CHT Core Framework > Overview > CHT Core
The different pieces of a CHT project, how they interact, and what they’re used for
Vertical vs Horizontal scaling
The power of clustered CouchDB to horizontally scale the CHT
Introduction
Horizontally scaling is the ability to add more servers to an application to make it more performant. This often yields better performance than vertical scaling, which is adding more resources like RAM or CPU to a single server.
CHT Core 4.0.0 introduces a new architecture for hosting which gives it the ability to easily scale horizontally. This enables large deployments to support more concurrent users and better utilize the underlying server hardware.
Vertical scaling in 3.x and 4.x
Before getting into how the CHT horizontally scales, it should be well understood the importance of vertical scaling and what it is. This is the ability of the CHT to support more users by adding more RAM and CPU to either the bare-metal or virtual machine host. This ensures key services like API, Sentinel and, most importantly, CouchDB, can operate without performance degradation.
When thousands of users are simultaneously trying to synchronize with the CHT, the load can overwhelm CouchDB. As discovered through extensive research and large production deployments, administrators will start to see errors in their logs and end users will complain of slow sync times. Before moving to more CouchDB nodes, administrators should consider adding more RAM and CPU to the single server where the CHT is hosted. This applies to both CHT 3.x and CHT 4.x. Given the ease of allocating more resources, presumably in virtualized environment like EC2, Proxmox or ESXi, this is much easier than moving from a single to multi-node CouchDB instance.
Here we see a normal deployment following the bare minimum hosting requirements for the CHT. We’ll call this a “short” deployment because it is not yet vertically scaled:
flowchart TD + Create documentation issue + Create project issue
Vertical vs Horizontal scaling
The power of clustered CouchDB to horizontally scale the CHT
Introduction
Horizontally scaling is the ability to add more servers to an application to make it more performant. This often yields better performance than vertical scaling, which is adding more resources like RAM or CPU to a single server.
CHT Core 4.0.0 introduces a new architecture for hosting which gives it the ability to easily scale horizontally. This enables large deployments to support more concurrent users and better utilize the underlying server hardware.
Vertical scaling in 3.x and 4.x
Before getting into how the CHT horizontally scales, it should be well understood the importance of vertical scaling and what it is. This is the ability of the CHT to support more users by adding more RAM and CPU to either the bare-metal or virtual machine host. This ensures key services like API, Sentinel and, most importantly, CouchDB, can operate without performance degradation.
When thousands of users are simultaneously trying to synchronize with the CHT, the load can overwhelm CouchDB. As discovered through extensive research and large production deployments, administrators will start to see errors in their logs and end users will complain of slow sync times. Before moving to more CouchDB nodes, administrators should consider adding more RAM and CPU to the single server where the CHT is hosted. This applies to both CHT 3.x and CHT 4.x. Given the ease of allocating more resources, presumably in virtualized environment like EC2, Proxmox or ESXi, this is much easier than moving from a single to multi-node CouchDB instance.
Here we see a normal deployment following the bare minimum hosting requirements for the CHT. We’ll call this a “short” deployment because it is not yet vertically scaled:
flowchart TD
subgraph couch1[" CouchDB - Single ''short'' Node "]
couchInner1["2 CPU/4 GB RAM"]
@@ -328,8 +328,8 @@
Data migration to 4.xGuide to migrate existent data from CHT 3.x to CHT 4.x