Documentation updates

Author: arieleeuw

core/sfc-core/src/main/kotlin/com/amazonaws/sfc/data/InProcessSourcesReader.kt

@@ -93,8 +93,8 @@ class InProcessSourcesReader(
     }
 
     companion object {
-        /**A
-         * Creates a in process reader from configuration data
+        /**
+         * Creates an in process reader from configuration data
          * @param schedule ScheduleConfiguration schedule
          * @param adapter ProtocolAdapter
          * @param sources Mapping<String, ArrayList<String>> sources with channels to read

docs/README.md

@@ -362,7 +362,7 @@ described above, for target data without changes to the actual end targets.
 ## High availability
 
 All SFC components that can run as microservices in their own processes can be configured to have an endpoint for
-handling [health endpoints](./sfc-health-endpoints). Mechanisms used to manage the service instances, (e.g., Docker Compose, Kubernetes) can use
+handling [health endpoints](./sfc-health-endpoints.md). Mechanisms used to manage the service instances, (e.g., Docker Compose, Kubernetes) can use
 these endpoints in their configuration to check the status of a service and recycle instances failing to respond to the
 health probe requests. This approach can help ensure the reliability and availability of microservices-based systems.
 

docs/adapters/nats.md

@@ -638,7 +638,7 @@ If a Password is configured then the Username must be configured as well.
 While authentication restricts the number of clients that can connect, TLS can be employed to encrypt traffic between the client and server, verifying the server's identity. Furthermore, in the most secure version of TLS (NATS), the server can be configured to verify the client's identity, thereby authenticating it. Upon initiating TLS mode, a nats-server will mandate that all clients connect using TLS.
 Additionally, if configured to utilize TLS, client libraries will fail to establish connections to servers without TLS.
 
-**Type**: [CertificateConfiguration](../core/certificate-configuration)
+**Type**: [CertificateConfiguration](../core/certificate-configuration.md)
 
 
 https://docs.nats.io/using-nats/developer/connecting/tls

docs/adapters/pccc.md

@@ -372,7 +372,7 @@ The PcccSourceConfiguration class defines which values (channels) to read from a
 
 ### AdapterController
 
-The AdapterController property specifies the server identifier for the PLC controller to read from. This identifier must match a controller defined in the Controllers section of the PCCC adapter configuration referenced by the source's [ProtocolAdapter](../core/source-configuration#protocoladapter) attribute.
+The AdapterController property specifies the server identifier for the PLC controller to read from. This identifier must match a controller defined in the Controllers section of the PCCC adapter configuration referenced by the source's [ProtocolAdapter](../core/source-configuration.md#protocoladapter) attribute.
 
 **Type** : String
 

docs/core/channel-configuration.md

@@ -49,7 +49,7 @@ The ChangeFilter property specifies a reference to a [change filter](./change-fi
 
 ---
 ### ConditionFilter
-The ConditionFilter property specifies a reference to a [condition filter](./condition-filter-configuration) that should be applied to the channel's values. It accepts a string value that must match an ID of a filter defined in the [ConditionFilters](./sfc-configuration.md#conditionfilters)  section of the top-level SFC configuration. This filter evaluates whether values should be processed based on specified conditions. The property is optional - if not specified, no condition filtering will be applied to the channel. This allows for selective processing of values based on defined conditions.
+The ConditionFilter property specifies a reference to a [condition filter](./condition-filter-configuration.md) that should be applied to the channel's values. It accepts a string value that must match an ID of a filter defined in the [ConditionFilters](./sfc-configuration.md#conditionfilters)  section of the top-level SFC configuration. This filter evaluates whether values should be processed based on specified conditions. The property is optional - if not specified, no condition filtering will be applied to the channel. This allows for selective processing of values based on defined conditions.
 
 **Type**: String
 

docs/core/schedule-configuration.md

@@ -52,7 +52,7 @@ Default is 1000
 
 ### Metadata
 
-Optional key-value pairs that add contextual information to the schedule's output data. When specified, these metadata values are included at the schedule level and can be customized using the [ElementNames](sfc-configuration#elementnames) configuration's Metadata entry
+Optional key-value pairs that add contextual information to the schedule's output data. When specified, these metadata values are included at the schedule level and can be customized using the [ElementNames](./sfc-configuration.md#elementnames) configuration's Metadata entry
 
