• provides high availability
• uses 5-tuple hash by default to forward traffic (source ip/port, destination ip/port, protocol)
• frontend connects to LB. LB connects to backend based on rules and health checks.
• can be used for inbound or outbound scenarios
• [[202407281423 Create Azure Load Balancer|Create Azure Load Balancer]] / needs:
  • frontend ip
  • backend pool
  • health probe
  • LB rules

Types

• public
• internal

Distribution methods

• 5 tuple hash
• source ip affinity
  • 2-tuple hash (source ip, destination ip)
  • 3-tuple hash (source ip, destination ip, protocol)

SKUs

• basic
  • open by default
  • inbound only
  • http/tcp probes
  • upto 300 backend pools
  • vms in a single availability set or [[202404181846 Azure VM scale sets|VMSS]]
  • supports basic [[202407271143 Public IP address allows inbound access based on tier in Azure|Public IP Address]]
• standard
  • closed by default
  • inbound/outbound
  • http/https/tcp probes
  • upto 1000 backend pools
  • vms in a [[202404121703 Azure VNet|VNet]]
• gateway
  • high performance
  • with NVAs

Backend pools

Health probes

• http probe
  • pings every 15 seconds
  • http 200 response means healthy within timeout period (default 31 sec)
• tcp probe
  • creates a tcp session.

LB rules

Stickiness

• By default traffic can go to any VM
• With persistence we can set which requests go to the same vm:
  • none
  • client ip
  • Client IP and protocol

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references:

MS Learn

• To implement a load balancer, you configure four components: - Front-end IP configuration - Back-end pools - Health probes - Load-balancing rules

• To configure a probe, you specify values for the following settings: - Port: Back-end port - URI: URI for requesting the health status from the backend - Interval: Amount of time between probe attempts (default is 15 seconds) - Unhealthy threshold: Number of failures that must occur for the instance to be considered unhealthy

MS Learn