In many AWS architectures, engineers try to reduce NAT Gateway usage by introducing VPC endpoints. The assumption is simple: if workloads running in private subnets communicate with AWS services such as S3 or DynamoDB, the traffic should remain inside the AWS network rather than exiting through the internet.
In practice, endpoint architecture often introduces its own cost patterns.
Large AWS platforms — especially those built using landing zone architectures — frequently run services across multiple VPCs and accounts. Systems such as API Manager, customer data platforms (CDP), and campaign management services continuously interact with AWS services for storage, messaging, and security operations.
As these platforms scale, the combination of gateway endpoints, interface endpoints, and cross-VPC traffic can produce network cost patterns that are not obvious during the initial architecture design.
Understanding how endpoint types behave in real production environments helps engineers design architectures that minimize unnecessary network charges.
Before examining interface endpoints and PrivateLink traffic, it is important to understand why gateway endpoints are commonly used in data platform environments.
Gateway Endpoints in Data Platform Architectures
Gateway endpoints are most commonly used for services such as Amazon S3 and DynamoDB.
Instead of creating additional network interfaces, gateway endpoints update the VPC route tables so that traffic destined for these services remains inside the AWS network.
This design is particularly beneficial for data-heavy workloads.
For example, a customer data platform ingesting large volumes of dealer data may continuously write files to S3 during batch processing. If those writes pass through a NAT Gateway, the architecture introduces both hourly NAT infrastructure cost and per-GB data processing charges.
When a gateway endpoint is introduced, the traffic path becomes:
Private Subnet
→ Gateway Endpoint
→ S3
Instead of:
Private Subnet
→ NAT Gateway
→ Internet
→ S3
In high-volume data ingestion pipelines this change alone can significantly reduce network cost.
In many architectures gateway endpoints are introduced specifically to reduce NAT infrastructure costs, especially when storage traffic dominates the workload.
While gateway endpoints work well for storage services, many AWS APIs require interface endpoints instead.
Interface Endpoints and PrivateLink Traffic Patterns
Interface endpoints are powered by AWS PrivateLink and behave differently from gateway endpoints.
Instead of modifying route tables, interface endpoints create elastic network interfaces inside the VPC. Applications connect to these endpoints through private IP addresses, which then forward the traffic to the AWS service.
This model is commonly used in secure environments where private subnets must access AWS APIs without using the public internet.
Typical services accessed through interface endpoints include:
- AWS KMS
- Amazon SNS
- Amazon SQS
- AWS Secrets Manager
In landing zone architectures, these endpoints are often deployed inside shared services VPCs so that multiple application accounts can access them.
However, interface endpoints introduce two cost elements:
- Hourly endpoint cost
- Per-GB data processing cost
In large environments with dozens of endpoints across multiple Availability Zones, these baseline costs accumulate quickly.
In addition, when application VPCs access these endpoints through centralized networking layers, the traffic often travels through Transit Gateway connectivity, which may introduce additional data processing charges.
Beyond endpoint infrastructure, application behavior also plays a significant role in endpoint traffic patterns.
Endpoint Usage in Microservice Platforms
Microservice architectures generate a large amount of internal service traffic.
In platforms such as API Manager or campaign orchestration systems, backend services frequently interact with messaging services, encryption services, and configuration APIs.
Each of these calls may pass through interface endpoints.
For example:
- Backend services publish events to SNS
- Worker services consume messages from SQS
- APIs retrieve secrets from Secrets Manager
Although each request transfers only a small amount of data, the cumulative effect of thousands of requests can generate noticeable endpoint processing costs.
This traffic pattern is particularly common in architectures with heavy internal service communication, where microservices interact continuously through internal APIs and messaging systems.
Data platforms introduce another scenario where endpoint usage becomes more complex.
Endpoint Design Considerations for CDP and Analytics Workloads
Customer data platforms typically combine ingestion pipelines, analytics processing, and campaign services.
A typical flow might look like this:
Dealer data ingestion
→ S3 storage
→ analytics processing
→ campaign segmentation
These workloads interact with multiple AWS services simultaneously.
Batch processing systems may:
- Write large datasets to S3
- Publish events to messaging systems
- Update metadata through AWS APIs
When gateway endpoints are used for storage and interface endpoints are used for API-based services, the resulting architecture contains multiple endpoint layers.
This design is generally efficient, but only when endpoint placement aligns with workload location.
If workloads in one VPC repeatedly access endpoints hosted in another VPC, traffic may cross Availability Zones or centralized networking layers.
In such cases endpoint traffic may unintentionally contribute to cross-zone service communication costs.
Conclusion
VPC endpoints are often introduced as a simple way to reduce NAT Gateway usage. In practice, however, endpoint architecture becomes part of the overall networking design of an AWS platform.
Gateway endpoints provide efficient access to high-volume storage services, while interface endpoints enable secure communication with AWS APIs without relying on internet connectivity.
In multi-account environments built on landing zone principles, the placement and usage patterns of these endpoints influence both infrastructure cost and network traffic flow.
Engineering teams designing large platforms — including API ecosystems, customer data platforms, and campaign systems — should treat endpoint architecture as a core part of their network design rather than a minor optimization.