 **Type**: Map[String, String]
 

docs/examples/README.md

@@ -26,7 +26,7 @@ Adapters
 
 Configuration
 - [Contextualization & Filter Demo](../../examples/opcua-to-iot-using-filters/README.md)
-- [Configuration Signing](../../examples/sign-sfc-config)
+- [Configuration Signing](../../examples/sign-sfc-config/README.md)
 - [Custom Config Provider Template](../../examples/custom-config-provider/README.md)
 - [Custom User Interface and API Config Provider](../../examples/custom-api-ui-config-provider/README.md)
 - [J1939 DBC file](../../examples/j1939dbc/README.md)

examples/greengrass-in-process/README.md

@@ -77,7 +77,7 @@ aws greengrassv2 get-component \
 ```
 >Note! <br> This permission set is too open for production and should be reduced. It is used here only for simplicity!
 
-5. Furthermore we assume you have the ability to run the following docker container for testing the setup in your Greengrass environment:
+5. Furthermore, we assume you have the ability to run the following docker container for testing the setup in your Greengrass environment:
 
 ```sh
 docker run -d -p 4840:4840 ghcr.io/umati/sample-server:main
@@ -96,7 +96,7 @@ The complete setup will create components for the SFC modules:
 - aws-iot-mqtt-target
 - opcua
 
-**The setup will configure all modules to be started in SFC's [`in-process mode`](../README.md#in-process-and-ipc-deployment-models)**. That means that all SFC modules run inside the sfc-main process on a single host.
+**The setup will configure all modules to be started in SFC's [`in-process mode`](../../docs/sfc-running-adapters.md#running-protocol-adapters-in-process)**. That means that all SFC modules run inside the sfc-main process on a single host.
 
 >Note! <br>
 If you have previously installed the modules in SFC's IPC mode   you must remove the components from IOT CORE and from your Greengrass deployment! 
@@ -139,7 +139,7 @@ You should see now the following directory structure:
 ![Working directory structure with downloaded modules](img/directory_structure1.png "working directory structure with downloaded modules")
 
 
-## Step 3: Creating Greengrass recipes 
+## Step 3: Creating Greengrass recipes
 Now we create the recipes for the sfc modules. Execute the following command:
 
 ```sh
@@ -197,7 +197,7 @@ Now copy the following content into the file **~/environment/GreengrassSFC/recip
 
 ``` 
 
->Note! <br> Replace the placeholder ***[REPLACE WITH YOUR S3 BUCKET]*** with an S3 bucket name where you want later to store your Greengrass components artifacts and recepies! 
+>Note! <br> Replace the placeholder ***[REPLACE WITH YOUR S3 BUCKET]*** with an S3 bucket name where you want later to store your Greengrass components artifacts and recepes! 
 
 
 Now copy the following content into the file **~/environment/GreengrassSFC/recipes/com.amazon.sfc.aws-s3-target-1.0.0.json**:
@@ -245,7 +245,7 @@ Now copy the following content into the file **~/environment/GreengrassSFC/recip
 
 ```
 
->Note! <br> Replace the placeholder ***[REPLACE WITH YOUR S3 BUCKET]*** with an S3 bucket name where you want later to store your Greengrass components artifacts and recepies! 
+>Note! <br> Replace the placeholder ***[REPLACE WITH YOUR S3 BUCKET]*** with an S3 bucket name where you want later to store your Greengrass components artifacts and recepes! 
 
 Now copy the following content into the file **~/environment/GreengrassSFC/recipes/com.amazon.sfc.debug-target-1.0.0.json**:
 ```json
@@ -291,7 +291,7 @@ Now copy the following content into the file **~/environment/GreengrassSFC/recip
 }
 
 ```
->Note! <br> Replace the placeholder ***[REPLACE WITH YOUR S3 BUCKET]*** with an S3 bucket name where you want later to store your Greengrass components artifacts and recepies! 
+>Note! <br> Replace the placeholder ***[REPLACE WITH YOUR S3 BUCKET]*** with an S3 bucket name where you want later to store your Greengrass components artifacts and recepes! 
 
 Now copy the following content into the file **~/environment/GreengrassSFC/recipes/com.amazon.sfc.opcua-1.0.0.json**:
 ```json
@@ -337,7 +337,7 @@ Now copy the following content into the file **~/environment/GreengrassSFC/recip
 }
 
 ```
->Note! <br> Replace the placeholder ***[REPLACE WITH YOUR S3 BUCKET]*** with an S3 bucket name where you want later to store your Greengrass components artifacts and recepies! 
+>Note! <br> Replace the placeholder ***[REPLACE WITH YOUR S3 BUCKET]*** with an S3 bucket name where you want later to store your Greengrass components artifacts and recepes! 
 
 Now copy the following content into the file **~/environment/GreengrassSFC/recipes/com.amazon.sfc.sfc-main-1.0.0.json**:
 
@@ -568,7 +568,7 @@ Now copy the following content into the file **~/environment/GreengrassSFC/recip
 ```
 >Note! <br>
  1. Make sure that after copying the script into the file that the line with the **"Script": "printf '{configuration:/SFC_CONFIG_JSON}' > {artifacts:path}/conf.json && {artifacts:path}/sfc-main/bin/sfc-main -config {artifacts:path}/conf.json""** has the ticks (') and not the less than character (**<**) as some markup viewer replace the (**'**) with (**<**).  
- 2. Replace the placeholder ***[REPLACE WITH YOUR S3 BUCKET]*** with an S3 bucket name where you want later to store your Greengrass components artifacts and recepies!
+ 2. Replace the placeholder ***[REPLACE WITH YOUR S3 BUCKET]*** with an S3 bucket name where you want later to store your Greengrass components artifacts and recepes!
 
