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What is Elastic Compute Cloud (EC2)?

EC2 stands for Elastic Compute Cloud. EC2 is an on-demand computing service on the AWS cloud platform. Under computing, it includes all the services a computing device can offer to you along with the flexibility of a virtual environment. It also allows the user to configure their instances as per their requirements i.e. allocate the RAM, ROM, and storage according to the need of the current task. Even the user can dismantle the virtual device once its task is completed and it is no more required. For providing, all these scalable resources AWS charges some bill amount at the end of every month, the bill amount is entirely dependent on your usage. EC2 allows you to rent virtual computers. The provision of servers on AWS Cloud is one of the easiest ways in EC2. EC2 has resizable capacity. EC2 offers security, reliability, high performance, and cost-effective infrastructure so as to meet the demanding business needs.

Table of Content

AWS EC2 (Elastic Compute Cloud)

What is amazon ec2 (elastic compute cloud), use cases of amazon ec2 (elastic compute cloud), aws ec2 instance types, features of aws ec2 (elastic compute cloud), pricing of aws ec2 (elastic compute cloud) instance, create aws free tier account, get started with amazon ec2 (elastic compute cloud) linux instances, benefits of amazon ec2, best practices of amazon ec2.

Amazon Web Service EC2 is a web service which is provided by the AWS cloud which is secure, resizable, and scalable. These virtual machines are pre-configured with the operating systems and some of the required software. Instead of managing the infrastructure AWS will do that so you can just launch and terminate the EC2 instance whenever you want. You can scale up and down the EC2 instance depending on the incoming traffic. The other advantage of AWS EC2 is that you need to pay only for how much you use it is like the pay-as-you-go model.

Amazon Web service offers EC2 which is a short form of Elastic Compute Cloud (ECC) it is a cloud computing service offered by the Cloud Service Provider AWS. You can deploy your applications in EC2 servers without any worrying about the underlying infrastructure. You configure the EC2-Instance in a very secure manner by using the VPC, Subnets, and Security groups. You can scale the configuration of the EC2 instance you have configured based on the demand of the application by attaching the autoscaling group to the EC2 instance. You can scale up and scale down the instance based on the incoming traffic of the application.

The following figure shows the EC2-Instance which is deployed in VPC (Virtual Private Cloud).

The following are the use cases of Amazon EC2:

• Deploying Application: In the AWS EC2 instance, you can deploy your application like .jar,.war, or .ear application without maintaining the underlying infrastructure.
• Scaling Application: Once you deployed your web application in the EC2 instance know you can scale your application based upon the demand you are having by scaling the AWS EC2-Instance.
• Deploying The ML Models: You can train and deploy your ML models in the EC2-instance because it offers up to 400 Gbps), and storage services purpose-built to optimize the price performance for ML projects.
• Hybrid Cloud Environment: You can deploy your web application in EC2-Instance and you can connect to the database which is deployed in the on-premises servers.
• Cost-Effective: Amazon EC2-instance is cost-effective so you can deploy your gaming application in the Amazon EC2-Instances

Different Amazon EC2 instance types are designed for certain activities. Consider the unique requirements of your workloads and applications when choosing an instance type. This might include needs for computing, memory, or storage.

The AWS EC2 Instance types are as follows:

• General Purpose Instances
• Compute Optimized Instances
• Memory-Optimized Instances
• Storage Optimized Instances
• Accelerated Computing Instances

1. General Purpose Instances

• It provides the balanced resources for a wide range of workloads.
• It is suitable for web servers, development environments, and small databases.

Examples: T3, M5 instances.

2. Compute Optimized Instances

• It provides high-performance processors for compute-intensive applications.
• It will be Ideal for high-performance web servers, scientific modeling, and batch processing.

Examples: C5, C6g instances.

3. Memory-Optimized Instances

• High memory-to-CPU ratios for large data sets.
• Perfect for in-memory databases, real-time big data analytics, and high-performance computing (HPC).

Examples: R5, X1e instances.

4. Storage Optimized Instances

• It provides optimized resource of instance for high, sequential read and write access to large data sets.
• Best for data warehousing, Hadoop, and distributed file systems.

Examples: I3, D2 instances.

5. Accelerated Computing Instances

• It facilitates with providing hardware accelerators or co-processors for graphics processing and parallel computations.
• It is ideal for machine learning, gaming, and 3D rendering.

Examples: P3, G4 instances.

The following are the features of AWS EC2:

1. AWS EC2 Functionality

EC2 provides its users with a true virtual computing platform, where they can use various operations and even launch another EC2 instance from this virtually created environment. This will increase the security of the virtual devices. Not only creating but also EC2 allows us to customize our environment as per our requirements, at any point of time during the life span of the virtual machine. Amazon EC2 itself comes with a set of default AMI(Amazon Machine Image) options supporting various operating systems along with some pre-configured resources like RAM, ROM, storage, etc. Besides these AMI options, we can also create an AMI curated with a combination of default and user-defined configurations. And for future purposes, we can store this user-defined AMI, so that next time, the user won’t have to re-configure a new AMI(Amazon Machine Image) from scratch. Rather than this whole process, the user can simply use the older reference while creating a new EC2 machine.

