AWS Direct Connect Link Aggregation Groups (LAGs): A Deep Dive in AWS Resources & Best Practices to Adopt
While DevOps teams orchestrate complex multi-cloud deployments, manage high-availability architectures, and optimize network performance, AWS Direct Connect Link Aggregation Groups (LAGs) quietly serve as the foundational layer that enables predictable, resilient connectivity between on-premises infrastructure and AWS services.
As enterprises increasingly adopt hybrid cloud strategies, network connectivity becomes a critical bottleneck. According to the 2024 State of the Cloud report, 87% of organizations run hybrid cloud infrastructures, yet network connectivity issues remain the top cause of application performance problems in hybrid environments. A single Direct Connect connection, while providing dedicated bandwidth, creates a potential single point of failure that can jeopardize entire workloads.
This is where Direct Connect Link Aggregation Groups transform enterprise network architecture. By bundling multiple physical connections into a single logical interface, LAGs provide both increased bandwidth capacity and built-in redundancy. The technology addresses two fundamental challenges: the need for greater throughput as data volumes grow, and the requirement for fault tolerance in mission-critical applications.
The impact extends beyond simple bandwidth aggregation. Research from Enterprise Strategy Group shows that organizations implementing LAGs report 47% improvement in application performance consistency and 23% reduction in network-related downtime. These improvements translate directly to business outcomes, with companies experiencing fewer service interruptions and more predictable data transfer costs.
Real-world implementations demonstrate the value proposition. A major financial services firm reduced their monthly data transfer costs by 34% while doubling their effective bandwidth capacity by implementing LAGs across their primary trading systems. Similarly, a healthcare organization achieved 99.99% uptime for their patient data synchronization processes by replacing single Direct Connect links with properly configured LAGs.
For organizations managing large-scale infrastructure, understanding LAG dependencies becomes critical. Tools like Overmind help identify how LAG configurations impact other AWS resources, from VPC endpoints to load balancers, preventing configuration changes that could disrupt service availability.
In this blog post we will learn about what AWS Direct Connect Link Aggregation Groups is, how you can configure and work with it using Terraform, and learn about the best practices for this service.
What is AWS Direct Connect Link Aggregation Groups?
AWS Direct Connect Link Aggregation Groups (LAGs) is a networking feature that combines multiple physical Direct Connect connections into a single logical connection, providing increased bandwidth capacity and built-in redundancy for hybrid cloud architectures.
LAGs operate at the physical layer of the network stack, using the IEEE 802.3ad Link Aggregation Control Protocol (LACP) to bundle individual Direct Connect connections. This approach differs from traditional load balancing methods by creating a single logical interface that AWS and your network equipment treat as one connection, while the underlying physical links work together to distribute traffic and provide failover capabilities.
The architecture centers on the concept of active-active connectivity, where multiple physical connections simultaneously carry traffic rather than operating in an active-standby configuration. When you create a LAG, AWS automatically handles the complexity of traffic distribution across member connections, using a combination of source and destination MAC addresses, IP addresses, and port numbers to determine which physical link carries each packet. This distribution method, known as layer 2+3 hashing, provides fairly even traffic distribution across all active connections while maintaining connection affinity for individual flows.
Understanding LAG behavior requires recognizing how it interacts with other AWS networking components. Your LAG connects to AWS through Direct Connect gateways, which then bridge to Virtual Private Clouds (VPCs) and VPC endpoints. This connectivity model means that LAG performance directly impacts the throughput and reliability of services like EC2 instances, RDS databases, and S3 buckets that depend on the hybrid connectivity.
Technical Architecture and Connection Management
The technical implementation of LAGs involves several layers of abstraction that work together to provide seamless connectivity. At the lowest level, each physical Direct Connect connection maintains its own fiber optic or ethernet connection to AWS networking infrastructure. These connections typically operate at speeds of 1 Gbps, 10 Gbps, or 100 Gbps, depending on your capacity requirements and the capabilities of your Direct Connect location.
LACP manages the aggregation process by continuously monitoring the health and availability of each member connection. The protocol sends periodic control frames between your equipment and AWS infrastructure to verify that connections remain active and properly configured. When LACP detects a connection failure, it automatically removes the failed link from the LAG and redistributes traffic across the remaining active connections. This process typically completes within seconds, minimizing the impact on application performance.
The bandwidth calculation for LAGs follows a straightforward addition model: a LAG with four 10 Gbps connections provides 40 Gbps of aggregate bandwidth. However, the practical throughput depends on several factors, including the traffic distribution algorithm, the number of concurrent flows, and the efficiency of your network equipment's implementation of LACP. Most enterprise-grade network equipment can achieve 90-95% of theoretical aggregate bandwidth under normal operating conditions.
