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AxonOps — AI-Native Control Plane for Open Source Data Platforms

Kafka Cloud Deployment

Deployment guides for running Apache Kafka on cloud platforms.


Cloud PlatformsIaaSContainerAWS EC2Azure VMsGCP ComputeKubernetesEKS/AKS/GKEFull controlSelf-managedPortableOrchestrated

AspectAWSAzureGCPKubernetes
ComputeEC2Virtual MachinesCompute EnginePods
StorageEBS gp3Premium SSD v2PD-SSDPVC
NetworkingVPCVNetVPCServices
Load BalancingNLBLBTCP LBService/Ingress
IAMIAM RolesManaged IdentityService AccountsRBAC

RegionAZ 1AZ 2AZ 3Broker 1Broker 2Broker 3replicationreplicationreplication
Primary RegionDR RegionClusterMirrorMaker 2ClusterHandles all trafficStandby for failoverconsumereplicate

Choosing between single-region and multi-region deployments is a critical architectural decision. See Single Region vs Multi-Region for:

  • Cloud region failure statistics and historical incidents
  • RTO/RPO analysis for different architectures
  • Industry-specific recommendations (finance, healthcare, e-commerce)
  • Cost analysis and decision framework
  • Implementation checklists

  • EC2 instance selection
  • EBS volume configuration
  • VPC and security groups
  • Terraform examples
  • VM sizing
  • Managed disk configuration
  • VNet and NSG
  • Terraform examples
  • Compute Engine sizing
  • Persistent disk configuration
  • VPC and firewall rules
  • Terraform examples
  • StatefulSet configuration
  • Persistent volume claims
  • Network policies
  • Helm charts

RequirementImplementation
Zone redundancySpread brokers across 3+ AZs
Rack awarenessConfigure broker.rack per zone
Replicationreplication.factor=3
ISRmin.insync.replicas=2
LayerCloud Implementation
NetworkPrivate subnets, security groups
Encryption in transitTLS certificates
Encryption at restEncrypted volumes
AuthenticationSASL/SCRAM or mTLS
AuthorizationKafka ACLs
AspectCloud Service
MetricsCloudWatch / Azure Monitor / Cloud Monitoring
LogsCloudWatch Logs / Log Analytics / Cloud Logging
AlertingSNS / Action Groups / Alerting

  • Use reserved instances for steady workloads
  • Right-size based on actual utilization
  • Consider spot/preemptible for non-critical workloads
  • Use appropriate disk type for workload
  • Implement retention policies to limit storage growth
  • Consider tiered storage for cold data
  • Keep replication traffic within zone when possible
  • Use private endpoints to avoid egress costs
  • Compress data to reduce transfer volume