2. AWS EC2 Operating Systems

Amazon EC2 includes a wide range of operating systems to choose from while selecting your AMI. Not only are these selected options, but users are also even given the privilege to upload their own operating systems and opt for that while selecting AMI during launching an EC2 instance. Currently, AWS has the following most preferred set of operating systems available on the EC2 console.

• Amazon Linux
• Windows Server
• Ubuntu Server
• Red Hat Linux

3. AWS EC2 Software

Amazon is single-handedly ruling the cloud computing market, because of the variety of options available on EC2 for its users. It allows its users to choose from various software present to run on their EC2 machines. This whole service is allocated to AWS Marketplace on the AWS platform. Numerous software like SAP, LAMP, Drupal, etc are available on AWS to use.

4. AWS EC2 Scalability and Reliability

EC2 provides us the facility to scale up or scale down as per the needs. All dynamic scenarios can be easily tackled by EC2 with the help of this feature. And because of the flexibility of volumes and snapshots, it is highly reliable for its users. Due to the scalable nature of the machine, many organizations like Flipkart, and Amazon rely on these days whenever humongous traffic occurs on their portals.

The pricing of AWS EC2-instance is mainly going to depend upon the type of instance you are going to choose. The following are the pricing charges on some of the EC2-Instances.

• On-Demand Instances: The On-Demand instance is like a pay-as-you-go model where you have to pay only for the time you are going to use if the instance is stopped then the billing for that instance will be stopped when it was in the running state then you are going to be charged. The billing will be done based on the time EC2-Instance is running.
• Reserved Instances: Reversed Instance is like you are going to give the commitment to the AWS by buying the instance for one year or more than one year by the requirement to your organization. Because you are giving one year of Commitment to the AWS they will discount the price on that instance.
• Spot Instances: You have to bid the instances and who will win the bid they are going to get the instance for use but you can’t save the data which is used in this type of instance.

Amazon Web Service(AWS) is the world’s most comprehensive and broadly adopted cloud platform, offering over 200 fully featured services from data centers globally. Millions of customers including the fastest-growing startups, largest enterprises, and leading government agencies are using AWS to lower costs, become more agile, and innovate faster. AWS offers new subscribers a 12-month free tier to get hands-on experience with all AWS cloud services. To know more about how to create an AWS account for free refer to Amazon Web Services (AWS) – Free Tier Account Set up .

Step 1: First login into your AWS account. Once you are directed to the management console. From the left click on “Services” and from the listed options click on EC2 .

• Afterward, you will be redirected to the EC2 console. Here is the image attached to refer to various features in EC2.

• To know more about creating an EC2-Instance in a Step-by-Step guide refer to the Amazon EC2 – Creating an Elastic Cloud Compute Instance.

The following are the benefits of Amazon EC2:

• Scalability: It helps to easily scale the instances up or down based on the demand with ensuring the optimal performance and cost-efficiency.
• Flexibility: It provides wide variety of instance types and configurations for matching different workload requirements and operating systems.
• Cost-Effectiveness: It comes with providing Pay-as-you-go model with options like On-Demand, Reserved, and Spot Instances for managing cost efficiently.
• High Availability and Reliability : It offers multiple geographic regions and availability zones for strong fault tolerance and disaster recovery.

The following are the best practices of Amazon EC2:

• Optimize Instance Selection: It helps in choosing the right instance type for your workload to balance the performance and cost.
• Implement Security Measures: On using the security groups, VPC, and IAM roles for control access and permissions.
• Enable Monitoring and Logging: It facilitates with utilizing cloudwatch to monitor the instance performance and setup the alarms.
• Automate and Backup: It helps in using the autoscaling features for automatically adjusting the instance capacity based on traffic.

AWS EC2-Instance – FAQs

Is ec2 a paas or iaas.

EC2 belongs to Infrastructure as a service where the underlaying infrastructure is taken care by AWS.

Is EC2 a Virtual Machine?

Yes EC2 is an virtual machine where you can deploy the web applications.

What is AWS EC2 vs Elastic?

EC2 is charged based on the types of resources you are using like instance type, region you are deploying it will cost as pay as you go model and elastic beanstalk will be charged based on the resources consumed by elastic beanstalk.

What is EC2 in AWS?

Amazon EC2 (Elastic Compute Cloud) provides scalable virtual servers in the AWS cloud.

Is EC2 just a VM?

Yes, EC2 instances are virtual machines that you can configure and manage in the cloud.

What is EC2 good for?

EC2 is will be ideal for running the applications, hosting the websites, and handling the scalable workloads.

Why do customers use EC2?

Customers can use the Amazon EC2 for its features such as flexibility, scalability, cost-effectiveness, and ease of use.

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What are some Amazon EC2 use cases?

Users and organizations across the globe continue to unearth new Amazon EC2 use cases, from simple and straightforward websites to complex machine learning web apps.

Enterprise large and small, developers solo and squad, are finding new and creative ways to put the power that Amazon makes available to them via Elastic Compute Cloud . The virtually unlimited compute capacity, and sublime integrations with other AWS services, means that EC2 is the platform of choice for any and all manner of cloud based solutions.

Let’s take a quick look at some of the interesting and commonly employed ways of putting the Amazon EC2 platform to use.

EC2 use cases

The low costs and the ability to turn features on or off with the click of a button means everyone from web and application developers to gamers, researchers and scientists to entertainment and marketing companies are jumping in on the EC2 bandwagon to make the cloud work for them.