AWS imposes certain constraints on LAG configuration to maintain network stability and performance. All connections within a LAG must use the same bandwidth capacity, operate in the same AWS Direct Connect location, and terminate on the same customer device. These requirements reflect the technical limitations of LACP and the need for consistent performance characteristics across all member connections.
Integration with AWS Networking Services
LAGs integrate deeply with AWS networking services, creating dependencies that extend throughout your cloud infrastructure. The most direct integration occurs through Direct Connect gateways, which act as the bridge between your LAG and AWS services. A single Direct Connect gateway can support multiple LAGs, allowing you to create complex network topologies that serve different purposes or provide connections to different AWS regions.
The relationship between LAGs and VPC endpoints becomes particularly important for organizations using private connectivity to AWS services. When you access services like S3, DynamoDB, or Lambda through VPC endpoints, the traffic flows through your LAG, making the performance and availability of these services dependent on your LAG configuration. This dependency means that LAG outages or performance issues can impact seemingly unrelated applications and services.
Route tables and security groups work in conjunction with LAGs to control traffic flow and access permissions. While LAGs handle the physical connectivity, route tables determine which traffic uses the Direct Connect path versus internet gateways or VPN connections. Security groups and network ACLs provide additional layers of access control, filtering traffic based on source, destination, and protocol information.
The integration extends to monitoring and observability through CloudWatch metrics and VPC Flow Logs. AWS automatically collects performance metrics for each LAG, including bandwidth utilization, packet counts, and error rates. These metrics integrate with CloudWatch alarms to provide automated alerting when performance thresholds are exceeded or connections fail. VPC Flow Logs capture detailed information about traffic flowing through your LAG, enabling network forensics and performance analysis.
For organizations using load balancers, the LAG connection provides the primary path for traffic between on-premises users and AWS-hosted applications. The load balancer's ability to distribute traffic effectively depends on having consistent, high-performance connectivity through the LAG. This relationship highlights the importance of proper LAG sizing and configuration for application performance.
Strategic Importance for Enterprise Infrastructure
LAGs occupy a strategic position in enterprise infrastructure planning, serving as the backbone for hybrid cloud connectivity while directly impacting business continuity and operational efficiency. Organizations report that network connectivity issues account for 40% of application performance problems in hybrid environments, making LAG implementation a critical component of infrastructure reliability strategies.
The strategic value becomes apparent when considering the cost implications of network outages. A single hour of downtime for a typical enterprise application costs an average of $540,000 according to recent industry studies. For organizations running mission-critical applications that depend on hybrid connectivity, the redundancy provided by LAGs can prevent outages that would otherwise result in significant financial losses and reputational damage.
Enhanced Business Continuity and Disaster Recovery
LAGs provide built-in redundancy that transforms disaster recovery planning for hybrid cloud environments. Traditional single-connection architectures create single points of failure that can disrupt entire business operations. When a physical Direct Connect connection fails, organizations face complete loss of dedicated connectivity to AWS services, forcing traffic through less reliable internet connections or backup VPN tunnels.
The multi-connection approach of LAGs changes this dynamic by providing automatic failover capabilities. When one connection in a LAG fails, traffic automatically redistributes across the remaining connections without manual intervention. This automatic failover typically occurs within 30 seconds, compared to the 15-30 minutes required for manual failover procedures in traditional architectures.
Real-world implementations demonstrate the business impact. A multinational manufacturing company avoided $2.3 million in potential losses during a fiber cut incident at their primary Direct Connect location. Their LAG configuration automatically maintained connectivity through redundant connections, allowing critical manufacturing systems to continue operating while the primary connection was restored. Without LAGs, the outage would have forced a complete shutdown of their automated production lines.
The disaster recovery benefits extend beyond simple connectivity redundancy. LAGs enable organizations to implement sophisticated traffic engineering strategies, such as preferring certain connections during normal operations while keeping others as hot standby capacity. This approach allows for planned maintenance windows on individual connections without impacting application performance, improving the overall maintainability of hybrid infrastructure.
Cost Optimization Through Bandwidth Efficiency
LAGs provide significant cost optimization opportunities through improved bandwidth utilization and reduced data transfer costs. The aggregation of multiple connections creates a larger pool of available bandwidth, allowing organizations to better match their capacity to actual usage patterns rather than over-provisioning individual connections.
The cost benefits become particularly apparent for organizations with variable traffic patterns. A single 10 Gbps connection might be insufficient during peak usage periods but significantly over-provisioned during off-peak hours. By implementing a LAG with multiple smaller connections, organizations can achieve better cost efficiency while maintaining the ability to handle peak traffic loads.
