diff --git a/README.md b/README.md
index a38aa360f064078a970314543f05192f2df9af6b..6ad1dd576bc165630fb378234102f324f9b66d8a 100644
--- a/README.md
+++ b/README.md
@@ -2,4 +2,18 @@
 
 > A theodolite is a precision optical instrument for measuring angles between designated visible points in the horizontal and vertical planes.  -- <cite>[Wikipedia](https://en.wikipedia.org/wiki/Theodolite)</cite>
 
-Theodolite is a framework for benchmarking the horizontal and vertical scalability of stream processing engines.
+Theodolite is a framework for benchmarking the horizontal and vertical scalability of stream processing engines. It consists of three modules:
+
+## Theodolite Benchmarks
+
+Theodolite contains 4 application benchmarks, which are based on typical use cases for stream processing within microservices. For each benchmark, a corresponding workload generator is provided. Currently, this repository provides benchmark implementations for Kafka Streams.
+
+
+## Theodolite Execution Framework
+
+Theodolite aims to benchmark scalability of stream processing engines for real use cases. Microservices that apply stream processing techniques are usually deployed in elastic cloud environments. Hence, Theodolite's cloud-native benchmarking framework deploys as components in a cloud environment, orchestrated by Kubernetes. More information on how to execute scalability benchmarks can be found in [Thedolite execution framework](execution).
+
+
+## Theodolite Analysis Tools
+
+Theodolite's benchmarking method create a *scalability graph* allowing to draw conclusions about the scalability of a stream processing engine or its deployment. A scalability graph shows how resource demand evolves with an increasing workload. Theodolite provides Jupyter notebooks for creating such scalability graphs based on benchmarking results from the execution framework. More information can be found in [Theodolite analysis tool](analysis).
diff --git a/analysis/README.md b/analysis/README.md
index 5318425825a51b4ab118bb1c6c11dfc92037c6a1..263b1db16fcabefe5409ebe744afe5997bc90d89 100644
--- a/analysis/README.md
+++ b/analysis/README.md
@@ -17,6 +17,6 @@ Python libraries, which can be installed via:
 pip install -r requirements.txt 
 ```
 
- We have tested these
+We have tested these
 notebooks with [Visual Studio Code](https://code.visualstudio.com/docs/python/jupyter-support),
 however, every other server should be fine as well.
diff --git a/execution/README.md b/execution/README.md
index 42fe9647d11daf16cfb50d91da1af8b72d9abf5d..7b914e4ece1b3bb21c3637c37865027ce5f672fa 100644
--- a/execution/README.md
+++ b/execution/README.md
@@ -95,7 +95,15 @@ kubectl apply -f infrastructure/kafka/service-monitor.yaml
 
 ##### Other options for Kafka
 
-Other Kafka deployments, for example, using Strimzi, should work in similiar way.
+Other Kafka deployments, for example, using Strimzi, should work in a similar way.
+
+#### A Kafka Client Pod
+
+A permanently running pod used for Kafka configuration is started via:
+
+```sh
+kubectl apply -f infrastructure/kafka/kafka-client.yaml 
+```
 
 #### The Kafka Lag Exporter
 
diff --git a/execution/infrastructure/kafka/kafka-client.yaml b/execution/infrastructure/kafka/kafka-client.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..4c7d3ed239faed62022c110e92b264b338a8c9a4
--- /dev/null
+++ b/execution/infrastructure/kafka/kafka-client.yaml
@@ -0,0 +1,12 @@
+apiVersion: v1
+kind: Pod
+metadata:
+  name: kafka-client-2
+spec:
+  containers:
+  - name: kafka-client
+    image: confluentinc/cp-enterprise-kafka:5.4.0
+    command:
+      - sh
+      - -c
+      - "exec tail -f /dev/null"
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