Here are some common EC2 use cases:

Hosting environments

One of the foremost uses of EC2 is for hosting a variety of applications, software and websites on the cloud. Users are even hosting games on the cloud, turning the servers on and off when needed. And the best part of this dynamic and scalable environment is that its compute capacity can grow along with the need of the application. This in turn ensures the best quality service for all end users at all times. Companies like Netflix, Reddit, and Nintendo are proof of the EC2 hosting success.

Development and test environments

The scalable nature of EC2 means that organizations now have the ability to create and deploy large scale testing and development environments with unprecedented ease. The Amazon cloud does away with any heavy upfront investments for hardware, all the while providing as scalable solution.

Backup and disaster recovery

Companies are leveraging EC2 as a medium for performing disaster recovery for both active and passive environments. The fact that the Amazon Elastic Compute Cloud can be turned up quickly in case of an emergency, means that businesses have access to a faster failover with minimal downtime for their applications.

Banking and financial sector

These are areas that demand the utmost in security and scalability — both are factors that Amazon EC2 provides in droves. Financial institutions trust the Amazon cloud to provide a range of highly secure services. Retail and commercial banks, credit unions, insurance providers, card service companies, and major payment platforms rely on AWS for their scalable cloud computing needs. EC2 provides efficient solutions for financial giants like Capital One, BBVA, UniCredit, and Pacific Life.

Marketing and advertisement

Low costs and rapid provisioning capabilities that EC2 allows have resulted in the platform increasingly being used to host marketing and advertising environments on the fly.

High performance computing

The need for HPC is exponentially on the rise, and EC2 provides specialized virtualized servers that provide both high performance networking and compute power. These can be used to perform a range of CPU intensive and number crunching tasks, including Big Data analytics and processing. NASA uses Amazon EC2 for JPL, and Pfizer is another organization that employs the use of HPC using EC2 instances.

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Featured Article

How Amazon EC2 grew from a notion into a foundational element of cloud computing

The beta launched 15 years ago this week.

Fifteen years ago this week on August 25, 2006, AWS turned on the very first beta instance of EC2 , its cloud-based virtual computers. Today cloud computing, and more specifically infrastructure as a service, is a staple of how businesses use computing, but at that moment it wasn’t a well known or widely understood concept .

The EC in EC2 stands for Elastic Compute, and that name was chosen deliberately. The idea was to provide as much compute power as you needed to do a job, then shut it down when you no longer needed it — making it flexible like an elastic band. The launch of EC2 in beta was preceded by the beta release of S3 storage six months earlier , and both services marked the starting point in AWS’ cloud infrastructure journey.

You really can’t overstate what Amazon was able to accomplish with these moves. It was able to anticipate an entirely different way of computing and create a market and a substantial side business in the process. It took vision to recognize what was coming and the courage to forge ahead and invest the resources necessary to make it happen, something that every business could learn from.

The AWS origin story is complex, but it was about bringing the IT power of the Amazon business to others. Amazon at the time was not the business it is today, but it was still rather substantial and still had to deal with massive fluctuations in traffic such as Black Friday when its website would be flooded with traffic for a short but sustained period of time. While the goal of an e-commerce site, and indeed every business, is attracting as many customers as possible, keeping the site up under such stress takes some doing and Amazon was learning how to do that well.

Those lessons and a desire to bring the company’s internal development processes under control would eventually lead to what we know today as Amazon Web Services, and that side business would help fuel a whole generation of startups. We spoke to Dave Brown, who is VP of EC2 today, and who helped build the first versions of the tech, to find out how this technological shift went down.

Sometimes you get a great notion

The genesis of the idea behind AWS started in the 2000 timeframe when the company began looking at creating a set of services to simplify how they produced software internally. Eventually, they developed a set of foundational services — compute, storage and database — that every developer could tap into.

But the idea of selling that set of services really began to take shape at an executive offsite at Jeff Bezos’ house in 2003. A 2016 TechCrunch article on the origins AWS described how that started to come together:

As the team worked, Jassy recalled, they realized they had also become quite good at running infrastructure services like compute, storage and database (due to those previously articulated internal requirements). What’s more, they had become highly skilled at running reliable, scalable, cost-effective data centers out of need. As a low-margin business like Amazon, they had to be as lean and efficient as possible.

They realized that those skills and abilities could translate into a side business that would eventually become AWS. It would take a while to put these initial ideas into action, but by December 2004, they had opened an engineering office in South Africa to begin building what would become EC2. As Brown explains it, the company was looking to expand outside of Seattle at the time, and Chris Pinkham, who was director in those days, hailed from South Africa and wanted to return home.

Brown was hired right around this time and went to work with Pinkham and a team of 14 people in a small office in Cape Town working on what was known at the time as the “Amazon Execution Engine.” Brown says that Amazon executives saw this as a potentially decent business, but nothing at the scale they are seeing today as they approach a $60 billion yearly run rate .

“When I joined, I think there were like 14 of us in the Cape Town office working on EC2, bringing in some of the very early preview customers at the time and telling us what they wanted. [ … ] We often had leaders come to the office and talk about how AWS could be a billion dollar business one day, and that just seemed so far away for us to ever get to that. It just seemed crazy,” he said.