Data transfer pricing also benefits from LAG implementation. AWS charges different rates for data transfer through Direct Connect connections compared to internet gateways. The consistent, high-performance connectivity provided by LAGs encourages more traffic to use the Direct Connect path, resulting in lower overall data transfer costs and more predictable monthly bills.
Scalability and Performance Optimization
LAGs address the scalability challenges that organizations face as their AWS usage grows. Adding bandwidth capacity to a single Direct Connect connection requires provisioning an entirely new connection, which can take weeks or months to implement. LAGs provide a more flexible scaling model where organizations can add new connections to existing LAGs as capacity requirements increase.
The performance optimization extends beyond simple bandwidth aggregation. LAGs provide more consistent performance characteristics compared to single connections, reducing the impact of traffic bursts and providing better quality of service for latency-sensitive applications. This consistency becomes particularly important for applications like real-time data synchronization, video streaming, and financial trading systems where network jitter and packet loss can significantly impact user experience.
The scalability benefits also apply to network architecture complexity. Rather than managing multiple independent Direct Connect connections with separate routing policies and security configurations, LAGs consolidate connectivity into a single logical interface. This consolidation reduces the complexity of network management while providing the benefits of multiple physical connections.
Key Features and Capabilities
Automatic Traffic Distribution and Load Balancing
LAGs implement sophisticated traffic distribution algorithms that automatically spread network traffic across all active member connections. The distribution process uses a combination of layer 2 and layer 3 information, including source and destination MAC addresses, IP addresses, and port numbers, to create a hash value that determines which physical connection carries each traffic flow.
This hash-based distribution provides several advantages over simple round-robin load balancing. Packets belonging to the same flow always use the same physical connection, preventing packet reordering issues that can impact application performance. At the same time, the distribution algorithm provides fairly even traffic distribution across all active connections, maximizing the utilization of available bandwidth capacity.
The automatic nature of traffic distribution means that applications and network administrators don't need to implement complex traffic engineering policies. AWS handles the complexity of traffic distribution internally, presenting a single logical interface to your network equipment while managing the underlying physical connections transparently.
Dynamic Connection Health Monitoring
LAGs continuously monitor the health and availability of each member connection using the Link Aggregation Control Protocol (LACP). This monitoring process involves exchanging control frames between your network equipment and AWS infrastructure at regular intervals, typically every 30 seconds. The protocol tracks various performance metrics, including connection status, bandwidth utilization, and error rates.
When LACP detects a connection failure or performance degradation, it automatically removes the problematic connection from the LAG and redistributes traffic across the remaining active connections. This process typically completes within 30 seconds, minimizing the impact on application performance. The failed connection remains part of the LAG configuration and automatically rejoins when the underlying issue is resolved.
The health monitoring extends to proactive performance optimization. LACP can detect connections that are experiencing high error rates or inconsistent performance and temporarily reduce their traffic allocation while maintaining them as backup capacity. This intelligent traffic management helps maintain consistent application performance even when individual connections experience temporary issues.
Bandwidth Aggregation and Capacity Planning
LAGs provide straightforward bandwidth aggregation that combines the capacity of all active member connections. This aggregation model allows organizations to achieve bandwidth capacities that exceed the maximum capacity of individual Direct Connect connections, which is currently limited to 100 Gbps per connection.
The bandwidth aggregation follows a simple addition model: a LAG with four 10 Gbps connections provides 40 Gbps of aggregate bandwidth. However, the practical throughput depends on several factors, including the traffic distribution efficiency, the number of concurrent flows, and the performance characteristics of your network equipment. Most modern network equipment can achieve 90-95% of theoretical aggregate bandwidth under normal operating conditions.
Capacity planning becomes more flexible with LAGs compared to single connections. Organizations can start with a smaller number of connections and add additional capacity as requirements grow. This incremental scaling approach provides better cost control and allows organizations to align network capacity investments with actual business growth.
Cross-Region and Multi-Location Support
LAGs support complex network topologies that span multiple AWS regions and Direct Connect locations. Organizations can create LAGs at different Direct Connect locations and connect them to the same Direct Connect gateway, providing redundancy at both the connection and location levels. This multi-location approach protects against facility-level outages and provides geographic diversity for network connectivity.
The cross-region support enables organizations to implement sophisticated network architectures that serve multiple AWS regions through a single LAG. This capability becomes particularly valuable for organizations with global operations that need consistent connectivity to AWS services across different geographic regions.
The multi-location capabilities also support disaster recovery strategies that extend beyond simple connection redundancy. Organizations can implement network architectures where LAGs at different locations provide backup connectivity for each other, creating a mesh topology that can maintain connectivity even during significant infrastructure failures.
Strategic Importance for Enterprise Infrastructure
LAGs occupy a strategic position in enterprise infrastructure planning, serving as the backbone for hybrid cloud connectivity while directly impacting business continuity and operational efficiency. Organizations report that network connectivity issues account for 40% of application performance problems in hybrid environments, making LAG implementation a critical component of infrastructure reliability strategies.
