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docs: fixed some typos, formatting, grammar (#11540)

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# Which Problems Are Solved

- Typos
- Punctuation
- Markdown table formatting
- ...

(A bunch of issues my editor gave)

# How the Problems Are Solved


# Additional Changes


# Additional Context
This commit is contained in:
Wim Van Laer
2026-02-13 07:45:17 +01:00
committed by GitHub
parent b0609aa861
commit 9b064d8b74
127 changed files with 764 additions and 760 deletions
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apps/docs/content/concepts/architecture/software.mdx
+7 -7
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@@ -17,7 +17,7 @@ This All in One (AiO) approach makes operating Zitadel simple.
## The Architecture
Zitadels software architecture is built around multiple components at different levels.
Zitadel's software architecture is built around multiple components at different levels.
This chapter should give you an idea of the components as well as the different layers.
![](../../../public/img/zitadel_software_architecture.png)
@@ -63,7 +63,7 @@ The Command Side has some unique requirements, these include:
The command handler receives all operations who alter a resource managed by Zitadel.
For example if a user changes their name. The API Layer will pass the instruction received through the API call to the command handler for further processing.
The command handler is then responsible of creating the necessary commands.
The command handler is then responsible for creating the necessary commands.
After creating the commands the command hand them down to the command validation.
##### Command Validation
@@ -76,7 +76,7 @@ These events now are being handed down to the storage layer for storage.
#### Events
Zitadel handles events in two ways.
Events that should be processed in near real time are processed by a in memory pub sub system.
Events that should be processed in near real time are processed by an in memory pub sub system.
Some events can be handled asynchronously using the spooler.
##### Pub Sub
@@ -103,7 +103,7 @@ Spoolers are especially necessary where someone can query datasets instead of si
#### Projections
Projections are responsible of normalizing data for the query side or for analytical purpose.
Projections are responsible for normalizing data for the query side or for analytical purpose.
They generally work by being invoked either through a scheduled spooler or the pub sub subscription.
When they receive events they will create their normalized object and then store this into the query view and its storage layer.
@@ -122,10 +122,10 @@ It has some unique requirements, which include:
##### Query Handler
The query handler receives all read relevant operations. These can either be query or simple `getById` calls.
The query handler receives all read relevant operations. These can either be queries or simple `getById` calls.
When receiving a query it will proceed by passing this to the repository which will call the database and return the dataset.
If a request calls for a specific id the call will, most of the times, be revalidated against the Event Store.
This is achieved by triggering the projection to make sure that the last sequence of a id is loaded into the query view.
If a request calls for a specific id the call will, most of the time, be revalidated against the Event Store.
This is achieved by triggering the projection to make sure that the last sequence of an id is loaded into the query view.
> The query side has the option to dynamically check the Event Store for newer events on a certain id to make sure for consistent responses without delay.