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Kevin Jahns 2019-05-08 13:33:41 +02:00
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The MIT License (MIT)
Copyright (c) 2019 Kevin Jahns <kevin.jahns@protonmail.com>.
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

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README.md
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@ -46,4 +46,8 @@ These are mere suggestions how you could scale your server environment.
**Option 1:** Websocket servers communicate with each other via a PubSub server. A room is represented by a PubSub channel. The downside of this approach is that the same shared document may be handled by many servers. But the upside is that this approach is fault tolerant, does not have a single point of failure, and is perfectly fit for route balancing.
**Option 2:** Sharding with *consistent hashing*. Each document is handled by a unique server. This patterns requires an entity, like etcd, that performs regular health checks and manages servers. Based on the list of available servers (which is managed by etcd) a proxy calculates which server is responsible for each requested document. The disadvantage of this approach is that it is that load distribution may not be fair. Still, this approach may be the preferred solution if you want to store the shared document in a database - e.g. for indexing.
**Option 2:** Sharding with *consistent hashing*. Each document is handled by a unique server. This patterns requires an entity, like etcd, that performs regular health checks and manages servers. Based on the list of available servers (which is managed by etcd) a proxy calculates which server is responsible for each requested document. The disadvantage of this approach is that it is that load distribution may not be fair. Still, this approach may be the preferred solution if you want to store the shared document in a database - e.g. for indexing.
### License
[The MIT License](./LICENSE) © Kevin Jahns