virajjasani commented on PR #5396:
URL: https://github.com/apache/hadoop/pull/5396#issuecomment-1432160563

   In a distributed system, it is essential to have robust fail-fast mechanisms 
in place to prevent issues related to network partitioning. The system must be 
designed to prevent further degradation of availability and consistency in the 
event of a network partition. Several distributed systems offer fail-safe 
approaches, and for some, partition tolerance is critical to the extent that 
even a few seconds of heartbeat loss can trigger the removal of an application 
server instance from the cluster. For instance, a majority of zooKeeper clients 
utilize the ephemeral nodes for this purpose to make system reliable, 
fault-tolerant and strongly consistent in the event of network partition.
   
   From the hdfs architecture viewpoint, it is crucial to understand the 
critical role that active and observer namenode play in file system operations. 
In a large-scale cluster, if the datanodes holding the same block (primary and 
replicas) lose connection to both active and observer namenodes for a 
significant amount of time, delaying the process of shutting down such 
datanodes and restarting it to re-establish the connection with the namenodes 
(assuming the active namenode is alive, assumption is important in the even of 
network partition to reestablish the connection) will further deteriorate the 
availability of the service. This scenario underscores the importance of 
resolving network partitioning.
   
   This is a real use case for hdfs and it is not prudent to assume that every 
deployment or cluster management application must be able to restart datanodes 
based on JMX metrics, as this would introduce another application to resolve 
the network partition impact of hdfs. Besides, popular cluster management 
applications are not typically used in all cloud-native env. Even if these 
cluster management applications are deployed, certain security constraints may 
restrict their access to JMX metrics and prevent them from interfering with 
hdfs operations. The applications that can only trigger alerts for users based 
on set parameters (for instance, missing blocks > 0) are allowed to access JMX 
metrics.


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