1. Introduction

This Chapter contains a short introduction about Techila Distributed Computing Engine and also describes the purpose of this document.

1.1. Techila Distributed Computing Engine

Techila Distributed Computing Engine is a distributed computing middleware and management solution that brings an on-demand supercomputer to every desk. The solution is designed to save the time of users and IT experts, to solve challenges related to parallel application development and deployment, and to speed up the idea-to-deployment cycle.

The solution, available in Google Cloud Platform Marketplace, uses Techila Distributed Computing Engine’s secure technology to integrate the scalable power of Google Cloud Platform seamlessly into MATLAB, R programming language, Python and other popular tools on your own PC. This brings rocket speed to simulation and analysis, without the complexity of traditional high-performance computing.

Techila Distributed Computing Engine in Google Cloud Platform Marketplace makes getting rocket speed to computing easier than ever. Google Cloud Platform Marketplace sets up Techila Distributed Computing Engine with just a couple of mouse clicks and the Techila Configuration Wizard allows you to adjust the system’s throughput with simplicity. Techila Distributed Computing Engine in Google Cloud Platform Marketplace allows you to benefit from rocket speed computing whenever you need it, wherever you need it.

1.2. What is This Document

This document is a guide for persons who are planning to set up Techila Distributed Computing Engine in Google Cloud Platform environment using the Techila Distributed Computing Engine in Google Cloud Platform Marketplace.

If you are unfamiliar with the Techila Distributed Computing Engine terminology used in this document, please refer to Introduction to Techila Distributed Computing Engine.

Screenshots and dialogs in this document are from Microsoft Windows 10. Depending on your operating system, the appearance of screens might be different. The structure of this document is as follows:

Overview gives an overview about system requirements and how billing is affected by different deployment activities.

Configuring and Managing the Techila Distributed Computing Environment contains step-by-step instructions on how to setup and test a Techila Distributed Computing Engine environment in Google Cloud Platform.

2. Overview

This Chapter contains an overview of the deployment of Techila Distributed Computing Engine.

Note! To use Techila Distributed Computing Engine in Google Cloud Platform Marketplace, you need to have billing for your Google Cloud Platform account set up. If you are using the free trial, Google creates a billing account for you and stores your credits to that billing account. More information about the billing account and free trial can be found here:

The flowchart in Overview contains documentation pointers, which indicate where you can find more information about the described activity. The documentation pointers have been noted using the following shapes:
chapterxy

These notations refer to Chapters in this document. For example, when you see the following notation, it means that you can find more information about the activity in Chapter 3.1 of this document.
chapter31

2.1. System Requirements

In order to perform computations in the Techila distributed computing environment, your workstation must meet certain programming language specific requirements. These requirements are described in the table below.

Table 1. System Requirements
Programming Language Supported Versions Additional Requirements Required Operating System

R

3.4.3 64-bit

Java Development Kit (JDK) or Java Runtime Environment (JRE) (version 6 or newer)

Microsoft Windows OR Linux

Python

2.7.11 64-bit,
3.5.1 64-bit

MATLAB

2012b-2017b, 64-bit

- MATLAB Compiler Toolbox
- C-compiler compatible with your MATLAB Compiler

Example 1: If you wish to perform R computations in Techila Distributed Computing Engine, your own workstation must be running either a Microsoft Windows or Linux operating system. Additionally, your own workstation must have JDK or JRE (version 6 or newer) available. Computations will be performed on the Techila Workers using 3.4.3 64-bit. If the R you have installed on your workstations is also 3.4.3 64-bit, then computations can be created without additional configuration steps. If you are using a different R version on your own workstation, then you can still use the system, but you will need to create an additional environment variable as described here.

Example 2: If you wish to perform Python computations in Techila Distributed Computing Engine, your own workstation must be running either a Microsoft Windows or Linux operating system. Additionally, your own workstation must have JDK or JRE (version 6 or newer) available. Computations will be performed on the Techila Workers using 2.7.11 64-bit or 3.5.1 64-bit, depending on whether you are using Python 2 or 3. If the Python you have installed on your workstations matches the Python version available in Google Cloud Platform Marketplace, then computations can be created without additional configuration steps. If you are using a different Python version on your own workstation, then you can still use the system, but you will need to create an additional environment variable as described here.

