fix the last of the commands

Author: dfangl

content/en/docs/Integrations/aws-cli/index.md

@@ -13,38 +13,37 @@ All CLI commands that access [services that are implemented in LocalStack]({{< r
 There are two ways to use the CLI:
 
 * Use our `awslocal` drop-in replacement:
-  ```
-  awslocal kinesis list-streams
-  ```
+  {{< command >}}
+  $ awslocal kinesis list-streams
+  {{< / command >}}
 * Configure AWS test environment variables and add the `--endpoint-url=<localstack-url>` flag to your `aws` CLI invocations.
   For example:
-  ```
-  export AWS_ACCESS_KEY_ID="test"
-  export AWS_SECRET_ACCESS_KEY="test"
-  export AWS_DEFAULT_REGION="us-east-1"
+  {{< command >}}
+  $ export AWS_ACCESS_KEY_ID="test"
+  $ export AWS_SECRET_ACCESS_KEY="test"
+  $ export AWS_DEFAULT_REGION="us-east-1"
 
-  aws --endpoint-url=http://localhost:4566 kinesis list-streams
-  ```
+  $ aws --endpoint-url=http://localhost:4566 kinesis list-streams
+  {{< / command >}}
 
 ## AWS CLI
 
 Use the below command to install `aws`, if not installed already.
 
-```
-pip install awscli
-```
+{{< command >}}
+$ pip install awscli
+{{< / command >}}
 
 ### Setting up local region and credentials to run LocalStack
 
 aws requires the region and the credentials to be set in order to run the aws commands.
 Create the default configuration and the credentials.
 Below key will ask for the Access key id, secret Access Key, region & output format.
+Config & credential file will be created under ~/.aws folder
 
-```
-aws configure --profile default
-
-# Config & credential file will be created under ~/.aws folder
-```
+{{< command >}}
+$ aws configure --profile default
+{{< / command >}}
 
 {{< alert >}}
 **Note** Please use `test` as value for AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY to make pre-signed URLs for S3 buckets work.

content/en/docs/Integrations/pulumi/index.md

@@ -22,10 +22,10 @@ This guide follows the instructions from Pulumi's [Get Started with Pulumi and A
 
 First, run the following commands and follow the instructions in the CLI to create a new project.
 
-```
-mkdir quickstart && cd quickstart
-pulumi new aws-typescript
-```
+{{< command >}}
+$ mkdir quickstart && cd quickstart
+$ pulumi new aws-typescript
+{{< / command >}}
 
 We use the default configuration values:
 

content/en/docs/Integrations/spring-cloud-function/index.md

@@ -79,16 +79,16 @@ install the Gradle build tool on your machine.
 
 Then run the following command to initialize a new Gradle project
 
-```shell
-gradle init
-```
+{{< command >}}
+$ gradle init
+{{< / command >}}
 
 After initialization, you will find the Gradle wrapper script `gradlew`.
 From now on, we will use the wrapper instead of the globally installed Gradle binary:
 
-```
-./gradlew <command>
-```
+{{< command >}}
+$ ./gradlew <command>
+{{< / command >}}
 
 ### Project Settings
 

content/en/docs/Local AWS Services/elastic-container-registry/index.md

@@ -8,8 +8,8 @@ description: >
 
 A basic version of Elastic Container Registry (ECR) is available to store application images. ECR is often used in combination with other APIs that deploy containerized apps, like ECS or EKS.
 
-```
-$ awslocal ecr create-repository --repository-name repo1
+{{< command >}}
+$ $ awslocal ecr create-repository --repository-name repo1
 {
     "repository": {
         "repositoryArn": "arn:aws:ecr:us-east-1:000000000000:repository/repo1",
@@ -18,10 +18,10 @@ $ awslocal ecr create-repository --repository-name repo1
         "repositoryUri": "localhost:4510/repo1"
     }
 }
-```
+{{< / command >}}
 