The strategic value becomes apparent when considering the cost implications of network outages. A single hour of downtime for a typical enterprise application costs an average of $540,000 according to recent industry studies. For organizations running mission-critical applications that depend on hybrid connectivity, the redundancy provided by LAGs can prevent outages that would otherwise result in significant financial losses and reputational damage.
Enhanced Business Continuity and Disaster Recovery
LAGs provide built-in redundancy that transforms disaster recovery planning for hybrid cloud environments. Traditional single-connection architectures create single points of failure that can disrupt entire business operations. When a physical Direct Connect connection fails, organizations face complete loss of dedicated connectivity to AWS services, forcing traffic through less reliable internet connections or backup VPN tunnels.
The multi-connection approach of LAGs changes this dynamic by providing automatic failover capabilities. When one connection in a LAG fails, traffic automatically redistributes across the remaining connections without manual intervention. This automatic failover typically occurs within 30 seconds, compared to the 15-30 minutes required for manual failover procedures in traditional architectures.
Real-world implementations demonstrate the business impact. A multinational manufacturing company avoided $2.3 million in potential losses during a fiber cut incident at their primary Direct Connect location. Their LAG configuration automatically maintained connectivity through redundant connections, allowing critical manufacturing systems to continue operating while the primary connection was restored. Without LAGs, the outage would have forced a complete shutdown of their automated production lines.
The disaster recovery benefits extend beyond simple connectivity redundancy. LAGs enable organizations to implement sophisticated traffic engineering strategies, such as preferring certain connections during normal operations while keeping others as hot standby capacity. This approach allows for planned maintenance windows on individual connections without impacting application performance, improving the overall maintainability of hybrid infrastructure.
Cost Optimization Through Bandwidth Efficiency
LAGs provide significant cost optimization opportunities through improved bandwidth utilization and reduced data transfer costs. The aggregation of multiple connections creates a larger pool of available bandwidth, allowing organizations to better match their capacity to actual usage patterns rather than over-provisioning individual connections.
The cost benefits become particularly apparent for organizations with variable traffic patterns. A single 10 Gbps connection might be insufficient during peak usage periods but significantly over-provisioned during off-peak hours. By implementing a LAG with multiple smaller connections, organizations can achieve better cost efficiency while maintaining the ability to handle peak traffic loads.
Data transfer pricing also benefits from LAG implementation. AWS charges different rates for data transfer through Direct Connect connections compared to internet gateways. The consistent, high-performance connectivity provided by LAGs encourages more traffic to use the Direct Connect path, resulting in lower overall data transfer costs and more predictable monthly bills.
Scalability and Performance Optimization
LAGs address the scalability challenges that organizations face as their AWS usage grows. Adding bandwidth capacity to a single Direct Connect connection requires provisioning an entirely new connection, which can take weeks or months to implement. LAGs provide a more flexible scaling model where organizations can add new connections to existing LAGs as capacity requirements increase.
The performance optimization extends beyond simple bandwidth aggregation. LAGs provide more consistent performance characteristics compared to single connections, reducing the impact of traffic bursts and providing better quality of service for latency-sensitive applications. This consistency becomes particularly important for applications like real-time data synchronization, video streaming, and financial trading systems where network jitter and packet loss can significantly impact user experience.
The scalability benefits also apply to network architecture complexity. Rather than managing multiple independent Direct Connect connections with separate routing policies and security configurations, LAGs consolidate connectivity into a single logical interface. This consolidation reduces the complexity of network management while providing the benefits of multiple physical connections.
Managing Direct Connect Link Aggregation Groups using Terraform
Working with Direct Connect LAGs through Terraform requires careful planning and a solid understanding of the dependencies between network resources. Unlike simpler AWS services, LAGs involve coordination between multiple physical connections, virtual interfaces, and routing configurations that must be precisely orchestrated to avoid connectivity disruptions.
The complexity stems from the fact that LAGs operate at the physical layer while integrating with virtual networking constructs. You're essentially managing both the hardware aggregation and the logical network interfaces that applications consume. This dual nature means that Terraform configurations must account for connection provisioning delays, bandwidth allocation across member connections, and the specific sequencing required to maintain connectivity during updates.
Production-Ready LAG with Redundant Connections
For production environments, creating a LAG with multiple connections across different facilities provides both increased bandwidth and geographic redundancy. This configuration protects against facility-level outages while maximizing throughput capacity.
