This adds the ability to have multiple concurrent connections to a single device. This is primarily useful when the network has multiple physical links for aggregated bandwidth. A single connection will never see a higher rate than a single link can give, but multiple connections are load-balanced over multiple links.
It is also incidentally useful for older multi-core CPUs, where bandwidth could be limited by the TLS performance of a single CPU core -- using multiple connections achieves concurrency in the required crypto calculations...
Co-authored-by: Simon Frei <freisim93@gmail.com>
Co-authored-by: tomasz1986 <twilczynski@naver.com>
Co-authored-by: bt90 <btom1990@googlemail.com>
The problem was that a statistics/cleanup run is triggered when the
database started and runs concurrently with the test. That cleanup run
removes old entries without valid addresses, and one of the test objects
matched this. The test object would thus randomly be removed in the
middle of the test, causing a failure. This fixes it so the object looks
recent when the cleaner-upper looks, and also uses a RAM database
(faster).
This makes sure addresses are sorted when coming in from the API. The
database merge operation still checks for correct ordering (which is
quick) and sorts if it isn't correct (legacy database record or
replication peer), but then does a copy first.
Tested with -race in production...
* go mod init; rm -rf vendor
* tweak proto files and generation
* go mod vendor
* clean up build.go
* protobuf literals in tests
* downgrade gogo/protobuf
This is a new revision of the discovery server. Relevant changes and
non-changes:
- Protocol towards clients is unchanged.
- Recommended large scale design is still to be deployed nehind nginx (I
tested, and it's still a lot faster at terminating TLS).
- Database backend is leveldb again, only. It scales enough, is easy to
setup, and we don't need any backend to take care of.
- Server supports replication. This is a simple TCP channel - protect it
with a firewall when deploying over the internet. (We deploy this within
the same datacenter, and with firewall.) Any incoming client announces
are sent over the replication channel(s) to other peer discosrvs.
Incoming replication changes are applied to the database as if they came
from clients, but without the TLS/certificate overhead.
- Metrics are exposed using the prometheus library, when enabled.
- The database values and replication protocol is protobuf, because JSON
was quite CPU intensive when I tried that and benchmarked it.
- The "Retry-After" value for failed lookups gets slowly increased from
a default of 120 seconds, by 5 seconds for each failed lookup,
independently by each discosrv. This lowers the query load over time for
clients that are never seen. The Retry-After maxes out at 3600 after a
couple of weeks of this increase. The number of failed lookups is
stored in the database, now and then (avoiding making each lookup a
database put).
All in all this means clients can be pointed towards a cluster using
just multiple A / AAAA records to gain both load sharing and redundancy
(if one is down, clients will talk to the remaining ones).
GitHub-Pull-Request: https://github.com/syncthing/syncthing/pull/4648