Getting down to business

Brown says when it came to building a workable solution they just rolled up their sleeves and got down to it. As they do today, they spoke to customers and tried to give them what they need while iterating on their design as they went. It would take 21 months from the time the office opened to the time they launched the beta, and it had to be an enormous engineering challenge to take the technology that was available in that time period and turn it into flexible compute resources that were available with a credit card.

One way they did that was emulating what a rack could look like in the data center they were building in Virginia to house this project. This was long before any racks had been ordered or built, so they had to fake it. “In fact, in the early days of building EC2, we were iterating so quickly on various prototypes that we ended up mocking a data center rack with a stack of laptops in the corner of the Cape Town office,” he said.

While VMware had built its first hypervisor a couple of years earlier, the EC2 team decided to go with an open source product, the Xen hypervisor , that they found that was more flexible for their purposes, even though there were many challenges trying to make the virtualization work in an efficient way at the time. They would eventually move on from Xen a few years later, but it enabled them to get the product off the ground.

“We actually chose Xen as our hypervisor, and just used that as the underlying technology. There were a number of challenges with virtualization. Many people loved what it could do, but from a performance point of view, there were challenges with getting the same performance that you would get out of bare metal,” he said. Bare metal refers to a single tenant server running one operating system. With cloud computing, the idea mostly is having multiple tenants sharing various virtual machines with each one running its own operating system.

Expecting to scale

Over the almost two year period they were building EC2, they overcame a slew of challenges and eventually got a beta product up and running on August 25, 2006. While it was a big moment, there would be additional problems, especially when it came to scaling this idea, which was and remains one of the primary value props cloud computing.

“I always talk about this idea of ‘the illusion of infinite capacity,’ and what we’re shooting for in the cloud is that anytime a customer comes along and says I need a machine, we never say no to them. And that’s incredibly difficult to scale. And so it means that we have to have really good algorithms so they manage our supply chain really well, as well,” Brown said.

That was the goal, but it didn’t always go as planned, and they were often putting out fires in the early days. He tells the story of how they almost ran out of capacity early on and had to make use of a bunch of test machines to keep the operation going. “Peter DeSantis, who was leading our cloud businesses at the time (and today runs worldwide infrastructure for AWS), ran out of his office and asked everyone on the team to shut down any [test] instances we were using. We managed to find about 70 [available servers] and that was good enough to get us through the next few days when the next group of racks landed,” Brown explained.

They would get better and better at managing capacity of course, but the early days brought a constant set of problems to deal with and solve. It took two years to reach a million instances, which was a major milestone for the group. Just two months later, it reached 2 million and a couple of months after that, 3 million. Brown says they stopped counting after that, and today they deliver 60 million instances every single day.

They got the vision right and the technology matured along the way. Over time formidable competitors like Microsoft and Google eventually entered the fray. Brown considers himself fortunate to have been along for the entire 15 year journey, and to be part of a team building technology that had such a huge impact on computing.

Today, no startup launching is running their own infrastructure unless their solution has a unique requirement that demands it, and the flexibility of cloud infrastructure means these young companies can concentrate on their core competencies to build the business instead of racking and stacking servers and worrying about budgeting for resource capacity. That is a huge advantage and one that wasn’t really possible at scale prior to AWS starting this business.

AWS was first to market and has maintained that first mover advantage all these years. Today the company has around 33% market share, according to Synergy Research , a percentage that has remained remarkably steady over the years, even as the market keeps growing. In the most recent Amazon earnings report, AWS generated over $14 billion for the quarter, a far cry from the $1 billion the company was envisioning when it launched EC2 fifteen years ago.

How AWS came to be

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Get started with Amazon EC2

Use this tutorial to get started with Amazon Elastic Compute Cloud (Amazon EC2). You'll learn how to launch and connect to an EC2 instance. An instance is a virtual server in the AWS Cloud. With Amazon EC2, you can set up and configure the operating system and applications that run on your instance.

The following diagram shows the key components that you'll use in this tutorial:

An image – A template that contains the software to run on your instance, such as the operating system.

A key pair – A set of security credentials that you use to prove your identity when connecting to your instance. The public key is on your instance and the private key is on your computer.

A network – A virtual private cloud (VPC) is a virtual network dedicated to your AWS account. To help you get started quickly, your account comes with a default VPC in each AWS Region, and each default VPC has a default subnet in each Availability Zone.

A security group – Acts as a virtual firewall to control inbound and outbound traffic.

An EBS volume – We require a root volume for the image. You can optionally add data volumes.

Cost for this tutorial

When you sign up for AWS, you can get started with Amazon EC2 using the AWS Free Tier . If you created your AWS account less than 12 months ago, and have not already exceeded the Free Tier benefits for Amazon EC2, it won't cost you anything to complete this tutorial, because we help you select options that are within the Free Tier benefits. Otherwise, you'll incur the standard Amazon EC2 usage fees from the time that you launch the instance until you terminate the instance (which is the final task of this tutorial), even if it remains idle.

For instructions to determine whether you are eligible for the Free Tier, see Track your Free Tier usage for Amazon EC2 .

Step 1: Launch an instance

Step 2: connect to your instance, step 3: clean up your instance.

You can launch an EC2 instance using the AWS Management Console as described in the following procedure. This tutorial is intended to help you quickly launch your first instance, so it doesn't cover all possible options.