Example 3: If you wish to perform MATLAB computations in Techila Distributed Computing Engine, your own workstation must be running either a Microsoft Windows or Linux operating system. Additionally, your own workstation must have one of the supported MATLAB versions (2012b-2017b, 64-bit). A separate Java installation is not required on your workstation.

2.2. Billing States

A common question among users is: When does the billing for the service start?

The flowchart in the below image contains a high level overview of the deployment process and billing in different stages. Techila Technologies does not take any responsibility and is not liable for possible inaccurate or outdated information related to other than Techila Server image fee or Techila Worker image fee. More information about setting up billing can be found here.

billing

3. Configuring and Managing the Techila Distributed Computing Environment

This Chapter contains instructions how to manage and configure the Techila distributed computing environment. Instructions are provided for all steps including starting, testing and deleting the VM instances.

3.1. Starting the Techila Server

This Chapter contains instructions on how to start the Techila Server by using Google Cloud Platform Marketplace.

  1. Using your web browser, navigate to Google Cloud Platform Marketplace page:

  2. Click on Explore Marketplace

    selmarket
  3. Type Techila in the search box and click on the matching search result.

    image6
  4. Click the Launch on Google Cloud Platform button to continue.

    image7
  5. After clicking the launch button, a new page will be displayed. The appearance of this page will depend on whether or not billing has been setup for your Google Cloud Platform account.

    If billing has already been setup for your Google Cloud Platform account, please continue from Step 5.

    If billing has not been setup on your Google Cloud Platform account, you might receive a page offering a free trial as illustrated below.

    image8

    In this case, you will either need to apply for the free trial or setup billing for your Google Cloud Platform account. Instructions for setting up billing can be found on the following website:

    After billing has been setup for your Google Cloud Platform account, you will be able to proceed with the Techila Distributed Computing Engine setup as described in the following steps.

  6. In order to deploy the Techila distributed computing environment, you will either need to create a new or choose an existing Google Cloud Platform project. This Google Cloud Platform project will contain all Techila resources created during the deployment. For the sake of clarity, a new project will be created in the steps described in this document.

    Enter a descriptive name for the project (e.g. techilacomputing) and click the Create button to create the project.

    image9

    Please note that creating the project may take several minutes. While the project is being created, your view should resemble the one shown below.

    image10
  7. After the project has been created, define a name for the deployment and select a geographical Zone where you want to have the system deployed. The Machine type dropdown menu can be used to select a different VM instance type for the Techila Server, but this is not required (the default 'n1-standard-4' will be sufficient). If you change the VM instance type, please make sure that you do not choose a VM instance type that exceeds your CPU quota.

    Note! It is good practice to choose a geographical zone that is close to your computer’s location. This will help reduce the network latency between your computer and the Techila Server. More information about Zones can be found at:

    Click the Deploy button to start the deployment process.

    Please note that the deployment process will take several minutes.

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  8. Wait for the deployment to complete. During the deployment, your view should resemble the one shown below.

    image12
  9. After the deployment has been completed, a message stating Your Techila Distributed Computing deployment is ready will be displayed.

    Note! When starting the deployment process, a deployment with a matching name was automatically created to your Google Cloud Platform environment. This deployment can be viewed in the Deployment Manager view in the Google Cloud Platform portal. Only delete the deployment if you wish to discontinue your Techila Distributed Computing Engine usage. If you delete the deployment, all network configurations, computational data and user credentials will be deleted, meaning you will not be able to restart the Techila Server successfully.

    Please continue from Accessing the Techila Configuration Wizard from the Post Deployment Page, which describes how you can log in to the Techila Configuration Wizard for the first time.

    image13

3.2. Accessing the Techila Configuration Wizard from the Post Deployment Page

This Chapter contains instructions on how you can log in to the Techila Configuration Wizard from the post deployment page, after starting the Techila Server for the first time.