# Create the Direct Connect LAG
resource "aws_dx_lag" "production_lag" {
name = "production-primary-lag"
connections_bandwidth = "10Gbps"
location = "EqDC2" # Primary facility
number_of_connections = 2
provider_name = "Equinix"
tags = {
Environment = "production"
Project = "hybrid-connectivity"
Owner = "network-team"
Purpose = "primary-aws-connection"
}
}
# Add additional connections from secondary facility
resource "aws_dx_connection" "secondary_facility_connection" {
count = 2
name = "secondary-facility-conn-${count.index + 1}"
bandwidth = "10Gbps"
location = "EqDA2" # Secondary facility
provider_name = "Equinix"
tags = {
Environment = "production"
Project = "hybrid-connectivity"
LAG = aws_dx_lag.production_lag.id
Facility = "secondary"
}
}
# Associate secondary facility connections with LAG
resource "aws_dx_lag_connection_association" "secondary_connections" {
count = length(aws_dx_connection.secondary_facility_connection)
connection_id = aws_dx_connection.secondary_facility_connection[count.index].id
lag_id = aws_dx_lag.production_lag.id
depends_on = [aws_dx_connection.secondary_facility_connection]
}
# Create Virtual Interface for production workloads
resource "aws_dx_private_virtual_interface" "production_vif" {
connection_id = aws_dx_lag.production_lag.id
name = "production-private-vif"
vlan = 100
# BGP configuration
bgp_asn = 65000
address_family = "ipv4"
customer_address = "192.168.1.1/30"
amazon_address = "192.168.1.2/30"
# Route filtering
route_filter_prefixes = [
"10.0.0.0/16", # Production VPC CIDR
"10.1.0.0/16", # Staging VPC CIDR
"172.16.0.0/12" # On-premises networks
]
tags = {
Environment = "production"
VIF-Type = "private"
Purpose = "production-workloads"
}
}
# Create backup VIF on the same LAG
resource "aws_dx_private_virtual_interface" "backup_vif" {
connection_id = aws_dx_lag.production_lag.id
name = "backup-private-vif"
vlan = 200
bgp_asn = 65000
address_family = "ipv4"
customer_address = "192.168.2.1/30"
amazon_address = "192.168.2.2/30"
# Backup routes with higher BGP weights
route_filter_prefixes = [
"10.0.0.0/16",
"10.1.0.0/16"
]
tags = {
Environment = "production"
VIF-Type = "private-backup"
Purpose = "failover-connectivity"
}
}
This configuration creates a production-grade LAG with several important characteristics. The connections_bandwidth
parameter defines the bandwidth for each individual connection within the LAG, while number_of_connections
determines how many connections are initially provisioned. The LAG automatically distributes traffic across all active member connections using hash-based load balancing.
The secondary facility connections provide geographic redundancy by connecting from a different physical location. This protects against facility-level outages or maintenance windows that might affect the primary location. The aws_dx_lag_connection_association
resources explicitly associate these connections with the LAG after they're provisioned.
Virtual interfaces on the LAG operate identically to VIFs on individual connections, but they benefit from the aggregated bandwidth and redundancy of all member connections. The route filtering configuration controls which prefixes are advertised across the connection, preventing accidental route leakage between environments.
Development LAG with Cost Optimization
For development and testing environments, you can create a smaller LAG configuration that balances redundancy with cost considerations. This approach provides some fault tolerance while minimizing the expense of multiple high-bandwidth connections.
# Development LAG with lower bandwidth connections
resource "aws_dx_lag" "development_lag" {
name = "development-lag"
connections_bandwidth = "1Gbps"
location = "EqDC2"
number_of_connections = 2
provider_name = "Equinix"
tags = {
Environment = "development"
Project = "hybrid-connectivity"
Owner = "devops-team"
Purpose = "development-testing"
CostCenter = "engineering"
}
}
# Single VIF for development workloads
resource "aws_dx_private_virtual_interface" "development_vif" {
connection_id = aws_dx_lag.development_lag.id
name = "development-private-vif"
vlan = 300
bgp_asn = 65000
address_family = "ipv4"
customer_address = "192.168.3.1/30"
amazon_address = "192.168.3.2/30"
# Limited route filtering for development
route_filter_prefixes = [
"10.2.0.0/16", # Development VPC CIDR
"192.168.0.0/16" # Development on-premises
]
tags = {
Environment = "development"
VIF-Type = "private"
Purpose = "development-workloads"
}
}
# Virtual gateway for development VPC attachment
resource "aws_dx_gateway" "development_gateway" {
name = "development-dx-gateway"
tags = {
Environment = "development"
Purpose = "vpc-connectivity"
}
}
# Associate VIF with Direct Connect Gateway
resource "aws_dx_gateway_association" "development_vif_association" {
dx_gateway_id = aws_dx_gateway.development_gateway.id
virtual_interface_id = aws_dx_private_virtual_interface.development_vif.id
# Allowed prefixes for this association
allowed_prefixes = [
"10.2.0.0/16"
]
}
# Development VPC attachment
resource "aws_dx_gateway_association" "development_vpc_association" {
dx_gateway_id = aws_dx_gateway.development_gateway.id
associated_gateway_id = aws_vpn_gateway.development_vgw.id
# Propagated routes from VPC
allowed_prefixes = [
"10.2.0.0/16"
]
depends_on = [aws_dx_gateway_association.development_vif_association]
}
# VPN Gateway for development VPC
resource "aws_vpn_gateway" "development_vgw" {
vpc_id = data.aws_vpc.development_vpc.id
tags = {
Environment = "development"
Purpose = "directconnect-attachment"
}
}
# Data source for existing development VPC
data "aws_vpc" "development_vpc" {
filter {
name = "tag:Environment"
values = ["development"]
}
}
This development configuration demonstrates several cost-optimization strategies. The 1Gbps connections provide sufficient bandwidth for development workloads while reducing port costs. The single VIF configuration simplifies routing and reduces the complexity of managing multiple network paths.
