Adaptive Load Balancer Connection Limits for Cloud Native Scaling
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Solution Overview
Problem
In cloud native environments, load balancers struggle to implement effective connection throttling due to the loss of client source IP information during traffic routing, making applications vulnerable to DDoS attacks and resource exhaustion.
Innovation Solution
Implementing a load balancer controller (LBC) that monitors application scaling states and adjusts connection limits based on cloud operator or application-provided rules, allowing dynamic control of connection forwarding behavior to protect against malicious attacks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the load balancer routes traffic to cluster nodes, then load distribution and resource utilization are improved, but client source IP information is lost and connection throttling becomes impossible
Solution Approach 1:
The load balancer acts as an intermediary that performs source IP preservation through specific routing configurations. By using XDP (eXpress Data Path) or similar advanced networking techniques, the load balancer mediates between traffic distribution requirements and source IP information preservation, allowing both functions to coexist without information loss.
2Reliability
If the application waits for TLS handshake to determine client identity, then authentication is improved, but the application remains vulnerable to DDoS attacks during the connection establishment phase
Solution Approach 1:
The load balancer performs preliminary connection throttling and source IP validation before the TLS handshake completes. By implementing connection limits and rate restricting at the load balancer level using preserved source IP information, the system performs protective action in advance, preventing DDoS attacks from overwhelming the application during the vulnerable connection establishment phase.
3Productivity
If new replicas are added to scale the application, then capacity to handle connections is improved, but rogue clients can drive growth through malicious connections
Solution Approach 1:
The load balancer implements preliminary protective measures by establishing connection limits and rate restricting policies before malicious connections can trigger unwanted scaling. By monitoring connection patterns and detecting rogue clients using preserved source IP information, the load balancer takes anti-action in advance to prevent malicious connections from driving application growth.
Data Source
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AI summary
Systems and methods are disclosed for implementing cloud native application load balancing. In certain embodiments, a method may comprise operating a cloud native application load balancing system to implement a process to impose application scaling-based connection limits on a cloud native (CN) application via a load balancer, including obtaining, at a load balancer controller (LBC), a set of connection limits for the CN application, the set of connection limits correlated to a scaling state of the CN application. The method may include configuring the load balancer to apply the set of connection limits for incoming connection requests directed to the CN application, obtaining, at the LBC, an indication of an update to the set of connection limits based on a change in the scaling state of the CN application, and controlling the load balancer to implement the update to the set of connection limits.