Please note that the steps in this Chapter assume that you are accessing the Techila Configuration Wizard for the first time after starting the Techila Server as described in Starting the Techila Server Instructions on how to access the Techila Configuration Wizard without the post deployment page can be found in Accessing the Techila Configuration Wizard.

  1. Click on the Open Techila Config Wizard button to open the Techila Configuration Wizard login page.

    image14
  2. After clicking on the button, you should see a login page. Note! If the Techila Server deployment is not ready, you will see the following message:

    `Techila Server deployment still in progress…​ Please wait a couple of minutes and refresh the page.`

    In this case, please wait a couple of minutes and refresh the page.

    The login page is used to access the Techila Configuration Wizard.

    Enter 'admin' as the username. In the password field, copy the Admin Password value from the Google Cloud Platform Console to the password field as shown in the screen capture below. Click the Log in button to log in.

    Note! Make sure you do not accidentally copy any whitespaces before or after the password.

    image16
  3. After logging in, you will be presented the first page of the Techila Configuration Wizard. This page will be used to download the application plugins (delivered in a file called TechilaSDK.zip) from the Techila Server.

    Instructions for downloading and configuring the application plugins can be found in Downloading and Configuring the Application Plugins.

    image17

3.3. Downloading and Configuring the Application Plugins

This Chapter contains instructions for downloading the application plugins to your computer. These application plugins will enable you to push computational workload from your computer to Techila Distributed Computing Engine.

The application plugins are delivered in a file called TechilaSDK.zip. In addition to containing the application plugins for e.g. MATLAB, Python and R, the TechilaSDK.zip contains ready-to-run examples for various programming languages. The application plugins package is also referred to as the "Techila SDK".

Note! The steps described in this Chapter assume that you have logged in to the Techila Configuration Wizard. If you have not logged in, please log in to the Techila Configuration Wizard before continuing.

  1. In the first page of the Techila Configuration Wizard, click the highlighted link to start downloading the application plugins (TechilaSDK.zip) to your computer.

    image18
  2. Save the TechilaSDK.zip file on your computer.

    image19
  3. Wait for the download to complete. After the download has been completed, you should have a file called 'TechilaSDK.zip' as illustrated in the example screenshot below. Please make a mental note where you saved the file, as you will need it when configuring the application plugins in the following steps.

    In the example screenshot below, TechilaSDK.zip has been saved to 'C:\Downloads'.

    image20
  4. Select your web browser and click the Continue button.

    image21
  5. After clicking the Continue button, the second page of the Techila Configuration Wizard will be displayed. This page contains a link to a help page, which contains instructions on how to configure the application plugins on your computer.

    Click the highlighted link to open a help page containing links on how to configure the application plugins on your computer.

    Please follow the instructions on the help page to configure the application plugins for the programming language you are using before continuing.

    image22

    The below table contains the direct links to programming language specific instructions describing the application plugin configuration steps:

Table 2. Configuration Instructions
Programming Language Link

MATLAB

http://www.techilatechnologies.com/techila-for-gcp-marketplace/install-and-configure-techila-for-matlab

Python

http://www.techilatechnologies.com/techila-for-gcp-marketplace/install-and-configure-techila-for-python

R

http://www.techilatechnologies.com/techila-for-gcp-marketplace/install-and-configure-techila-for-r-programming-language

3.4. Increasing Computing Throughput

This Chapter contains instructions for increasing computing throughput, which is done by starting Techila Worker VM instances using the Techila Configuration Wizard.

Note! If you are using the Google free trial, the maximum amount of Techila Worker CPU cores you can deploy is 7. This means that you will only be able to, for example, deploy 7 n1-standard-1 instances, or 3 n1-standard-2 instances. Please also note that when using the Google free trial, CPU core quota increase requests are limited as described here: https://cloud.google.com/free/docs/frequently-asked-questions

Note! Before starting any Techila Workers, it is recommended that you configure the application plugins as described in Downloading and Configuring the Application Plugins.

Note! The steps described in this Chapter assume that you have logged in to the Techila Configuration Wizard. If you have not logged in, please log in before continuing.

