Which cloud provider should I choose?

AWS for broadest service selection, GCP for data and ML workloads, Azure for Microsoft ecosystem integration. Most applications work well on any of the three.

How do I control cloud costs?

Right-size instances, use reserved capacity for predictable workloads, enable auto-scaling, and set up cost alerts. Review spending weekly during the first month.

Should I use containers or serverless?

Containers (ECS/EKS) for long-running services with predictable traffic. Serverless (Lambda) for event-driven, bursty workloads. Many apps use both.

Cloud Deployment Checklist

Deploy to production on AWS, GCP, or Azure with confidence using this comprehensive infrastructure, security, and monitoring checklist.

Checklist: Cloud Deployment (engineering)

Deploying to the cloud requires configuring infrastructure, security, monitoring, and cost controls correctly from the start. Mistakes in production infrastructure are expensive to fix later. This checklist covers the essential steps for a production-ready cloud deployment.

Checklist Items

Configure IAM roles with least-privilege access [critical]: Create service-specific IAM roles with minimal required permissions. Never use root or admin credentials.
Enable encryption at rest and in transit [critical]: Encrypt all data stores, enable TLS for all network communication, and manage keys with KMS.
Set up auto-scaling policies [critical]: Configure horizontal auto-scaling based on CPU, memory, or custom metrics to handle traffic spikes.
Configure health checks and load balancing [important]: Set up application health endpoints and configure load balancers to route traffic away from unhealthy instances.
Set up monitoring and alerting [important]: Configure CloudWatch, Datadog, or equivalent for infrastructure and application metrics with alert thresholds.
Enable automated backups [important]: Configure daily automated backups for databases and persistent storage with tested restore procedures.
Set up VPC and network segmentation [important]: Isolate workloads in private subnets, configure security groups, and restrict inbound traffic.
Configure cost alerts and budgets [recommended]: Set up billing alerts and budget thresholds to prevent unexpected cloud spending.
Implement infrastructure as code [recommended]: Define all infrastructure using Terraform, CloudFormation, or Pulumi for reproducible, version-controlled environments.
Set up log aggregation [recommended]: Centralize application and infrastructure logs in CloudWatch, ELK, or Datadog for debugging and audit.

Common Mistakes

Overly permissive security groups: Start with deny-all and add specific rules. Never open 0.0.0.0/0 on SSH or database ports.
No cost monitoring: Set billing alerts on day one. Misconfigured resources can generate thousands in unexpected charges overnight.
Manual infrastructure changes: Use infrastructure as code for all resources. Manual console changes create drift and are not reproducible.

Frequently Asked Questions

Which cloud provider should I choose?: AWS for broadest service selection, GCP for data and ML workloads, Azure for Microsoft ecosystem integration. Most applications work well on any of the three.
How do I control cloud costs?: Right-size instances, use reserved capacity for predictable workloads, enable auto-scaling, and set up cost alerts. Review spending weekly during the first month.
Should I use containers or serverless?: Containers (ECS/EKS) for long-running services with predictable traffic. Serverless (Lambda) for event-driven, bursty workloads. Many apps use both.