The Direct Connect Gateway integration allows the LAG to connect to multiple VPCs without requiring separate VIFs for each VPC. This approach scales more efficiently as you add development environments and provides centralized routing control through the gateway.
The allowed_prefixes
configuration on both the VIF association and VPC association provides fine-grained control over which routes are exchanged between on-premises and AWS environments. This prevents accidental connectivity between development and production networks.
The dependency management between the gateway associations ensures that Terraform creates the VIF association before attempting to associate VPCs. This sequencing prevents race conditions that can occur when multiple resources try to modify the same Direct Connect Gateway simultaneously.
Both configurations demonstrate the importance of comprehensive tagging strategies for Direct Connect resources. Tags enable cost tracking, resource organization, and automated management policies. The CostCenter
tag in the development configuration allows for chargeback to specific teams or projects.
When implementing these configurations, consider the lead times for Direct Connect provisioning. Physical connections typically require 2-4 weeks for initial setup, though LAG modifications for existing connections can be completed much faster. Plan your Terraform deployments accordingly, and consider using separate apply operations for the initial LAG creation versus subsequent modifications.
Best practices for Direct Connect Link Aggregation Groups (LAGs)
Managing Direct Connect LAGs requires careful attention to both networking fundamentals and AWS-specific configuration patterns. These practices have been developed through real-world implementations across enterprise environments where network reliability directly impacts business operations.
Design for Redundancy Across Multiple Locations
Why it matters: Single location failures can take down entire LAG configurations, regardless of how many connections you bundle together. Geographic diversity protects against facility-level outages, power failures, and regional network issues.
Implementation: Always distribute LAG connections across different Direct Connect locations when possible. For maximum resilience, configure LAGs in at least two separate AWS regions with cross-region routing capabilities.
# Verify connection locations for your LAG
aws directconnect describe-lags --lag-id dxlag-12345678 \\
--query 'lags[0].connections[*].location'
# Check connection distribution
aws directconnect describe-connections \\
--query 'connections[?lagId==`dxlag-12345678`].[connectionId,location]'
Consider implementing a hub-and-spoke topology where primary LAGs handle normal traffic loads, while secondary LAGs in different locations provide automatic failover. This approach has proven effective for organizations processing financial transactions or real-time data where even brief network interruptions can have significant business impact.
Implement Proper LACP Configuration and Monitoring
Why it matters: Link Aggregation Control Protocol (LACP) manages the bundling of physical connections, but misconfigurations can lead to uneven traffic distribution, connection flapping, or complete LAG failures. Proper LACP tuning maximizes both performance and reliability.
Implementation: Configure LACP with appropriate timing intervals and ensure all connections use identical parameters. Monitor LACP statistics regularly to detect early signs of connection degradation.
# Monitor LACP health and traffic distribution
resource "aws_cloudwatch_metric_alarm" "lag_connection_state" {
alarm_name = "directconnect-lag-connection-down"
comparison_operator = "LessThanThreshold"
evaluation_periods = "2"
metric_name = "ConnectionState"
namespace = "AWS/DX"
period = "60"
statistic = "Maximum"
threshold = "1"
alarm_description = "Direct Connect LAG connection is down"
dimensions = {
ConnectionId = "dxcon-12345678"
}
}
Set up automated alerts for LACP negotiation failures and implement procedures for investigating connection asymmetries. Many organizations discover that seemingly minor timing differences between connections can cause significant performance variations under load.
Right-Size Your LAG Capacity with Growth Planning
Why it matters: LAG capacity planning involves more than simple bandwidth addition. Each connection in a LAG must be identical in terms of bandwidth, and scaling requires careful coordination with AWS and your network provider. Poor capacity planning leads to either wasted resources or performance bottlenecks.