  1. Select your web browser and navigate to the third page of the Techila Configuration Wizard using the Continue button.

    image23
  2. The third page of the Techila Configuration Wizard is used to adjust the computing throughput by starting and shutting down Techila Worker VM instances. Note! Add this page to your browser’s bookmarks so you can easily access it later.

    image24
  3. After creating a bookmark, select the Techila Worker VM instance type, choose the operating system and define how many Techila Worker VM instances you want to start.

    After defining the properties, click the Start button to start the Techila Workers.

    Note! If you already have Techila Workers that are running, you can increase (or decrease) the amount of Techila Workers by entering the desired number in the field and clicking the Update button.

    Note! It is strongly recommended that the deletion of the instances is always verified using the Google Cloud Console.

    The Idle Shutdown field can be used to specify a shutdown delay for the Techila Workers. Specifying a shutdown delay will automatically cause Techila Worker VM instances to be deleted if no Jobs are detected on Techila Workers within the specified time. The idle shutdown timer will be activated when computational Jobs are detected on the Techila Workers.

    Example: Let’s assume that you start 10 Workers at 12:10 and you specify a 20 minute idle shutdown timer. You then leave them idling for 30 minutes while you go for lunch. The idle shutdown timer will not shutdown the instances, as they have not processed any Jobs yet. At 12:40 you return from lunch and create a computational Project. The Jobs are then processed on the Techila Workers. The last Job finishes processing on a Worker at 12:50. This triggers the idle timeout timer, which starts monitoring the Techila Workers. The Workers will then idle for 20 minutes (assuming no new Projects are created) and will be terminated at 13:10 by the idle shutdown timer.

    The Computing Environment and Instance Type dropdown menus will only be enabled in situations where no Techila Workers are currently running. If Techila Workers are already running, these menus will default to the values used when starting the existing Techila Workers.

    It is recommended to choose the same operating system that you are using on the computer where you installed and configured the application plugins package.

    Note! When starting Techila Workers, the maximum number of Techila Worker that can be started will be limited by your GCP CPU core quota. Information about resource quotas can be found on the website shown below. This page also contains a link that can be used to request a quota adjustment.

    Information on how to perform a Google quota increase request can also be found in this Chapter: Making a Google Quota Increase request

    Note! For more information about the advanced settings in the Techila Configuration Wizard, please see Advanced Techila Configuration Wizard Settings.

    The settings in the example screenshot below could be used to start 10 Techila Worker VM instances (type n1-standard-8), with a Windows operating system.

    Techila Workers will be started when the Start button is clicked.

    image25
  4. After clicking the Start button, the deployment process for the Techila Workers will start. Progress information will be displayed at the bottom of the page, on the Worker Status and Deployment Status lines.

    The Worker Status line contains information about the status of Techila Workers. The initial value when no instances have been deployed will say 0 of 0 ready for computation. When you start instances, the values on this line will show how many Techila Workers are ready for computations. For example, if you have started 10 instances and the value says 8 of 10 ready for computation, it means that 8 Techila Workers are currently ready and can be used for computing purposes. When all Techila Workers are ready, the values should be the same, e.g. 10 of 10 ready for computation.

    The Deployment Status line contains information about the status of instances. The initial value when no instances are deployed will be not deployed. When you start instances, the value will update to display the status of instances. For example, if you have started 10 instances, you would see a message stating 10 staging while the instances are being started. After all instances have been started and all Techila Workers are online, you will see the following message:

    Workers are ready for computation.

    There are several other values that can be displayed on the Status line, depending on the state of the VM instances that are being deployed. More information about these status values can be found on the following Google documentation page:

    The example screenshots below illustrate the changes in the Ready / Total and Status values when starting Techila Workers.

    Value 0 of 10 ready for computation in Worker Status means no Techila Workers are ready yet. The Deployment Status is 10 staging, which indicates that the user has clicked the Start button and the deployment process has been started.

    image26

    Value 9 of 10 ready for computation means that 9 Techila Workers are ready to process computational Jobs. The Status line states 10 running, which means resources have been acquired and the instances are running.

    image27

    Finally, when all 10 Workers are ready, the view would resemble the one shown below:

    image27 1
  5. After you have started Techila Workers, you can create a computational Project to test that everything works.

