Architecture
Comprehensive guide to Highflame's deployment architecture for enterprises
Highflame Platform Features:
Runtime guardrails for robust agent operations.
Typed Cedar policy enforcement ensures secure interactions.
Agent identity management for secure authentication.
MCP gateway security for protecting communication channels.
Model supply chain scanning for integrity verification.
Adversarial red teaming to test system defenses.
Unified detection and observability layer for comprehensive monitoring.
Deployment Architecture
Overview
Highflame leverages Kubernetes for container orchestration, using Helm charts to streamline application deployments. This approach ensures consistent and repeatable deployments across different cloud infrastructures, enabling high availability and easy scaling.
Key Components
Kubernetes Cluster: Acts as the foundational layer, providing the orchestration platform for containerized applications.
Helm Charts: Simplifies deployments with pre-configured templates, ensuring version control and facilitating rollback capabilities.
Cloud Provider Support: Compatible with AWS, GCP, and Azure, allowing for flexible hosting and integration with native services.
Infrastructure Components
Highflame modules
Highflame components for serving
Deployed as Kubernetes pods with high availability configurations, such as Pod Disruption Budgets (PDB) and Horizontal Pod Autoscalers (HPA).
Transactional database
Store the application data
Managed postgres from the cloud providers
Analytical database
Optimize storage for rapid analysis of large datasets.
Clickhouse in kubernetes
Cache system
Optimize application performance by caching data to expedite internal communication.
Redis cluster solution from the cloud providers
Authentication
For Application authentication and authorization
Clerk (Highflame team will setup this at the time of onboarding)
Blob store
Backup store for clickhouse database server from the kubernetes
Cloud native blob stores such as AWS S3, Azure blobe store, Google GCS
Ingress
Application load balancing for accessing the service by the end users
Application load balancer or other load balancer can integrate with kubernetes
Logging system
For storing the logs of the application
Cloud native logging integration with K8s
Infrastructure Requirements
Kubernetes Cluster: K8s 1.32+ with minimum 6 worker nodes and Helm 3.x
Postgres Server v17.2
Redis cluster v7.1
Outbound connectivity to
ghcr.io for pulling the application images
Clerk endpoints for authentication and authorization
Recommended Resource Requirements:
CPU: 8-16 cores, Memory: 16-32GB per k8s worker nodes
Memory: 4 GB per Redis node
CPU: 4 vCPU, Memory 8 GB Postgres
Data Security & Encryption
All data remains within your network
All data in Highflame is encrypted at rest (If your cloud resources are configured to encrypt, such as the Database server, K8s worker nodes, Redis server, etc)
Communication between the Highflame services over the ingress uses TLS encryption in transit
Highflame service-to-service communication is happening within the K8s cluster and not leaving the K8s
Sensitive data, such as an AI model's API keys, is stored in K8s secrets
Highflame Infra Setup
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