To launch an instance

Open the Amazon EC2 console at https://console.aws.amazon.com/ec2/ .

In the navigation bar at the top of the screen, we display the current AWS Region — for example, Ohio . You can use the selected Region, or optionally select a Region that is closer to you.

From the EC2 console dashboard, in the Launch instance pane, choose Launch instance .

Under Name and tags , for Name , enter a descriptive name for your instance.

Under Application and OS Images (Amazon Machine Image) , do the following:

Choose Quick Start , and then choose the operating system (OS) for your instance. For your first Linux instance, we recommend that you choose Amazon Linux.

From Amazon Machine Image (AMI) , select an AMI that is marked Free Tier eligible .

Under Instance type , for Instance type , choose t2.micro , which is eligible for the Free Tier. In Regions where t2.micro is not available, t3.micro is eligible for the Free Tier .

Under Key pair (login) , for Key pair name , choose an existing key pair or choose Create new key pair to create your first key pair.

If you choose Proceed without a key pair (Not recommended) , you won't be able to connect to your instance using the methods described in this tutorial.

Under Network settings , notice that we selected your default VPC, selected the option to use the default subnet in an Availability Zone that we choose for you, and configured a security group with a rule that allows connections to your instance from anywhere. For your first instance, we recommend that you use the default settings. Otherwise, you can update your network settings as follows:

(Optional) To use a specific default subnet, choose Edit and then choose a subnet.

(Optional) To use a different VPC, choose Edit and then choose an existing VPC. If the VPC isn't configured for public internet access, you won't be able to connect to your instance.

(Optional) To restrict inbound connection traffic to a specific network, choose Custom instead of Anywhere , and enter the CIDR block for your network.

(Optional) To use a different security group, choose Select existing security group and choose an existing security group. If the security group does not have a rule that allows connection traffic from your network, you won't be able to connect to your instance. For a Linux instance, you must allow SSH traffic. For a Windows instance, you must allow RDP traffic.

Under Configure storage , notice that we configured a root volume but no data volumes. This is sufficient for test purposes.

Review a summary of your instance configuration in the Summary panel, and when you're ready, choose Launch instance .

If the launch is successful, choose the ID of the instance from the Success notification to open the Instances page and monitor the status of the launch.

Select the check box for the instance. The initial instance state is pending . After the instance starts, its state changes to running . Choose the Status and alarms tab. After your instance passes its status checks, it is ready to receive connection requests.

The procedure that you use depends on the operating system of the instance. If you can't connect to your instance, see Troubleshoot issues connecting to your Amazon EC2 Linux instance for assistance.

You can connect to your Linux instance using any SSH client. If you are running Windows on your computer, open a terminal and run the ssh command to verify that you have an SSH client installed. If the command is not found, install OpenSSH for Windows .

To connect to your instance using SSH

In the navigation pane, choose Instances .

Select the instance and then choose Connect .

On the Connect to instance page, choose the SSH client tab.

(Optional) If you created a key pair when you launched the instance and downloaded the private key (.pem file) to a computer running Linux or macOS, run the example chmod command to set the permissions for your private key.

Copy the example SSH command. The following is an example, where key-pair-name .pem is the name of your private key file, ec2-user is the username associated with the image, and the string after the @ symbol is the public DNS name of the instance.

In a terminal window on your computer, run the ssh command that you saved in the previous step. If the private key file is not in the current directory, you must specify the fully-qualified path to the key file in this command.

The following is an example response:

(Optional) Verify that the fingerprint in the security alert matches the instance fingerprint contained in the console output when you first start an instance. To get the console output, choose Actions , Monitor and troubleshoot , Get system log . If the fingerprints don't match, someone might be attempting a man-in-the-middle attack. If they match, continue to the next step.

Enter yes .

To connect to a Windows instance using RDP, you must retrieve the initial administrator password and then enter this password when you connect to your instance. It takes a few minutes after instance launch before this password is available.

The default username for the Administrator account depends on the language of the operating system (OS) contained in the AMI. To ascertain the correct username, identify the language of your AMI's OS, and then choose the corresponding username. For example, for an English OS, the username is Administrator , for a French OS it's Administrateur , and for a Portuguese OS it's Administrador . If a language version of the OS does not have a username in the same language, choose the username Administrator (Other) . For more information, see Localized Names for Administrator Account in Windows in the Microsoft TechNet Wiki.

To retrieve the initial administrator password

On the Connect to instance page, choose the RDP client tab.

For Username , choose the default username for the Administrator account. The username you choose must match the language of the operating system (OS) contained in the AMI that you used to launch your instance. If there is no username in the same language as your OS, choose Administrator (Other) .

Choose Get password .

On the Get Windows password page, do the following:

Choose Upload private key file and navigate to the private key ( .pem ) file that you specified when you launched the instance. Select the file and choose Open to copy the entire contents of the file to this window.

Choose Decrypt password . The Get Windows password page closes, and the default administrator password for the instance appears under Password , replacing the Get password link shown previously.

Copy the password and save it in a safe place. This password is required to connect to the instance.

The following procedure uses the Remote Desktop Connection client for Windows (MSTSC). If you're using a different RDP client, download the RDP file and then see the documentation for the RDP client for the steps to establish the RDP connection.