  6. Verify functionality by executing one of examples included in the Techila SDK. Examples for R, Python and MATLAB can be found in the following Techila SDK directories:

    • Python examples: 'techila/examples/python'

    • R examples: 'techila/examples/R

    • MATLAB examples: 'techila/examples/Matlab'

      The Techila SDK examples contain information on how you add Techila Distributed Computing Engine functionality to your application and how to enable various Techila Distributed Computing Engine features. Additional information on how to use the Techila Distributed Computing Engine functions from different programming languages can be found using the following links.

    • Techila Distributed Computing Engine with Python

    • Techila Distributed Computing Engine with R

    • Techila Distributed Computing Engine with MATLAB

      Note! After starting Techila Workers, program specific runtime components will be transferred from the Techila Server to the Techila Workers during the first Project. Depending on the programming language you are using, the transfer process may take several minutes. After the runtime components have been transferred, they will be stored on the Techila Workers' hard disks and will be stored there until the Techila Worker VM instances are deleted. During subsequent Projects, the runtime components will be used from the Techila Worker’s hard disk, meaning there will be no network transfer delay.

      If you delete the Techila Worker VM instances and restart Techila Workers at a later time, the runtime components will be need to be re-transferred.

  7. After verifying that the Techila Distributed Computing Engine environment works as expected, you can continue by adding the Techila Distributed Computing Engine functionality to your own application and running it in Techila Distributed Computing Engine.

  8. After you have completed processing computational workloads, it is recommended to delete ALL Techila Workers VM instances to prevent unnecessary costs from being incurred. Instructions for deleting Techila Worker VM instances can be found in Decreasing Computing Throughput.

3.5. Decreasing Computing Throughput

This Chapter contains instructions for decreasing computing throughput, which is done by deleting the Techila Worker VM instances using the Techila Configuration Wizard.

Note! The steps described in this Chapter assume that you have logged in to the Techila Configuration Wizard. If you have not logged in, please log in before continuing.

If you, at some later point, again wish to perform computations in the Techila Distributed Computing Engine environment, you will need to start new Techila Workers as described in Increasing Computing Throughput

  1. Using your browser, open the third page of the Techila Configuration Wizard (the page that was bookmarked earlier). If you did not bookmark the page, navigate to the third page of the Techila Configuration Wizard using the Continue button.

  2. Click the Stop button to delete all ALL Techila Worker VM instances that are currently running.

    Note! If you only want to delete some of the Techila Worker VM instances, you can do this by entering a smaller value in the Number of Worker Nodes field and clicking the Update button. This value should be set to match the number of desired Techila Workers. For example, if you currently have 10 Techila Workers running and you then define value 6 in the Number of Worker Nodes field, the number of running Techila Workers would be reduced to 6 when the Update button is clicked.

    Clicking the Stop button will delete ALL Techila Worker VM instances. After clicking the Stop button, verity that the Techila Worker VM instances were successfully deleted by doing checks described in the following steps.

    image28
  3. Steps for Check 1:

    1. In the Google Cloud Platform Console, navigate to:

      Google Cloud Platform Console → Compute Engine → Instance Groups

      The Google Cloud Platform Console can be accessed from the following page:

      Note! Verify that you have selected the project that you used to deploy Techila Distributed Computing Engine.

    2. Verify that there are no instance groups that start with the deployment name you specified when deploying Techila Distributed Computing Engine. For example, if your deployment is named 'techila-1', make sure that there are no instance groups that have a name starting with 'techila-1'.

      Note! If there are instance groups that have a name that starts with the deployment name you specified when creating the deployment, select the instance groups and delete them using the Delete functionality in the Google Cloud Platform Console.

      The example screenshot below illustrates a situation where there are two instance groups for a Techila deployment named 'techila-1'. These instance groups could be deleted by selecting them and by clicking the Delete icon.

      Techila related instance groups can be deleted by selecting them and clicking the highlighted button.

      image30

      If required, confirm the action.

      image31

      After ensuring that there are no Techila related instance groups, perform the check described in the following step to verify that there are no Techila Worker VM instances running.

