Kafka Cloud Deployment
Deployment guides for running Apache Kafka on cloud platforms.
Cloud Deployment Overview

| Aspect |
AWS |
Azure |
GCP |
Kubernetes |
| Compute |
EC2 |
Virtual Machines |
Compute Engine |
Pods |
| Storage |
EBS gp3 |
Premium SSD v2 |
PD-SSD |
PVC |
| Networking |
VPC |
VNet |
VPC |
Services |
| Load Balancing |
NLB |
LB |
TCP LB |
Service/Ingress |
| IAM |
IAM Roles |
Managed Identity |
Service Accounts |
RBAC |
Deployment Patterns
Single Region

Multi-Region (Active-Passive)

Cloud-Specific Guides
- 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
Common Considerations
High Availability
| Requirement |
Implementation |
| Zone redundancy |
Spread brokers across 3+ AZs |
| Rack awareness |
Configure broker.rack per zone |
| Replication |
replication.factor=3 |
| ISR |
min.insync.replicas=2 |
Security
| Layer |
Cloud Implementation |
| Network |
Private subnets, security groups |
| Encryption in transit |
TLS certificates |
| Encryption at rest |
Encrypted volumes |
| Authentication |
SASL/SCRAM or mTLS |
| Authorization |
Kafka ACLs |
Monitoring
| Aspect |
Cloud Service |
| Metrics |
CloudWatch / Azure Monitor / Cloud Monitoring |
| Logs |
CloudWatch Logs / Log Analytics / Cloud Logging |
| Alerting |
SNS / Action Groups / Alerting |
Cost Optimization
Compute
- Use reserved instances for steady workloads
- Right-size based on actual utilization
- Consider spot/preemptible for non-critical workloads
Storage
- Use appropriate disk type for workload
- Implement retention policies to limit storage growth
- Consider tiered storage for cold data
Network
- Keep replication traffic within zone when possible
- Use private endpoints to avoid egress costs
- Compress data to reduce transfer volume