Using AWS EC2 - Revision history

PSuthar: /* Accessing DeepSense AWS Management Console */

2023-08-15T00:08:40Z

‎Accessing DeepSense AWS Management Console

PSuthar at 00:03, 15 August 2023

2023-08-15T00:03:38Z

PSuthar at 00:03, 15 August 2023

2023-08-15T00:03:16Z

PSuthar: /* Accessing DeepSense EC2 Instance by SSH */

2023-08-14T23:37:01Z

‎Accessing DeepSense EC2 Instance by SSH

PSuthar: /* How to start Machine Learning Environment? */

2023-03-10T23:50:09Z

‎How to start Machine Learning Environment?

PSuthar: /* How to start Machine Learning Environment? */

2023-03-10T23:47:14Z

‎How to start Machine Learning Environment?

PSuthar: Final changes for AWS EC2

2023-03-10T23:41:23Z

Final changes for AWS EC2

PSuthar: /* Accessing DeepSense EC2 Instance by SSH */

2023-03-07T06:17:50Z

‎Accessing DeepSense EC2 Instance by SSH

PSuthar: /* DeepSense AWS EC2 Instances */

2023-03-07T06:13:58Z

‎DeepSense AWS EC2 Instances

PSuthar: /* DeepSense AWS EC2 Instances */

2023-03-07T06:13:38Z

‎DeepSense AWS EC2 Instances

@@ Line 13: / Line 13: @@
 == Accessing DeepSense AWS Management Console ==
 *Open web browser and navigate to the AWS Management Console login page.
-*Enter the URL provided by your AWS correspondence email or type "https://aws.amazon.com/" in the address bar and press Enter.
+*Enter the URL provided in AWS correspondence email and continue as Sign in as IAM user.
-*On the AWS Management Console login page, locate the "Sign in to the Console" section.
+*Enter the IAM username in the "IAM user name" field.
-*Enter the IAM username in the "IAM Username" field.
+*Enter the IAM user's temporary first password in the "Password" field provided by DeepSense AWS Admin.
 *You will be redirected to change the password on first login, create a new password.
-*After signing in to the AWS Management Console, locate the security credentials in the right top corner, where the account name is written.
+*After signing in to the AWS Management Console, locate the security credentials in the right top corner, where the account number and user name is written.
 *Click on add MFA and follow the on-screen instructions to enable MFA. (https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_mfa_enable_virtual.html#enable-virt-mfa-for-iam-user)
 *After setting MFA kindly sign out and then sign in again with new password you have created and use MFA to access the cloud resources.

@@ Line 11: / Line 11: @@
 EC2 provides the most comprehensive and comprehensive set of machine learning services and cloud infrastructure, putting machine learning in the hands of every developer, data scientist, and expert practitioner. We have used Amazon Deep Learning AMI in every instance to ensure we get all the necessary packeges and libraries so we can avoid time to set up the system and focus on working on model development.
-== Accessing your DeepSense AWS Management Console ==
+== Accessing DeepSense AWS Management Console ==
 *Open web browser and navigate to the AWS Management Console login page.
 *Enter the URL provided by your AWS correspondence email or type "https://aws.amazon.com/" in the address bar and press Enter.

@@ Line 10: / Line 10: @@
 EC2 provides the most comprehensive and comprehensive set of machine learning services and cloud infrastructure, putting machine learning in the hands of every developer, data scientist, and expert practitioner. We have used Amazon Deep Learning AMI in every instance to ensure we get all the necessary packeges and libraries so we can avoid time to set up the system and focus on working on model development.
 == Accessing DeepSense EC2 Instance by SSH ==
 * Prerequisites include providing your own newly created SSH public to the cloud system administrator.
-* Open web browser and navigate to the AWS Management Console login page.
+* Go to EC2 service from search bar.
-* Enter the URL provided by your AWS correspondence email or type "https://aws.amazon.com/" in the address bar and press Enter.
+* Select instances and find the Project Named instance.
 * Select the instance and go to actions.
-* Select Start instance
+* Select Start instance.
-* Select the option Connect and change tab to SSH client
+* Select the option Connect and change tab to SSH client.
-* Copy the SSH command with instance’s present dns address
+* Copy the SSH command with instance’s present dns address.
-* Start your DalVPN to access the instance
+* Start your DalVPN to access the instance.
 * Open Terminal and paste the SSH command and edit it as this: <code>'''ssh -i “privatekey_path” username@DNSaddress'''</code>
-* You should have the access to instance now
+* You should have the access to instance now.
 * Stop instance by console same way you started when your work is done or taking break.