To connect to a Windows instance using an RDP client

On the Connect to instance page, choose Download remote desktop file . When the file download is finished, choose Cancel to return to the Instances page. The RDP file is downloaded to your Downloads folder.

Run mstsc.exe to open the RDP client.

Expand Show options , choose Open , and select the .rdp file from your Downloads folder.

By default, Computer is the public IPv4 DNS name of the instance and User name is the administrator account. To connect to the instance using IPv6 instead, replace the public IPv4 DNS name of the instance with its IPv6 address. Review the default settings and change them as needed.

Choose Connect . If you receive a warning that the publisher of the remote connection is unknown, choose Connect to continue.

Enter the password that you saved previously, and then choose OK .

Due to the nature of self-signed certificates, you might get a warning that the security certificate could not be authenticated. Do one of the following:

If you trust the certificate, choose Yes to connect to your instance.

[Windows] Before you proceed, compare the thumbprint of the certificate with the value in the system log to confirm the identity of the remote computer. Choose View certificate and then choose Thumbprint from the Details tab. Compare this value to the value of RDPCERTIFICATE-THUMBPRINT in Actions , Monitor and troubleshoot , Get system log .

[Mac OS X] Before you proceed, compare the fingerprint of the certificate with the value in the system log to confirm the identity of the remote computer. Choose Show Certificate , expand Details , and choose SHA1 Fingerprints . Compare this value to the value of RDPCERTIFICATE-THUMBPRINT in Actions , Monitor and troubleshoot , Get system log .

If the RDP connection is successful, the RDP client displays the Windows login screen and then the Windows desktop. If you receive an error message instead, see Remote Desktop can't connect to the remote computer . When you are finished with the RDP connection, you can close the RDP client.

After you've finished with the instance that you created for this tutorial, you should clean up by terminating the instance. If you want to do more with this instance before you clean up, see Next steps .

Terminating an instance effectively deletes it; you can't reconnect to an instance after you've terminated it.

You'll stop incurring charges for that instance or usage that counts against your Free Tier limits as soon as the instance status changes to shutting down or terminated . To keep your instance for later, but not incur charges or usage that counts against your Free Tier limits , you can stop the instance now and then start it again later. For more information, see Stop and start Amazon EC2 instances .

To terminate your instance

In the navigation pane, choose Instances . In the list of instances, select the instance.

Choose Instance state , Terminate instance .

Choose Terminate when prompted for confirmation.

Amazon EC2 shuts down and terminates your instance. After your instance is terminated, it remains visible on the console for a short while, and then the entry is automatically deleted. You cannot remove the terminated instance from the console display yourself.

After you start your instance, you might want to explore the following next steps:

Learn how to track your Amazon EC2 Free Tier usage using the console. For more information, see Track your Free Tier usage for Amazon EC2 .

Configure a CloudWatch alarm to notify you if your usage exceeds the Free Tier. For more information, see Tracking your AWS Free Tier usage in the AWS Billing User Guide .

Add an EBS volume. For more information, see Create an Amazon EBS volume in the Amazon EBS User Guide .

Learn how to remotely manage your EC2 instance using the Run command. For more information, see AWS Systems Manager Run Command in the AWS Systems Manager User Guide .

Learn about instance purchasing options. For more information, see Amazon EC2 billing and purchasing options .

Get advice about instance types. For more information, see Get recommendations from EC2 instance type finder .

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Agents for Cloud Resource Allocation: An Amazon EC2 Case Study

2011, Communications in Computer and Information Science

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Dr. Manisha Malhotra

A cloud computing environment offers a simplified, centralized platform or resources for use when needed on low cost. One of the key functionality of this type of computing is to allocate the resources on an individual demand. However, with the expanding requirements of cloud user, the need of efficient resource computing is also emerging. The main role of service provider is to effectively distribute and share the resources which otherwise would result into resource wastage. In addition to the user getting the appropriate service according to request, the cost of respective resource is also optimized. In order to surmount the mentioned shortcomings, this paper proposes a new agent based optimized resource assignment algorithm which is not only responsible for searching comprehensive services but also considers reducing the cost of virtual machines which are consumed by on-demand services only.

Yaser Jararweh

Applied Sciences

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The cloud computing paradigm has the ability to adapt to new technologies and provide consistent cloud services. These features have led to the widespread use of the paradigm, making it necessary for the underlying computer infrastructure to cope with the increased demand and the high number of end users. Platforms often use classical mathematical models for this purpose, helping assign computational resources to the services provided to the final user. Although this kind of model is valid and widespread, it can be refined through intelligent techniques. Therefore, this research presents a novel system consisting of a multi-agent system, which integrates a case-based reasoning system. The resulting system dynamically allocates resources within a cloud computing platform. This approach, which is distributed and scalable, can learn from previous experiences and produce better results in each resource allocation. A model of the system has been implemented and tested on a real cloud pla...

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Juan M Corchado , javier Bajo

The distribution of computational resources in a Cloud Computing platform is a complex process with several parameters to consider such as the demand for services, available computational resources and service level agreements with end users. Currently, the state-of-the-art presents centralized approaches derived from previous technologies related to cluster of servers. These approaches allocate computational resources by means of the addition/removal of (physical/virtual) computational nodes. However, virtualization technology currently allows for research into new techniques, which makes it possible to allocate at a lower level. In other words, not only is it possible to add/remove nodes, but also to modify the resources of each virtual machine (low level resource allocation). Thus, agent theory is a key technology in this field, allowing decentralized resource allocation. This innovative approach has undeniable improvements such us computational load distribution and reduced computation time. The evaluation was carried out through experiments in a real Cloud environment, thus proving the validity of the proposed approach.

