Maglev

Google( https://research.google.com/pubs/pub44824.html )
Used in Google Cloud since 2008
Scalable load balancer
- Consistent hashing
- Connection Tracking
- Scale-out model backed by router’s ECMP
Bypass kernel space for performance.
Support connection persistence

Network Architecture

DNS - Routers - Maglevs - Service EndPoints.
One service is served by one or more VIPs
- DNS returns VIP considering geolocation and load of location
One VIP is served by multiple Maglevs
- Router use ECMP to select one Maglev
One VIP is mapped to multiple Service EndPoints
- Maglev select Service EndPoint by seletion algorithm and connection tracking table
Maglev use GRE to send incoming packet to Service EndPoint or another Maglev
- Send to IP fragment to another special Maglev servers
- Use only 3-tuple for IP fragment
Each Service EndPoint use Direct Server Return(DSR)

Each VIP has one or multiple backend pools(BP)
BP contain physical IP address of the Service EndPoint
Each BP has specific health checking methods - depends on the service requirement(just reachability or more)
Config Manager parse and update configuration of forwarder’s behavior based on the Config Objects
Sharding
- Sharding of Maglev enables service isolation - new service or QoS

Consistent Hashing distribute loads
Record selection in LOCAL connection tracking table
- Connection tracking table is not shared with another Maglev
- Does not guarantee consistency on Maglev or Service EndPoint Changes(add/delete)
For different traffic type
- TCP SYN : select Backend and record it in connection tracking table
- TCP non-SYN : lookup connection tracking table
- 5-tuple : (maybe) lookup connection tracking table and select backend if not found

If Maglev is added or removed, router select different Maglev for the exsiting session - ECMP is changed
If one Maglev’s local connection tracking table is overflowed, it will lose previous selection
To resolve this issues,
- Synchronize local connection tracking table between Maglevs -> overhead, overhead, overhead
- Consistent hashing for minimize disruption in member changes
- Maglev hashing - load balancing and minimal disruption on member changes