  3. Replace the placeholder ***[REPLACE WITH YOUR S3 BUCKET FOR OPCUA DATA]*** with an S3 bucket name and ***[AWS BUCKET REGION]*** with the AWS region where you want to store the data collected from the OPCUA server!
 
@@ -632,7 +632,7 @@ Component Name: com.amazon.sfc.sfc-main
 ```
 
 >Notice: <br>
-Because we use [`in process model`](../../docs#in-process-and-ipc-deployment-models) the components on which sfc-main depends only unpack the the modules during deployment and do not start a process. So they report State: *Finished*. <br>
+Because we use [`in process model`](../../docs/sfc-running-adapters.md#running-protocol-adapters-in-process) the components on which sfc-main depends only unpack the modules during deployment and do not start a process. So they report State: *Finished*. <br>
 The component sfc-main is the only component which actually start a process and keeps running.
 
 >Note! <br>
@@ -647,11 +647,11 @@ sudo /greengrass/v2/bin/greengrass-cli deployment create --remove "com.amazon.sf
 
 >Note! <br>
 If you had not started the OPCUA test docker container before deploying the sfc-main component you will see in the **/greengrass/v2/logscom.amazon.sfc.sfc-main.log** the following error code which you can ignore: <br>
-*ERROR - Error creating client for for source "OPCUA-SOURCE" at  opc.tcp://localhost:4840//, Connection refused: localhost/127.0.0.1:4840*. 
+*ERROR - Error creating client for source "OPCUA-SOURCE" at  opc.tcp://localhost:4840//, Connection refused: localhost/127.0.0.1:4840*. 
 
 
 ## Step 5: Testing the deployment
-To test the deployment we have to start the docker container with the test OPCUA server. Do do this use the following command:
+To test the deployment we have to start the docker container with the test OPCUA server. Do this use the following command:
 
 ```bash
 docker run -d -p 4840:4840 ghcr.io/umati/sample-server:main
@@ -705,7 +705,7 @@ For that open the **IOT Core web console** and select **MQTT test client**.
 
 ![](img/MQTT_test_client.png "AWS IOT Core MQTT Test Client")
 
-You should be able to see messages beeing received.
+You should be able to see messages being received.
 
 ## Step 6: Remove the local deployment
 After successful testing we remove the deployment which was done locally with the following command:
@@ -716,7 +716,7 @@ sudo /greengrass/v2/bin/greengrass-cli deployment create --remove "com.amazon.sf
 
 
 ## Step 7: Publish the components
-To publish these these components make one more time sure that you have replaced the ***[REPLACE WITH YOUR S3 BUCKET]*** placeholder with the S3 bucket where you want to upload the components in all recipes!
+To publish these components make one more time sure that you have replaced the ***[REPLACE WITH YOUR S3 BUCKET]*** placeholder with the S3 bucket where you want to upload the components in all recipes!
 
 Upload all artifacts and recipies to S3 with the following command:
 
@@ -817,7 +817,7 @@ Because we used SFC's `in-process` model all components which deploy the depende
 # Removing components from deployment and deleting components
 ## Remove SFC components from deployment
 
-To remove the components from the Greengrass environemnt do the following steps:
+To remove the components from the Greengrass environment do the following steps:
 
 1. Go to the AWS IoT Core web console and select **Greengrass devices** then select **Deployments** then check the box before your deployment then select **Revise** 
 
@@ -866,7 +866,7 @@ To delete the components from IOT Core do the following steps:
 - com.amazon.sfc.opcua
 - com.amazon.sfc.aws-s3-target
 - com.amazon.sfc.aws-iot-mqtt-target
-- com-amazon.svf.debug-tagret
+- com-amazon.svf.debug-target
 
 
 [Examples](../../docs/examples/README.md)