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new 4ebbc90c9 kie-kogito-examples-1974: Fix typos in
serverless-workflow-timeouts-showcase-operator-devprofile example readme file
(#1975)
4ebbc90c9 is described below
commit 4ebbc90c98420e81dd1e2c6d44ada443ec3aebf7
Author: Lubo Terifaj <[email protected]>
AuthorDate: Thu Jun 20 09:19:45 2024 +0200
kie-kogito-examples-1974: Fix typos in
serverless-workflow-timeouts-showcase-operator-devprofile example readme file
(#1975)
---
.../README.md | 6 +++---
1 file changed, 3 insertions(+), 3 deletions(-)
diff --git
a/serverless-workflow-examples/serverless-workflow-timeouts-showcase-operator-devprofile/README.md
b/serverless-workflow-examples/serverless-workflow-timeouts-showcase-operator-devprofile/README.md
index b5d75d040..7ff1f95e0 100644
---
a/serverless-workflow-examples/serverless-workflow-timeouts-showcase-operator-devprofile/README.md
+++
b/serverless-workflow-examples/serverless-workflow-timeouts-showcase-operator-devprofile/README.md
@@ -8,8 +8,8 @@
minikube start --cpus 4 --memory 10g --addons registry --addons metrics-server
--insecure-registry "10.0.0.0/24" --insecure-registry "localhost:5000"
```
-> **NOTE:** If the number of allocated cpus and memory configurations don't
feet well for your installation you can try to change this numbers.
-> However lower configuration might lead your cluster to get out of memmory.
Remember that every time you change this values, you will have to recreate your
instance.
+> **NOTE:** If the allocated cpus and memory configurations don't fit well for
your installation, you can try adjusting these numbers.
+> However, lower configurations might cause your cluster to run out of memory.
Remember that every time you change these values, you will have to recreate
your instance.
3. Be sure that the SonataFlow Operator is installed in your minikube.
@@ -39,7 +39,7 @@ kubectl apply -f
workflows/callback_state_timeouts_devprofile.yaml -n timeouts-s
> **NOTE:** In local environments, we recommend that you deploy the workflows
> one by one at the same time you verify that
> each deployment was successful. To do that, you can execute this command
> after each deployment, and you might have to
-> execute command several times until you see that the deployed workflow pod
is running successfully, since it might take
+> execute command several times until you see that the deployed workflow pod
is running successfully, as it might take
> some time to download the images used by the operator.
>
>
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