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With the advent of evolution of cloud computing, large organizations have been scaling the on-premise IT infrastructure to the cloud. Although this being a popular practice, it lacks comprehensive efforts to study the aspects of automated negotiation of resources among cloud customers and providers. This paper proposes a full-fledged framework for the multi-party, multi-issue negotiation system for cloud resources. It introduces a robust cloud marketplace system to buy and sell cloud resources. The Belief-Desire-Intention (BDI) model-based cloud customer and provider agents concurrently negotiate on multiple issues, pursuing a hybrid tactic of time and resource-based dynamic deadline algorithms to generate offers and counter-offers. The cloud marketplace-based system is further augmented with the assignment of behavior norm score and reputation index to the agents to establish trust among them.

It is undeniable that the term Cloud Computing has gained in importance at a remarkable pace. It is a technology which is becoming a common element of our life, due to the variety of devices related to the Internet of Things. In this technological frame, there are not many studies in which a Mul-tiagent system has facilitated the management of a cloud-based computational environment; although a first sight its features (autonomy, decentralization, auto organization , etc.) seem suitable for the task. This study presents the +Cloud which is a cloud platform managed by a Multiagent System.

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The Ultimate Guide to Amazon EC2 Cloud Services

Amazon EC2 is one of the most popular cloud computing services available, providing a flexible and easy-to-use platform for businesses of all sizes to access the power of the cloud. With this comprehensive guide, you’ll learn how to use Amazon EC2 to take advantage of its scalability, cost-effectiveness, security, and more.

Amazon EC2 offers the broadest and deepest compute platform. It has over 500 instances to meet the diverse needs of workloads in any instance type. Amazon EC2 was the first major cloud provider that offered support for Intel, AMD, and Arm CPUs, as well as Mac instances and on-demand network throughput of over 400 Gbps.

Table of Contents

What is amazon ec2.

Amazon EC2 (Elastic Compute Cloud) is a cloud computing platform offered by Amazon Web Services (AWS), that allows businesses to quickly and easily build, deploy, scale, and manage computing resources such as virtual machines. With Amazon EC2, businesses can access servers on demand to help speed up development and reduce costs associated with maintaining their own physical infrastructure.

Setting Up an Amazon EC2 Instance

Setting up an instance on Amazon EC2 is easy and efficient. The first step is to go to the EC2 dashboard in the AWS Console and select “Launch Instance” from the menu. From there, you will be prompted to choose from a variety of Amazon Machine Images (AMI) that contain operating systems and other software packages. Once you have chosen an AMI, modify your instance settings, such as memory and storage size, to meet your operational needs. Finally, click “Review and Launch” and follow instructions on screen to complete the process.

Configuring Your EC2 Security Policy

Security is key when setting up an instance on Amazon EC2. In order to protect your data and prevent unauthorized access, it is important to configure proper security policies. Begin by configuring the identity access management (IAM) roles for this instance using the AWS IAM service and then create a security group that determines which traffic can reach your instance. You should also set up a Virtual Private Cloud (VPC) in which a subnet of devices can communicate securely and separately from public-facing networks. Finally, use Access Control Lists (ACLs) to specify acceptable levels of permissions and activities for your EC2 instance.

Using Amazon EC2 Auto-Scaling

To ensure optimal performance and reliability, it is important to deploy your instance with Amazon EC2 Auto-Scaling. This service allows you to automatically scale up or down your EC2 instances as needed. You can set a desired number of target instances, maximum capacity limit, minimum capacity limit and an autoscaling policy that specifies how the service should respond to changes in demand. Additionally, you can also configure advanced monitoring metrics such as CPU utilization and latency, which enable the auto scaler to scale up or down accordingly to prevent unexpected spikes or drops in performance.

The Benefits of Using Amazon EC2

Amazon EC2 provides resizable compute capacity in the cloud. Some benefits of using Amazon EC2 include:

Scalability

Amazon Elastic Compute Cloud allows you to increase or decrease the number of resources (virtual CPUs and memory) as needed, making it easy to handle changes in demand.

Flexibility

EC2 allows you to choose from various instance types, operating systems, and software packages, so you can choose the configuration that best meets your needs.

Cost-effectiveness

EC2 allows you to pay for only the resources you need when you need them, so you save time and money when compared to maintaining your own physical servers.

High availability

EC2 provides a number of configurations for ensuring high availability and fault tolerance, such as using multiple availability zones and load balancers.

EC2 provides various security features, such as security groups and network access control lists, to help you secure your instances and data.

Works with other AWS services

EC2 instances can easily integrate with other AWS services, making it easy to build and run complex applications in the cloud.

Bonus Tip: Automating EC2 Instances with AWS CloudFormation and Lambda Functions

AWS CloudFormation and  AWS Lambda  functions enable you to automate the scaling of your EC2 instances. With CloudFormation, you can define your desired EC2 instance runtime and capacity as a template that can be automated with simple Lambda functions. This allows you to quickly and easily manage large numbers of resources without having to manually adjust them daily. Additionally, Lambda functions can also use advanced metrics such as latency, CPU utilization and recent requests per second in order to determine when it is appropriate to scale up or down your EC2 infrastructure.

