[airflow-site] branch master updated: docs: fix spelling (#356)

[po...@apache.org]

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potiuk pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/airflow-site.git


The following commit(s) were added to refs/heads/master by this push:
     new f8a6b5b  docs: fix spelling (#356)
f8a6b5b is described below

commit f8a6b5b65aa4381148d91956f99f38172f56d914
Author: John Bampton <jb...@users.noreply.github.com>
AuthorDate: Fri Dec 18 20:51:34 2020 +1000

    docs: fix spelling (#356)
---
 landing-pages/site/content/en/use-cases/experity.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/landing-pages/site/content/en/use-cases/experity.md b/landing-pages/site/content/en/use-cases/experity.md
index 7371ebd..d1c145e 100644
--- a/landing-pages/site/content/en/use-cases/experity.md
+++ b/landing-pages/site/content/en/use-cases/experity.md
@@ -11,7 +11,7 @@ logo: "experity-logo.jpg"
 We had to deploy our complex, flagship app to multiple nodes in multiple ways. This required tasks to communicate across Windows nodes and coordinate timing perfectly. We did not want to buy an expensive enterprise scheduling tool and needed ultimate flexibility.
 
 ##### How did Apache Airflow help to solve this problem?
-Ultimately we decided flexible, multi-node, DAG capable tooling was key and airflow was one of the few tools that fit that bill. Having it based on open source and python were large factors that upheld our core principles. At the time, Airflow was missing a windows hook and operator so we contributed the WinRM hook and operator back to the community. Given its flexibilty we also use DAG generators to have our metadata drive our DAGs and keep maintenance costs down.
+Ultimately we decided flexible, multi-node, DAG capable tooling was key and airflow was one of the few tools that fit that bill. Having it based on open source and python were large factors that upheld our core principles. At the time, Airflow was missing a windows hook and operator so we contributed the WinRM hook and operator back to the community. Given its flexibility we also use DAG generators to have our metadata drive our DAGs and keep maintenance costs down.
 
 ##### What are the results?
 We have a very flexible deployment framework that allows us to be as nimble as possible. The reliability is something we have grown to trust as long as we use the tool correctly. The scalability has also allowed us to decrease the time it takes to operate on our fleet of servers.