In today's cloud-first world, managing AWS costs has become a critical challenge for growing businesses. Container technologies like Kubernetes promise efficiency, but without proper management, they can lead to unexpected cloud bills. At Convox, we've helped hundreds of companies optimize their infrastructure spending while maintaining performance. Here are five practical ways to reduce your AWS costs through better container management.

1. Right-size Your Node Capacity with Mixed Instance Types

One of the most common sources of wasted spend is over-provisioned infrastructure. Many teams default to using on-demand instances with excessive capacity "just in case."

Convox allows you to configure the node capacity type to be either "on_demand", "spot" or "mixed". The mixed setting creates one node group with on-demand instances and two others with spot instances, giving you both reliability and cost savings.

To implement this strategy:

$ convox rack params set node_capacity_type=mixed -r production
$ convox rack params set min_on_demand_count=2 -r production
$ convox rack params set max_on_demand_count=5 -r production

This configuration ensures you always have 2-5 on-demand instances for critical workloads, while leveraging more cost-effective spot instances for everything else. For typical workloads, this can reduce infrastructure costs by 30-50%.

2. Implement Scheduled Scaling for Predictable Workloads

Many applications have predictable usage patterns. Development and testing environments often sit idle during evenings and weekends, while production workloads might have clear peak hours.

Convox's schedule_rack_scale_down and schedule_rack_scale_up parameters allow you to automatically scale your infrastructure based on cron expressions. For example:

# Scale down development environments at 8 PM on weekdays
$ convox rack params set schedule_rack_scale_down="0 20 * * 1-5" -r development

# Scale back up at 7 AM Monday-Friday
$ convox rack params set schedule_rack_scale_up="0 7 * * 1-5" -r development

For non-production environments, this approach can reduce costs by up to 70% by eliminating unnecessary runtime during off-hours.

3. Optimize Build Processes with Dedicated Build Groups

Continuous integration processes can consume substantial resources, especially for larger applications. Rather than running builds on your production nodes, use Convox's additional_build_groups_config to create dedicated spot-based build infrastructure.

[
  {
    "type": "c5.large",
    "capacity_type": "SPOT",
    "min_size": 0,
    "desired_size": 0,
    "max_size": 3,
    "label": "app-build",
    "disk": 100
  }
]

Then configure your applications to use these dedicated build nodes:

$ convox apps params set BuildLabels=convox.io/label=app-build -a myapp

This configuration ensures that:

• Build processes don't compete with production workloads
• You use cost-effective spot instances for interruptible build jobs
• Build nodes scale to zero when not in use, eliminating idle costs

4. Use EFS Selectively for Persistent Storage

AWS's Elastic File System (EFS) provides convenient persistent storage for containers but can become costly for high-throughput applications. Convox allows you to enable the EFS CSI driver and selectively attach volumes to services that truly need persistence:

services:
  web:
    volumeOptions:
      - awsEfs:
          id: "efs-1"
          accessMode: ReadWriteMany
          mountPath: "/data/"
      - emptyDir:
          id: "temp-vol"
          mountPath: "/tmp/cache/"

This hybrid approach uses:

• EFS for critical data that must persist
• Local ephemeral storage (emptyDir) for temporary caches and processing
• Memory-based volumes for high-performance needs

By being selective about what data requires persistence, you can reduce EFS throughput charges while maintaining data durability where it matters.

5. Leverage Resource Overlays for Environment-Specific Optimization

Database costs often represent a significant portion of cloud spending. Convox's resource overlays allow you to use containerized resources in development environments while connecting to properly sized AWS managed services in production.

Define your database in convox.yml:

resources:
  database:
    type: postgres

For development environments, this runs as a containerized PostgreSQL instance. For production, override with an appropriately sized RDS instance:

$ convox env set DATABASE_URL=postgres://username:password@production-db.us-east-1.rds.amazonaws.com:5432/dbname -r production

This strategy provides:

• Full-featured databases in development without RDS costs
• Appropriately sized RDS instances in production
• Consistent application configuration across environments

Using containerized databases in non-production environments can reduce database costs by 50-80% compared to running separate RDS instances for each environment.

Conclusion

Effective container management isn't just about technology—it's about matching resources to actual needs. Convox provides the tools to optimize your AWS infrastructure for both cost and performance without requiring deep Kubernetes expertise.

By implementing these five strategies, most organizations can reduce their AWS spending by 30-60% while maintaining or even improving application performance and reliability.

Ready to optimize your AWS costs? Get started free today or email us for a personalized assessment of your infrastructure spending.