 You can then build and tag a new Docker image, and push it to the repository URL (`localhost:4510/repo1` in the example above):
-```
+{{< command >}}
 $ cat Dockerfile
 FROM nginx
 ENV foo=bar
@@ -36,4 +36,4 @@ fe08d5d042ab: Pushed
 f2cb0ecef392: Pushed
 latest: digest: sha256:4dd893a43df24c8f779a5ab343b7ef172fb147c69ed5e1278d95b97fe0f584a5 size: 948
 ...
-```
+{{< / command >}}

content/en/docs/Local AWS Services/elastic-kubernetes-service/index.md

@@ -12,7 +12,7 @@ Please note that EKS requires an existing local Kubernetes installation. In rece
 ![Kubernetes in Docker](kubernetes.png)
 
 The example below illustrates how to create an EKS cluster configuration (assuming you have [`awslocal`](https://github.com/localstack/awscli-local) installed):
-```
+{{< command >}}
 $ awslocal eks create-cluster --name cluster1 --role-arn r1 --resources-vpc-config '{}'
 {
     "cluster": {
@@ -30,5 +30,5 @@ $ awslocal eks list-clusters
         "cluster1"
     ]
 }
-```
+{{< / command >}}
 Simply configure your Kubernetes client (e.g., `kubectl` or other SDK) to point to the `endpoint` specified in the `create-cluster` output above. Depending on whether you're calling the Kubernetes API from the local machine or from within a Lambda, you may have to use different endpoint URLs (`https://localhost:6443` vs `https://172.17.0.1:6443`).

content/en/docs/Local AWS Services/elastic-mapreduce/index.md

@@ -9,12 +9,12 @@ description: >
 LocalStack Pro allows running data analytics workloads locally via the [EMR](https://aws.amazon.com/emr) API. EMR utilizes various tools in the [Hadoop](https://hadoop.apache.org/) and [Spark](https://spark.apache.org) ecosystem, and your EMR instance is automatically configured to connect seamlessly to the LocalStack S3 API.
 
 To create a virtual EMR cluster locally from the command line (assuming you have [`awslocal`](https://github.com/localstack/awscli-local) installed):
-```
+{{< command >}}
 $ awslocal emr create-cluster --release-label emr-5.9.0 --instance-groups InstanceGroupType=MASTER,InstanceCount=1,InstanceType=m4.large InstanceGroupType=CORE,InstanceCount=1,InstanceType=m4.large
 {
     "ClusterId": "j-A2KF3EKLAOWRI"
 }
-```
+{{< / command >}}
 
 The commmand above will spin up one more more Docker containers on your local machine that can be used to run analytics workloads using Spark, Hadoop, Pig, and other tools.
 

content/en/docs/Local AWS Services/elasticache/index.md

@@ -9,7 +9,7 @@ description: >
 A basic version of [ElastiCache](https://aws.amazon.com/elasticache/) is provided. By default, the API is started on http://localhost:4598 and supports running a local Redis instance (Memcached support coming soon).
 
 After starting LocalStack Pro, you can test the following commands:
-```
+{{< command >}}
 $ awslocal elasticache create-cache-cluster --cache-cluster-id i1
 {
     "CacheCluster": {
@@ -20,14 +20,14 @@ $ awslocal elasticache create-cache-cluster --cache-cluster-id i1
         }
     }
 }
-```
+{{< / command >}}
 
 Then use the returned port number (`4530`) to connect to the Redis instance:
-```
+{{< command >}}
 $ redis-cli -p 4530 ping
 PONG
 $ redis-cli -p 4530 set foo bar
 OK
 $ redis-cli -p 4530 get foo
 "bar"
-```
+{{< / command >}}

content/en/docs/Local AWS Services/glue/index.md

@@ -15,7 +15,7 @@ In order to run Glue jobs, some additional dependencies have to be fetched from
 ## Creating Databases and Table Metadata
 
 The commands below illustrate the creation of some very basic entries (databases, tables) in the Glue data catalog:
-```
+{{< command >}}
 $ awslocal glue create-database --database-input '{"Name":"db1"}'
 $ awslocal glue create-table --database db1 --table-input '{"Name":"table1"}'
 $ awslocal glue get-tables --database db1
@@ -27,30 +27,30 @@ $ awslocal glue get-tables --database db1
         }
     ]
 }
-```
+{{< / command >}}
 