@@ Line 14: / Line 14: @@
 * Prerequisites include providing your own newly created SSH public to the cloud system administrator.
-* Access your AWS console (from email – you will be asked to create new password)
+* Open web browser and navigate to the AWS Management Console login page.
-* Once everything is in place, you will see the AWS console dashboard.
+* Enter the URL provided by your AWS correspondence email or type "https://aws.amazon.com/" in the address bar and press Enter.
-* Navigate to security credentials in the right top corner, where the account name is written.
+* On the AWS Management Console login page, locate the "Sign in to the Console" section.
-* Follow the on-screen instructions to enable MFA. (https://docs.aws.amazon.com/IAM/latest/UserGuide/id_credentials_mfa_enable_virtual.html#enable-virt-mfa-for-iam-user)
+* Enter the IAM username in the "IAM Username" field.
 * Go to EC2 service from search bar [search ec2]
 * Select instances and find the Project Named instance

@@ Line 29: / Line 29: @@
 * Stop instance by console same way you started when your work is done or taking break.
-== How to start Machine Learning Environment? ==
+== How to activate Machine Learning Environment? ==
 * After successful login from terminal through SSH you will have terminal access to your instance.

@@ Line 38: / Line 38: @@
 The AWS Deep Learning AMI (DLAMI) is customised machine instance is available in the Amazon EC2 regions for a variety of instance types, ranging from a small CPU-only instance to the most recent high-powered multi-GPU instances.
-* As all the GPU resourses are of NVIDIA, you can find out the GPU info by typing <code>nvidia-ami</code>
+* As all the GPU resourses are of NVIDIA, you can find out the GPU info by typing <code>nvidia-smi</code>
 * To activate the inbuilt environment write this command <code>activate tensorflow</code> or <code> activate pytorch</code>.

← Older revision		Revision as of 23:41, 10 March 2023
Line 28:		Line 28:
	* You should have the access to instance now		* You should have the access to instance now
	* Stop instance by console same way you started when your work is done or taking break.		* Stop instance by console same way you started when your work is done or taking break.
		+
		+	== How to start Machine Learning Environment? ==
		+
		+	* After successful login from terminal through SSH you will have terminal access to your instance.
		+	* DeepSense virtual machines launched in the AWS Deep Learning AMI.
		+
		+	=== What is AWS DLAMI? ===
		+
		+	The AWS Deep Learning AMI (DLAMI) is customised machine instance is available in the Amazon EC2 regions for a variety of instance types, ranging from a small CPU-only instance to the most recent high-powered multi-GPU instances.
		+
		+	* As all the GPU resourses are of NVIDIA, you can find out the GPU info by typing <code>nvidia-ami</code>
		+	* To activate the inbuilt environment write this command <code>activate tensorflow</code> or <code> activate pytorch</code>.

@@ Line 3: / Line 3: @@
 ==  DeepSense AWS EC2 Instances ==
-Find the available EC2 options here [[Resources]]
+Find the available EC2 options on [[Resources]]
 We acquired AWS EC2 for DeepSense in order to take advantage of its best services and use it as a Virtual Machine. This is ideal for running high-performance applications, long-running applications, and applications that must start immediately. If you use AWS EC2 instances, remember to backup your data to avoid losing it. Amazon EC2 offers users a variety of instance types, software packages, instance storage, and operating systems, resulting in flexibility. Users can configure memory, CPU, and boot partition size on Amazon EC2, which is then optimised for the operating system and application.