Implementation: Plan LAG capacity based on peak traffic patterns plus 30-40% headroom for growth. Consider that LAG traffic distribution may not be perfectly even across all connections, especially during connection failures.
# Analyze current LAG utilization patterns
aws cloudwatch get-metric-statistics \\
--namespace AWS/DX \\
--metric-name ConnectionBpsEgress \\
--dimensions Name=ConnectionId,Value=dxlag-12345678 \\
--start-time 2024-01-01T00:00:00Z \\
--end-time 2024-01-31T23:59:59Z \\
--period 3600 \\
--statistics Average,Maximum
Monitor individual connection utilization within your LAG to identify uneven traffic distribution. This data helps determine when to add additional connections and whether your current configuration effectively balances traffic across all available links.
Configure BGP Routing for LAG Resilience
Why it matters: BGP routing configuration determines how traffic flows through your LAG and how quickly your network adapts to connection failures. Poor BGP configuration can negate the redundancy benefits of LAGs, leading to traffic loss during transitions.
Implementation: Configure BGP with appropriate AS-PATH prepending and local preference values to control traffic flow. Implement BFD (Bidirectional Forwarding Detection) for faster failure detection.
resource "aws_dx_virtual_interface" "lag_vif" {
connection_id = aws_dx_lag.main.id
name = "production-lag-vif"
vlan = 100
address_family = "ipv4"
bgp_asn = 65000
amazon_address = "192.168.1.1/30"
customer_address = "192.168.1.2/30"
bgp_auth_key = var.bgp_auth_key
tags = {
Environment = "production"
Purpose = "lag-primary"
}
}
Test BGP failover scenarios regularly by simulating connection failures. Document expected convergence times and ensure they meet your application's tolerance for network interruptions. Many organizations find that default BGP timers are too slow for their requirements and need customization.
Monitor LAG Health with Comprehensive Metrics
Why it matters: LAG health monitoring requires tracking multiple layers: physical connection status, LACP negotiation state, traffic distribution, and application-level performance. Without comprehensive monitoring, problems often go undetected until they cause user-visible issues.
Implementation: Implement monitoring that tracks both AWS-provided metrics and custom application-level performance indicators. Set up alerts for connection imbalances and performance degradation.
# Create comprehensive LAG monitoring dashboard
aws cloudwatch put-dashboard --dashboard-name "DirectConnect-LAG-Health" \\
--dashboard-body '{
"widgets": [
{
"type": "metric",
"properties": {
"metrics": [
["AWS/DX", "ConnectionBpsEgress", "ConnectionId", "dxlag-12345678"],
[".", "ConnectionBpsIngress", ".", "."],
[".", "ConnectionPpsEgress", ".", "."],
[".", "ConnectionPpsIngress", ".", "."]
],
"period": 300,
"stat": "Average",
"region": "us-east-1",
"title": "LAG Traffic Metrics"
}
}
]
}'
Establish baseline performance metrics for your LAG configuration and monitor for deviations. Track packet loss, latency variations, and throughput consistency across all connections. This data becomes invaluable when troubleshooting performance issues or planning capacity changes.
Implement LAG Configuration Management and Change Control
Why it matters: LAG configurations involve coordination between multiple parties: AWS, your network provider, and your internal teams. Changes must be carefully orchestrated to avoid service disruptions, and configuration drift can lead to subtle performance issues.
Implementation: Use infrastructure as code for all LAG configurations and implement strict change management processes. Maintain configuration documentation that includes both technical specifications and operational procedures.
# Implement LAG configuration with proper versioning
resource "aws_dx_lag" "production" {
name = "production-lag-${var.environment}"
connections_bandwidth = "1Gbps"
location = var.dx_location
number_of_connections = 4
tags = {
Environment = var.environment
ConfigVersion = "v2.1.0"
ChangeTicket = "CHG-2024-001"
MaintenanceWindow = "Sunday-02:00-06:00-UTC"
}
}
Document rollback procedures for LAG changes and test them regularly. Many organizations have discovered that LAG modifications can have unexpected impacts on traffic patterns, making quick rollback capabilities critical for maintaining service availability.
These best practices reflect lessons learned from enterprise implementations where network reliability directly impacts business operations. The key to successful LAG management lies in treating network infrastructure as a critical business asset that requires the same level of attention and care as any other production system.
Product Integration
Direct Connect Link Aggregation Groups integrate seamlessly with AWS's networking ecosystem, creating a foundation for high-performance hybrid cloud architectures. The service works hand-in-hand with AWS networking services to provide comprehensive connectivity solutions.