 ## Running Scripts with Scala and PySpark
 
 Assuming we would like to deploy a simple PySpark script `job.py` in the local folder, we can first copy the script to an S3 bucket:
-```
+{{< command >}}
 $ awslocal s3 mb s3://glue-test
 $ awslocal s3 cp job.py s3://glue-test/job.py
-```
+{{< / command >}}
 
 Next, we can create a job definition:
-```
+{{< command >}}
 $ awslocal glue create-job --name job1 --role r1 \
   --command '{"Name": "pythonshell", "ScriptLocation": "s3://glue-test/job.py"}'
-```
+{{< / command >}}
 ... and finally start the job:
-```
+{{< command >}}
 $ awslocal glue start-job-run --job-name job1
 {
     "JobRunId": "733b76d0"
 }
-```
+{{< / command >}}
 The returned `JobRunId` can be used to query the status job the job execution, until it becomes `SUCCEEDED`:
-```
+{{< command >}}
 $ awslocal glue get-job-run --job-name job1 --run-id 733b76d0
 {
     "JobRun": {
@@ -59,7 +59,7 @@ $ awslocal glue get-job-run --job-name job1 --run-id 733b76d0
         "JobRunState": "SUCCEEDED"
     }
 }
-```
+{{< / command >}}
 
 For a more detailed example illustrating how to run a local Glue PySpark job, please refer to this [sample repository](https://github.com/localstack/localstack-pro-samples/tree/master/glue-etl-jobs).
 
@@ -75,12 +75,12 @@ CREATE EXTERNAL TABLE db2.table2 (a1 Date, a2 STRING, a3 INT) LOCATION 's3://tes
 ```
 
 Then this command will import these DB/table definitions into the Glue data catalog:
-```
+{{< command >}}
 $ awslocal glue import-catalog-to-glue
-```
+{{< / command >}}
 
 ... and finally they will be available in Glue:
-```
+{{< command >}}
 $ awslocal glue get-databases
 {
     "DatabaseList": [
@@ -112,7 +112,7 @@ $ awslocal glue get-tables --database-name db2
         }
     ]
 }
-```
+{{< / command >}}
 
 ## Further Reading
 

content/en/docs/Local AWS Services/iam/index.md

@@ -14,7 +14,7 @@ The environment configuration `ENFORCE_IAM=1` is required to enable this feature
 {{< /alert >}}
 
 Below is a simple example that illustrates the use of IAM policy enforcement. It first attempts to create an S3 bucket with the default user (which fails), then create a user and attempts to create a bucket with that user (which fails again), and then finally attaches a policy to the user to allow `s3:CreateBucket`, which allows the bucket to be created.
-```
+{{< command >}}
 $ awslocal s3 mb s3://test
 make_bucket failed: s3://test An error occurred (AccessDeniedException) when calling the CreateBucket operation: Access to the specified resource is denied
 $ awslocal iam create-user --user-name test
@@ -32,7 +32,7 @@ $ awslocal iam create-policy --policy-name p1 --policy-document '{"Version":"201
 $ awslocal iam attach-user-policy --user-name test --policy-arn arn:aws:iam::000000000000:policy/p1
 $ awslocal s3 mb s3://test
 make_bucket: test
-```
+{{< / command >}}
 
 ### Supported APIs
 

content/en/docs/Local AWS Services/iot/index.md

@@ -9,12 +9,12 @@ description: >
 Basic support for [IoT](https://aws.amazon.com/iot/) (including IoT Analytics, IoT Data, and related APIs) is provided in the Pro version. The main endpoints for creating and updating entities are currently implemented, as well as the CloudFormation integrations for creating them.
 
 The IoT API ships with a built-in MQTT message broker. In order to get the MQTT endpoint, the `describe-endpoint` API can be used; for example, using [`awslocal`](https://github.com/localstack/awscli-local):
-```
+{{< command >}}
 $ awslocal iot describe-endpoint
 {
     "endpointAddress": "localhost:4520"
 }
-```
+{{< / command >}}
 
 This endpoint can then be used with any MQTT client to send/receive messages (e.g., using the endpoint URL `mqtt://localhost:4520`).