  4. Steps for Check 2:

    1. In the Google Cloud Console, navigate to:

      Google Cloud Console → Compute Engine → VM instances.

    2. Verify that no Techila Worker VM instances are running. Techila Worker VM instances can be identified from the 'worker' string in the VM instance name.

      Note! If any Techila Worker VM instances are running, delete any virtual machines that have the string 'worker' in their name by using the Delete functionality in the Google Cloud Platform Console. Only delete the VM instances that that have the string 'worker' in their name, do not delete any other VM instances.

      The example screenshot below illustrates a situation where only the Techila Server is running.

      The VM Instances view when no Techila Workers are running. If some Techila Worker VM instances were not deleted successfully, you can delete them by using the Delete button located on the top-right on the page.

      image32

3.6. Stopping the Techila Server

This Chapter contains instructions for stopping the Techila Server VM instance using the Google Cloud Console. Stopping the Techila Server VM instance will not remove any important data from the Techila Server. If you stop the Techila Server VM instance, you will be able to restart it at a later time.

Note! Stopping the Techila Server will not delete the Techila Worker VM instances. Please delete all Techila Worker VM instances that are running by using the Techila Configuration Wizard. Instructions for deleting Techila Worker VM instances can be found in Decreasing Computing Throughput.

Please also note that even though you stop the Techila Server VM instance and delete all Techila Worker VM instances, you will be billed for the Techila Server disk (default size 64 GB) and for the static IP address that is reserved for the Techila Server.

  1. Navigate to the Google Cloud Platform Console:

  2. In the search box, type compute engine and click on the matching search result to navigate to the Compute Engine view.

    image33
  3. Tick the checkbox for your Techila Server VM instance and click the Stop button. Your Techila Server VM instance name will be <your deployment name>-instance.

    In this example, the name of the Techila Server VM instance is 'techila-1-instance', which means that the deployment name is 'techila-1'.

    image34
  4. When prompted, confirm the action.

    image35

    After confirming the action, the Techila Server VM instance will be stopped.

    After the Techila Server VM has been stopped, there should be an icon indicating the stopped state next to the Techila Server VM. The VM instances view should resemble the one shown below.

    image36

3.7. Restarting the Techila Server

This Chapter contains instructions for restarting the Techila Server using the Google Cloud Platform Console. After restarting the Techila Server, you can continue using your existing application plugin package. You do NOT need to re-download or re-configure the application plugins.

After restarting the Techila Server VM instance according to the instructions in this Chapter, the IP address of the Techila Server will be the same as in the initial deployment. This means that you can use your existing browser bookmarks to access the Techila Configuration Wizard.

Note! If you have more than one Google Cloud Platform project created, make sure that you have selected the project that contains the Techila Distributed Computing Engine components.

  1. Navigate to the Google Cloud Platform Console located at:

  2. In the search box, type compute engine and click on the matching search result to navigate to the Compute Engine view.

    image37
  3. In the VM instances view, tick the checkbox next to your Techila Server VM instance and click the `Start button to start the VM instance.

    image38
  4. When prompted, confirm the action.

    image39

    After the Techila Server has started, an icon indicating the running state should be displayed next to the Techila Server VM instance.

    image40
  5. After starting the Techila Server VM instance, please follow instructions in Accessing the Techila Configuration Wizard to access the Techila Configuration Wizard.

3.8. Accessing the Techila Configuration Wizard

This Chapter contains instructions on how you can access and log in to the Techila Configuration Wizard after restarting the Techila Server, or in other situations where the post deployment page is not accessible (e.g. if you accidentally closed the page after starting the Techila Server).

  1. Using your web browser, navigate to the Google Cloud Platform Console:

  2. In the search box, type deployments and click on the matching search result to navigate to the Compute Engine view.

    image41
  3. Locate your Techila deployment and click on the deployment name.

    image42
  4. Click on the Open Techila Config Wizard button to open the Techila Configuration Wizard login page.

    image14
  5. If you are opening the Techila Configuration Wizard for the first time, your web browser might not trust the Techila Server’s certificate. Accept the certificate using your web browser and continue.

    image15
  6. After trusting the certificate, you should see a login page. Note! If the Techila Server deployment is not ready, you will see the following message:

    `Techila Server deployment still in progress…​ Please wait a couple of minutes and refresh the page.`

    In this case, please wait a couple of minutes and refresh the page.

