This guide provides you information about how to get started for on-prem as well as on cloud platforms like Google Cloud.
2.Google Cloud Marketplace
Dive Lite version is available on Google Cloud Marketplace. For on prem and/or other versions of the software please reach out to the support team.
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2.2.Tutorial Access on Google
Prerequisite: If you have completed the get-started session and received an email with your credentials and dive server instance IP address
Follow the below steps to access the system for On prem solution:
- On Windows OS, open putty.
- Enter the hostname or IP address that was sent to you in the email. (default port is 22 and connection type is SSH). Enter a session_name (for ex., Dive_platform) and click on save to save the session.
- On the left category sidebar, expand SSH. You will see options like below.
- Click on Auth. Click on Browse to upload your Private key file generated before.
- On the left category sidebar, click on Tunnels.
- Add source port as 3391(any port number) and destination port as localhost:3389 and click Add.
- On the left category sidebar, go to Session and click Save to save you settings.
- Select the saved session (Dive_platform) and click on Open at the bottom to open a tunneled connection to the server.
- When the login window prompts, enter the username that you received in the email and hit enter.
- Now you have successfully tunneled into the server.
- Open Remote Desktop Connection.
- Enter computer as localhost:3391 and hit connect.
- It will prompt for a login window like below. Enter your username and password that you received in the email and click ok.
- Now you are logged in into the server.
- You can start using the Dive Platform.
Note: Signup for trial version will require you to generate a private key to ssh into the platform. The below section will describe the steps to install Putty on windows machine and generate your private key. You can skip step I & II if you already have installed putty and generated a private key
- On Windows OS, you should download Putty to generate public and private keys.
- Go the link: https://www.chiark.greenend.org.uk/~sgtatham/putty/latest.html
- Scroll to Package files section. In MSI (‘Windows Installer’) choose which version of Windows OS (32-bit or 64-bit) you are using, and download the msi.
- Go to download folder and run the installer.msi.
- Click Next.
- Choose the destination folder for installing Putty. Click Next.
- Click Install.
- Click Yes when prompted.
- Click Finish when done. Putty is installed on your machine.
- Open PuTTYgen.
- Select Type of key to generate as RSA (default) and click on Generate.
- Move the mouse over the black area to generate randomness.
- Save your keys by clicking ‘Save public key’ as .txt file type and ‘Save private key’ as .ppk file type
Public key should be submitted for your account to create in the dive server.
Private key is used by you to login into the dive server.
- Login into dywhin.com with your username and password.
- Under Account tab, click on Enter Public_Key page.
- Open saved public key file.
- Copy the content in between the comment lines (highlighted area in above picture) and paste it in the Enter Public_Key page and click submit.
- You’re done.Thank You for submitting your public key. We will mail you shortly with the details and steps to login into dive server.
This section helps you to create/delete/recreate a service using Dive Manager. Services deployed uses the system resources and once the job is done end users can delete the service to release the system resources.
4.1.Create a Service
- Login into Dive Manager
- In Dive manager services tab, you can see Add button on top. To add a new service, click on Add.
- A new page will be loaded to add a new service configuration.
- You can select new in Add configuration option. Enter the service name and required options for the service and select the image for the service. Click on save service to start the service.
- Replica: Enter a number (minimum 1) for number of service instances to be created.
- Mount: Specify the target and source directories to mount for service data to persist.
- Network: Specify a network you want to use for the service.
- Ports: Specify the ports to be exposed (Host port:Service port)
- Once you click save service, service will be created and a message will be displayed.
- You can click on services side menu to view newly created services.
4.2.Delete a Service
- Login into Dive Manager
- On the services page, you can see the remove option next to the corresponding service. Click on the remove button to completely remove the service from the server.
- Click ok and a service removed message will be displayed and service will be removed.
4.3.Recreate a Service
- Login into Dive Manager
- At later point of time, if you want to recreate a new service with already existing configuration, click on the add button on the top of the page. Add service page will be opened.
- Click on Existing in add configuration option. Under services, select the previously configured service you want to use to create a new service.
- Once you select the service you want to re-use, the configuration will be loaded into the page.
- Enter a new service name, which doesn’t conflict with existing services and click save service. The new service will be created and running.
5.End to End data flow
The below sessions will provide you sample workflows that you can run to familiarize with the dive platform.
