWS Bedrock region) via the platform admin panel.
- Configure Keycloak with your identity provider if required.
For full documentation, refer to the product User Guide.
Resources
Vendor resources
Support
Vendor support
SoftBank Corp. provides support for AGENTIC STAR on AWS through the official inquiry form.
Support Scope:
Assistance with AWS Marketplace deployment and AWS CloudFormation launch issues Guidance for initial configuration and post-deployment setup Documentation for platform administration and operation Support for product updates and security-related notices Troubleshooting for Kubernetes application health and connectivity Guidance on AWS service quotas relevant to Amazon EKS and Amazon RDS resources
How to Get Help:
For deployment issues, initial configuration questions, operational questions, and other product support inquiries, contact SoftBank Corp. using the official inquiry form.
Sizing Guidance:
AGENTIC STAR requires sufficient vCPU service quotas for the Amazon EKS node groups. Ensure that the AWS account has appropriate service quotas for Amazon EKS, Amazon RDS, Amazon VPC, and Amazon EC2 before deployment. Contact support for assistance with capacity planning and service quota requirements. For support inquiries, please contact SoftBank Corp. using the following form: https://www.softbank.jp/biz/contact-us/demand/ai/agentic-star-inquiry/
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