    Enter 'admin' as the username. In the password field, copy the Password value from the Google Cloud Platform Console to the password field as shown in the screen capture. Click the Log in button to log in.

    image16

3.9. Removing all Techila Distributed Computing Engine Components from Google Cloud Platform

This Chapter contains instructions on how to remove ALL components that were created when taking Techila Distributed Computing Engine in Google Cloud Platform Marketplace into use.

Please note that the steps described in this Chapter are typically only required in situations where you want to discontinue using the Techila Distributed Computing Engine system and plan on never performing any computations using Techila Distributed Computing Engine in Google Cloud Platform Marketplace.

Note! If you perform the steps described in this Chapter, you will NOT be able to restart the Techila Server. Performing the steps described in this Chapter will also delete all user credentials and computational data stored on the Techila Server.

  1. Delete ALL Techila Worker VM instances as described in Decreasing Computing Throughput

  2. In the Google Cloud Platform Console, type deployments in the search box and click the matching search result to open the Deployments view.

    image41
  3. Locate the deployment you have been using for your Techila Distributed Computing Engine components and click on the trash bin icon.

    image44
  4. When prompted, confirm the action.

    image45
  5. Wait for the deployment to be deleted. After the deployment has been deleted, it will no longer be visible on the Deployments page as illustrated below.

    image46

    All components that were created when taking Techila Distributed Computing Engine in Google Cloud Platform Marketplace into use have now been removed from Google Cloud Platform.

4. Appendix

4.1. Advanced Techila Configuration Wizard Settings

Advanced Techila Configuration Wizard settings can be displayed by clicking the Advanced Instance Options and Advanced Options links highlighted in the image below..

options1

The image below shows the advanced instance options.

options2

These advanced instance settings allow you to modify the amount of disk space available on each Techila Worker. The default amount of disk space per Techila Worker node is typically sufficient, but if you plan on processing computational workloads that require large amounts of disk space, increasing the amount of disk space per node might be required. When using the default value, the data will be stored on standard disks, which are not SSD. If you increase the disk space to 375 GB or greater, the disks will be SSD.

Please note that if you set the amount of disk space to a high value and attempt to start a large number of Techila Worker nodes, you might end up in a situation where the deployment exceeds your GCP local SSD disk quota. In this case, either reduce the amount of disk space per node or use larger, but fewer, instances with more CPU cores per node to reduce the total amount of disks required.

The advanced settings also allow you to use preemptible instances, which can help you reduce the cost of the computing capacity.

Please note that preemptible instances will use a different disk quota than regular instances. This means that you might not be able to increase the disk space per node when using preemptible instances.

The image below shows the advanced options available.

options3

These advanced instance settings allow you to enable an alternative idle shutdown mode called One-By-One. When One-By-One is enabled, individual instances will be automatically terminated if they remain idling (= not processing Jobs) over the time period defined in the Idle Shutdown field. This differs from the standard mode, where all instances will be deleted in a single delete operation if they have all idled over the specified time period.

The last option in the advanced section allows you to upload a Techila Distributed Computing Engine (TDCE) license. TDCE licenses can be purchased from Techila Technologies.

4.2. Accessing Techila Configuration Wizard Using https

By default, when opening the Techila Configuration Wizard using your browser, it will be accessed using http. To switch to using https, replace http with https in the url. Example below:

Default:

http://<IP Address>/gce_deployment.php

Https:

https://<IP Address>/gce_deployment.php

Please note that when opening the Techila Configuration Wizard for the first time using https, your web browser might not trust the Techila Server’s certificate. Accept the certificate using your web browser and continue.

Please note that the process for accepting certificates is different in each web browser, meaning the appearance of this screen may be different than the one illustrated here.