- Continuous build & deploy workflow is a sample flow that uses Jenkins engine to automate the build and deploy of an ETL workflow build in Apache Spark
- Model Services workflow uses the Dive Manager engine to publish a PMML formatted Machine Learning model built using Python and deployed as a web-service in Dive Platform
5.1.Continuous Build/Deploy Workflow
Prerequisite: Dive Platform installed with Continuous Build & Deploy services
1. Logging into Jenkins
- Url to open Jenkins is http://<ip>or<dns>. For ex., http://lokesh-dev.dywhin.com
- Default credentials to login into Jenkins is username: “****” and password is “*****”.
- By default, all the required plugins for the workflows are installed. If you want to install new plugins, you can install by going into “Manager Jenkins” > “Manage Plugins”
2. Configuring Jenkins to GitLab projects
2.1 Adding Credentials to Jenkins
- In Jenkins, credentials can be stored to use globally in all workflows and configurations.
- On the left sidebar, click on “Credentials” > “Jenkins” > “Global Credentails”.
- On the left sidebar, click on “Add Credentials”.
- You can add different types of credentials here. For ex., Username with password, GitLab API tokens, SSH username with private keys and certificates.
- Choose your kind and fill the required fields and click OK.
- You can use these credentials globally in Jenkins by identifying them with the ID or description.
2.2 Setting up GitLab API token and GitLab credentials
- Now, we will be setting up GitLab API token and GitLab credentials to use them in the workflows.
- Go to add credentials and select kind “GitLab API token” and enter API Token you saved when setting up GitLab environment. Enter a description and click OK.
- Similarly, store GitLab UI credentials. Click on add credentials and select kind “Username with Password” and enter username and password for GitLab URL in the fields and click OK.
- In the figure below, you can see GitLab API token and GitLab URL credentials.
2.3 Configuring Jenkins system to use GitLab projects
- Let’s assume you have created a project “KNIME” in GitLab already to create a workflow.
- On the left sidebar, click on “Manage Jenkins” and “Configure System”. Scroll down to GitLab section > GitLab connections.
- Enter the details in the Connection Name, GitLab host URL. In the credentials drop-down, choose GitLab API token stored in Global credentials section.
- Test connection if Jenkins is able to access GitLab project.
- You can add any number of GitLab connections connecting to different projects in GitLab and click save when done.
3. Setting up Workflows
- Click on “New Item” on the left sidebar. Enter a name for your workflow ex., KNIME and choose “Pipeline” project below and click ok. It will take you to workflow configuration page.
- In the configuration page, in general section under “GitLab connection” drop-down menu, choose the GitLab project URL (for “knime”).
- In “build triggers” section, select “Poll SCM”. You can schedule the workflow to run in this section. Let’s assume we are scheduling it to run every 5 minutes. Enter H/5 * * * *
- In advanced project options, under pipeline definition choose “Pipeline script from SCM”, under SCM drop-down menu select Git.
- Enter the “GitLab repository URL” and select corresponding “credentials” (ex., “GitLab URL credentials stored”) from the drop-down.
- You can choose any specific branch to build, default is master.
- In script path, add “Jenkinsfile”.
- Click save.
5.2.Deploy a model using Dive Manager
Prerequisite: Login into Dive Manager Application
PMML uses XML to represent mining models. The structure of the models is described by an XML Schema. One or more mining models can be contained in a PMML document
- Creates or updates a model.
- The request body is a PMML document.
- In this page we select model PMML file to be published .
- After submission the data is stored in database with selected parameter with the related values.
1.3 Create PMML Web service.
- Select PMML model and verify the same with given URL.
- We need check the web service URL using HTTP Requester plug-in in Firefox.
1.4 REST web service for scoring PMML models.
- Once published we can run web service using below URL on HTTP Requester.
- Evaluates data in “single prediction” mode.
- Response status codes:
200 OK. The evaluation was successful.
400 Bad Request. The evaluation failed permanently due to missing or invalid
404 Not Found. The requested model was not found.
500 Internal Server Error. The evaluation failed temporarily.
- Sample request: The request body is a JSON serialized form of an org object.
- We can embed the request in json file or paste the same in request body.
- Sample response:
- The response body is a JSON serialized form of an object.