Oops, sorry, I got AZs and regions mixed up! Best Jan --
> On 5. Dec 2017, at 13:43, Robert Samuel Newson <[email protected]> wrote: > > Sorry to contradict you, but Cloudant deploys clusters across amazon AZ's as > standard. It's fast enough. It's cross-region that you need to avoid. > > B. > >> On 5 Dec 2017, at 09:11, Jan Lehnardt <[email protected]> wrote: >> >> Heya Geoff, >> >> a CouchDB cluster is designed to run in the same data center / with local >> are networking latencies. A cluster across AWS Availability Zones won’t work >> as you see. If you want CouchDB’s in both AZs, use regular replication and >> keep the clusters local to the AZ. >> >> Best >> Jan >> -- >> >>> On 4. Dec 2017, at 19:46, Geoffrey Cox <[email protected]> wrote: >>> >>> Hi, >>> >>> I've spent days using trial and error to try and figure out why I am >>> getting a very high CPU load on only a single node in my cluster. I'm >>> hoping someone has an idea of what is going on as I'm getting stuck. >>> >>> Here's my configuration: >>> >>> 1. 2 node cluster: >>> 1. Each node is located in a different AWS availability zone >>> 2. Each node is a t2 medium instance (2 CPU cores, 4 GB Mem) >>> 2. A haproxy server is load balancing traffic to the nodes using round >>> robin >>> >>> The problem: >>> >>> 1. After users make changes via PouchDB, a backend runs a number of >>> routines that use views to calculate notifications. The issue is that on a >>> single node, the couchjs processes stack up and then start to consume >>> nearly all the available CPU. This server then becomes the "workhorse" that >>> always does *all* the heavy duty couchjs processing until I restart this >>> node. >>> 2. It is important to note that both nodes have couchjs processes, but >>> it is only a single node that has the couchjs processes that are using 100% >>> CPU >>> 3. I've even resorted to setting `os_process_limit = 10` and this just >>> results in each couchjs process taking over 10% each! In other words, the >>> couchjs processes just eat up all the CPU no matter how many couchjs >>> process there are! >>> 4. The CPU usage will eventually clear after all the processing is done, >>> but then as soon as there is more to process the workhorse node will get >>> bogged down again. >>> 5. If I restart the workhorse node, the other node then becomes the >>> workhorse node. This is the only way to get the couchjs processes to "move" >>> to another node. >>> 6. The problem is that this design is not scalable as only one node can >>> be the workhorse node at any given time. Moreover this causes specific >>> instances to run out of CPU credits. Shouldn't the couchjs processes be >>> spread out over all my nodes? From what I can tell, if I add more nodes I'm >>> still going to have the issue where only one of the nodes is getting bogged >>> down. Is it possible that the problem is that I have 2 nodes and really I >>> need at least 3 nodes? (I know a 2-node cluster is not very typical) >>> >>> >>> Things I've checked: >>> >>> 1. Ensured that the load balancing is working, i.e. haproxy is indeed >>> distributing traffic accordingly >>> 2. I've tried setting `os_process_limit = 10` and `os_process_soft_limit >>> = 5` to see if I could force a more conservative usage of couchjs >>> processes, but instead the couchjs processes just consume all the CPU load. >>> 3. I've tried simulating the issue locally with VMs and I cannot >>> duplicate any such load. My guess is that this is because the nodes are >>> located on the same box so hop distance between nodes is very small and >>> this somehow keeps the CPU usage to a minimum >>> 4. I've tried isolating the issue by creating short code snippets that >>> intentionally try to spawn a lot of couchjs processes and they are spawned >>> but don't consume 100% CPU >>> 5. I've tried rolling back from CouchDB 2.1.1 to CouchDB 2.0 and this >>> doesn't seem to change anything >>> 6. The only error entries in my CouchDB logs are like the following and >>> I don't believe they are related to my issue: >>> 1. >>> >>> [error] 2017-12-04T18:13:38.728970Z [email protected] <0.13974.79> >>> 4b0b21c664 rexi_server: from: [email protected](<0.20638.79>) mfa: >>> fabric_rpc:open_shard/2 throw:{forbidden,<<"You are not allowed to access >>> this db.">>} >>> >>> [{couch_db,open,2,[{file,"src/couch_db.erl"},{line,185}]},{fabric_rpc,open_shard,2,[{file,"src/fabric_rpc.erl"},{line,267}]},{rexi_server,init_p,3,[{file,"src/rexi_server.erl"},{line,139}]}] >>> >>> Does CouchDB have some logic built in that spawns a number of couchjs >>> processes on a "primary" node? Will future view processing then always be >>> routed to this "primary" node? >>> >>> Is there a way to better distribute these heavy duty couchjs processes? Is >>> it possible to limit their CPU consumption? (I'm hesitant to start down the >>> path of using something like cpulimit as I think there is a root problem >>> that needs to be addressed) >>> >>> I'm running out of ideas and hope that someone has some notion of what is >>> causing this bizarre load or if there is a bug in CouchDB. >>> >>> Thank you for any help you can provide! >>> >>> Geoff >> >> -- >> Professional Support for Apache CouchDB: >> https://neighbourhood.ie/couchdb-support/ >> > -- Professional Support for Apache CouchDB: https://neighbourhood.ie/couchdb-support/