This message is displayed because the default certificate for Techila Configuration Wizard is a self signed cert. Its highly recommended that a Trusted root cert be applied to the web server before starting to use https connections. Learn more.

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4.3. Making a Google Quota Increase request

This Chapter describes how to request a quota increase.

When making a quota increase request, the following key points need to be taken into account:

  • Quota increases are project-specific, so please make sure that you are increasing the quota for the same Google project you are using for your Techila Distributed Computing Engine environment.

  • Quota increases are location-specific, so please make sure that you are increasing the quota in the same location where your Techila Distributed Computing Engine deployment is running.

The example flow below shows how to request a quota increase for a project called DemoEnvironment which contains a Techila Distributed Computing Engine deployment running in europe-west4 location.

  1. Log in to the Google Cloud Console

  2. Check that you are using the correct project. After checking, enter "deployments" in the search box and click the matching search result.

    q1
  3. Click on your Techila Distributed Computing Engine deployment.

    q2
  4. Check which zone your deployment is running in and make a mental note of it. When making the quota increase request, this is the zone that will need to be used.

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  5. Next we will start making the quota increase request. In the search box, enter IAM and click the matching search result.

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  6. Click Quotas in the left hand side menu to view the quotas for your project. There will be quite a lot of information in the default view, as shown below.

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  7. Next we will add some filters to reduce the amount of information displayed. In the Location menu, deselect all and choose the location that matches your deployment zone. In this example, europe-west4 has been selected.

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  8. In the Metric menu, deselect all and choose CPUs.

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  9. In the same Metric menu, also select In-use IP addresses.

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  10. You should now have two metrics selected and the view should resemble the one shown below (quota amounts might differ).

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  11. Make a quota increase for both the CPU cores and IP-address amount. Each Techila Worker will require an IP address, meaning when increasing the CPU core quota, it is a good idea to also increase the IP address quota.

    To make the quota requests, tick both checkboxes and click Edit quotas. Fill in your contact details and click Next

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  12. Fill in the amount of CPU cores you need. In this example value 50 is used. The IP address amount should be set to the same value to ensure that you don’t run out of IP addresses when deploying instances with 1 CPU core. Enter a description and click Done.

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  13. Finally, click the Submit request button.

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  14. A confirmation message should be displayed.

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  15. When the quota has been increased, you should receive a confirmation email to your inbox in the email address you entered earlier. The screenshot below illustrates the relevant part of the confirmation email.

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  16. After receiving the confirmation email, the Techila Configuration Wizard will automatically detect the increased quota and you will be able to start instances using the increased quota.

4.4. Checking Monthly Techila Charges

General billing information can be viewed in the Google Cloud Console.

This Chapter contains information on how to check the total amount of costs in a Google project.

  1. Log in to the Google Cloud Console

  2. Click Billing.

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  3. Click Reports.

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  4. The Reports page can be used to extract billing information. The filter options on the right hand side of the page can be used to define the type of billing information that will be extracted and how it will be presented.

    The following example filter settings could be used to extract all costs of one Google project for the current month. This includes the Techila License Fees and all other Google related fees (e.g. instances and storage). By changing the values of the filter, you can change what information will be extracted.

  5. In the filter settings, set the time range to Current month. Set Group by to Project. Tip! If you want a breakdown on how much money was spent on Techila License Fees and how much was spent on other cloud components, you can set Group by to SKU.

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  6. Open the Projects dropdown menu and select the project you want to extract the billing information from. This should be the same project you are using for your TDCE deployment.

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  7. Check that the Products dropdown menu has selected all items.

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  8. Check that the SKUs dropdown menu has selected all items. Please note that when all SKUs are selected, the report will include the costs generated by any Google components in the specified project. This means that if you have, for example, some virtual machines set up in the project that are not generated by the TDCE system (e.g. a development virtual machine that you have set up manually) , they will also be included in the bill.

    If you are only interested in the amount of Techila Software License Fees, you can use the SKUs dropdown to only select the SKUs that start with Licensing Fee for Techila Technologies. Please note that this will only extract the information for the License Fee. It will not include the actual instance costs.

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