Notes and Thoughts on Cephadm’s scalability
About this document
This document does NOT define a specific proposal or some future work. Instead it merely lists a few thoughts that MIGHT be relevant for future cephadm enhancements.
Cephadm manages all registered hosts. This means that it periodically scrapes data from each host to identify changes on the host like:
host network/firewall etc has changed
Currently, cephadm scrapes each host (up to 10 in parallel) every 6 minutes, unless a refresh is forced manually.
Refreshes for disks (ceph-volume), daemons (podman/docker), etc, happen in sequence.
With the cephadm exporter, we have now reduced the time to scan hosts considerably, but the question remains:
Is the cephadm-exporter sufficient to solve all future scalability issues?
Considerations of cephadm-exporter’s REST API
The cephadm-exporter uses HTTP to serve an endpoint to the hosts metadata. We MIGHT encounter some issues with this approach, which need to be mitigated at some point.
With the cephadm-exporter we use SSH and HTTP to connect to each host. Having two distinct transport layers feels odd, and we might want to consider reducing it to only a single protocol.
The current approach of delivering
bin/cephadmto the host doesn’t allow the use of external dependencies. This means that we’re stuck with the built-in HTTP server lib, which isn’t great for providing a good developer experience.
bin/cephadmneeds to be packaged and distributed (one way or the other) for us to make use of a better http server library.
MON’s config-key store
mgr/cephadm queried metadata from each host, cephadm stores
the data within the mon’s k-v store.
If each host would be allowed to write their own metadata to the store,
mgr/cephadm would no longer be required to gather the data.
Some questions arise:
mgr/cephadmnow needs to query data from the config-key store, instead of relying on cached data.
cephadm knows three different types of data: (1) Data that is critical and needs to be stored in the config-key store. (2) Data that can be kept in memory only. (3) Data that can be stored in RADOS pool. How can we apply this idea to those different types of data.
Increase the worker pool size
mgr/cephadm is currently able to scrape 10 nodes at the same time.
The scrape of a individual host takes the same amount of time persists. We’d just reduce the overall execution time.
At best we can reach O(hosts) + O(daemons).
Any changes need to be backwards compatible or completely isolated from any existing functionality. There are running cephadm clusters out there that require an upgrade path.