diff --git a/docs/creating-a-benchmark.md b/docs/creating-a-benchmark.md
index 122f43b645c9702d16722a3061bfde8bec7c94c6..2b1d93bbec0afb3a8897a77439388538fc75c4a6 100644
--- a/docs/creating-a-benchmark.md
+++ b/docs/creating-a-benchmark.md
@@ -108,6 +108,9 @@ Suppose the resources needed by your benchmark are defined as YAML files, locate
 Benchmarks need to specify at least one supported load and resource type for which scalability can be benchmarked.
 
 Load and resource types are described by a name (used for reference from an Execution) and a list of patchers.
+Patchers can be seen as functions, which take a value as input and modify a Kubernetes resource in a patcher-specific way. Examples of patchers are the *ReplicaPatcher*, which modifies the replica specification of a deployment, or the *EnvVarPatcher*, which modifies an environment variable.
+See the [patcher API reference](api-reference/patchers) for an overview of available patchers.
+
 If a benchmark is [executed by an Execution](running-benchmarks), these patchers are used to configure SUT and load generator according to the [load and resource values](creating-an-execution) set in the Execution.
 
 ## Kafka Configuration
@@ -116,6 +119,12 @@ Theodolite allows to automatically create and remove Kafka topics for each SLO e
 Use the `removeOnly: True` property for topics which are created automatically by the SUT.
 For those topics, also wildcards are allowed in the topic name.
 
+If no Kafka topics should be created, simply set:
+
+```yaml
+kafkaConfig: []
+```
+
 
 <!-- Further information: API Reference -->
 <!-- Further information: How to deploy -->
diff --git a/docs/running-benchmarks.md b/docs/running-benchmarks.md
index 7da1c7e5f8385a2818ae587b4c3ab3715a6c2bb2..0a76316c0515233f9445b363f941d60ab7aa0e06 100644
--- a/docs/running-benchmarks.md
+++ b/docs/running-benchmarks.md
@@ -143,7 +143,7 @@ The easiest way to use them is at MyBinder:
 
 Alternatively, you can also [run these notebook locally](https://github.com/cau-se/theodolite/tree/master/analysis), for example, with Docker or Visual Studio Code.
 
-The notebooks allow to compute a scalability function using its *demand* metric and to visualize multiple such functions in plots:
+The notebooks allow to compute a scalability function using Theodolite's *demand* metric and to visualize multiple such functions in plots:
 
 ### Computing the *demand* metric with `demand-metric.ipynb` (optional)