LAGs connect directly to Virtual Private Gateways (VGWs) and Direct Connect Gateways (DXGWs), enabling sophisticated routing scenarios. With EC2 VPC integration, LAGs can distribute traffic across multiple availability zones while maintaining consistent latency profiles. This integration becomes particularly powerful when combined with EC2 Route Tables that can leverage multiple paths for optimal traffic distribution.
The integration extends to AWS Transit Gateway, where LAGs can serve as high-bandwidth connections between on-premises networks and multiple VPCs. This architecture pattern supports complex multi-VPC deployments where consistent, high-throughput connectivity is required across all environments.
CloudWatch monitoring integration provides real-time visibility into LAG performance, with metrics for individual connection health, aggregate bandwidth utilization, and error rates. These metrics feed into CloudWatch Alarms that can trigger automated responses when connection issues arise.
Use Cases
Enterprise Data Center Migration
Large enterprises migrating workloads to AWS often face bandwidth and reliability challenges during the transition period. LAGs provide the high-throughput, resilient connectivity needed for large-scale data migration projects.
A Fortune 500 financial services company used LAGs to migrate 500TB of trading data while maintaining real-time replication between their on-premises data center and AWS. The LAG configuration provided 20Gbps of aggregate bandwidth with automatic failover, enabling them to complete the migration 60% faster than estimated while maintaining zero-downtime operations.
High-Frequency Trading and Financial Services
Financial institutions require ultra-low latency and high-reliability connections for trading systems and risk management platforms. LAGs deliver the consistent performance and redundancy needed for these demanding applications.
A major investment bank implemented LAGs to connect their trading floor to AWS-hosted risk calculation engines. The configuration provided sub-10ms latency consistency and 99.99% uptime, enabling real-time portfolio risk assessment without performance degradation during market volatility.
Media and Content Distribution
Media companies processing large video files and streaming content benefit from LAGs' high-bandwidth capabilities and reliability for content ingestion and distribution workflows.
A streaming platform uses LAGs to upload 4K content from production studios to AWS, where S3 buckets store the raw content and CloudFront distributions handle global delivery. The LAG configuration provides 40Gbps of aggregate bandwidth, reducing upload times by 75% and eliminating transfer interruptions.
Limitations
Cost Considerations
LAGs require multiple Direct Connect connections, which significantly increases monthly costs compared to single-connection setups. Each connection in a LAG incurs separate port fees, cross-connect charges, and bandwidth costs. For smaller organizations, the financial commitment can be substantial, often ranging from $5,000 to $50,000 monthly depending on bandwidth requirements.
Geographic and Facility Constraints
LAGs are limited to connections within the same Direct Connect location, which can create challenges for organizations requiring geographic redundancy. If a Direct Connect facility experiences issues, the entire LAG becomes unavailable. This limitation requires careful consideration of disaster recovery strategies and may necessitate additional LAGs in different locations.
Complex Configuration Requirements
LAGs require identical connection specifications across all member connections, including bandwidth, VLAN configurations, and BGP settings. This uniformity requirement can limit flexibility in network design and make troubleshooting more complex. Changes to LAG configuration often require coordination across multiple connections, increasing the risk of service disruption during maintenance windows.
Bandwidth Scaling Limitations
While LAGs provide increased bandwidth through aggregation, they cannot exceed the maximum bandwidth supported by individual connection types. For organizations requiring bandwidth beyond 100Gbps, LAGs may not provide sufficient capacity, requiring alternative solutions like multiple LAGs or different connectivity approaches.
Conclusion
AWS Direct Connect Link Aggregation Groups represent a mature solution for organizations requiring high-bandwidth, resilient connectivity between on-premises infrastructure and AWS services. The service addresses fundamental challenges in hybrid cloud networking by providing both increased throughput capacity and built-in redundancy through connection bundling.
The integration with AWS's broader networking ecosystem, from VPC endpoints to Transit Gateway, creates opportunities for sophisticated network architectures that can scale with business requirements. Organizations implementing LAGs typically see significant improvements in application performance consistency and reduced network-related downtime.
However, the service requires careful planning and substantial financial investment. The cost implications, geographic limitations, and configuration complexity mean that LAGs are most suitable for enterprises with significant bandwidth requirements and the resources to manage complex network configurations.
For organizations with demanding network performance requirements, regulatory compliance needs, or large-scale data transfer requirements, LAGs provide a proven path to reliable, high-performance AWS connectivity. The technology particularly shines in scenarios requiring predictable bandwidth and fault tolerance, making it an excellent choice for financial services, media companies, and large enterprises with substantial cloud workloads.
When implementing LAGs through Terraform, the complexity of managing multiple connections and their interdependencies creates potential for configuration errors that could impact production traffic. Understanding these relationships and implementing proper change management processes becomes critical for maintaining service reliability.