From 3f52eec9eacf7f43435cc843a1986a0916134f8c Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?S=C3=B6ren=20Henning?= <soeren.henning@email.uni-kiel.de>
Date: Fri, 27 Nov 2020 14:50:25 +0100
Subject: [PATCH] Fix typos

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 README.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index a9de5f63d..8969a283d 100644
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@@ -11,9 +11,9 @@ Theodolite contains 4 application benchmarks, which are based on typical use cas
 
 ## 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 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 its 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).
+Theodolite's benchmarking method creates 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).
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