Micromanaging an Amazon RDS Instance means fine-tuning the configurations and settings to get the most performance out of your database. Here are a few tips and tricks to achieve optimal performance from an Amazon RDS instance.

• Enable automated backups to ensure that important data is regularly backed up.
• Set multiple availability zones for fault tolerance, meaning if one zone experiences an outage due to a natural disaster or failure, the other zones will remain operational.
• Configure CPU Credits to increase burst capacity – especially if your workloads spike during certain times of day or year.

Ready to mak the most of your Amazon EC2 Service?

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AWS Case Studies: Services and Benefits in 2024

Home Blog Cloud Computing AWS Case Studies: Services and Benefits in 2024

With its extensive range of cloud services, Amazon Web Services (AWS) has completely changed the way businesses run. Organisations demonstrate how AWS has revolutionized their operations by enabling scalability, cost-efficiency, and innovation through many case studies. AWS's computing power, storage, database management, and artificial intelligence technologies have benefited businesses of all sizes, from startups to multinational corporations. These include improved security, agility, worldwide reach, and lower infrastructure costs. With Amazon AWS educate program it helps businesses in various industries to increase growth, enhance workflow, and maintain their competitiveness in today's ever-changing digital landscape. So, let's discuss the AWS cloud migration case study   and its importance in getting a better understanding of the topic in detail.

What are AWS Case Studies, and Why are They Important?

The   AWS case   studies comprehensively explain how companies or organizations have used Amazon Web Services (AWS) to solve problems, boost productivity, and accomplish objectives. These studies provide real-life scenarios of Amazon Web Services (AWS) in operation, showcasing the wide range of sectors and use cases in which AWS can be successfully implemented. They offer vital lessons and inspiration for anyone considering or already using AWS by providing insights into the tactics, solutions, and best practices businesses use the AWS Cloud Engineer program . The Amazon ec2 case study   is crucial since it provides S's capabilities, assisting prospective clients in comprehending the valuable advantages and showcasing AWS's dependability, scalability, and affordability in fostering corporate innovation and expansion.

What are the Services Provided by AWS, and What are its Use Cases?

The   case study on AWS in Cloud Computing provided and its use cases mentioned:

Elastic Compute Cloud (EC2) Use Cases

Amazon Elastic Compute Cloud (EC2) enables you to quickly spin up virtual computers with no initial expenditure and no need for a significant hardware investment. Use the AWS admin console or automation scripts to provision new servers for testing and production environments promptly and shut them down when not in use.

AWS EC2 use cases consist of:

• With options for load balancing and auto-scaling, create a fault-tolerant architecture.
• Select EC2 accelerated computing instances if you require a lot of processing power and GPU capability for deep learning and machine learning.

Relational Database Service (RDS) Use Cases

Since Amazon Relational Database Service (Amazon RDS) is a managed database service, it alleviates the stress associated with maintaining, administering, and other database-related responsibilities.

AWS RDS uses common cases, including:

• Without additional overhead or staff expenditures, a new database server can be deployed in minutes and significantly elevate dependability and uptime. It is the perfect fit for complex daily database requirements that are OLTP/transactional.
• RDS should be utilized with NoSQL databases like Amazon OpenSearch Service (for text and unstructured data) and DynamoDB (for low-latency/high-traffic use cases).

AWS Workspaces

AWS offers Amazon Workspaces, a fully managed, persistent desktop virtualization service, to help remote workers and give businesses access to virtual desktops within the cloud. With it, users can access the data, apps, and resources they require from any supported device, anywhere, at any time.

AWS workspaces use cases

• IT can set up and manage access fast. With the web filter, you can allow outgoing traffic from a Workspace to reach your chosen internal sites.
• Some companies can work without physical offices and rely solely on SaaS apps. Thus, there is no on-premises infrastructure. They use cloud-based desktops via AWS Workspaces and other services in these situations.

AWS Case Studies

Now, we'll be discussing different case studies of AWS, which are mentioned below: -

Case Study - 1: Modern Web Application Platform with AWS

American Public Media, the programming section of Minnesota Public Radio, is one of the world's biggest producers and distributors of public television. To host their podcast, streaming music, and news websites on AWS, they worked to develop a proof of concept.

After reviewing an outdated active-passive disaster recovery plan, MPR decided to upgrade to a cloud infrastructure to modernize its apps and methodology. This infrastructure would need to be adaptable to changes within the technology powering their apps, scalable to accommodate their audience growth, and resilient to support their disaster recovery strategy.

MPR and AWS determined that MPR News and the public podcast websites should be hosted on the new infrastructure to show off AWS as a feasible choice. Furthermore, AWS must host multiple administrative apps to demonstrate its private cloud capabilities. These applications would be an image manager, a schedule editor, and a configuration manager.

To do this, AWS helped MPR set up an EKS Kubernetes cluster . The apps would be able to grow automatically according to workload and traffic due to the cluster. AWS and MPR developed Elasticsearch at Elastic.co and a MySQL instance in RDS to hold application data.

Business Benefits

Considerable cost savings were made possible by the upgraded infrastructure. Fewer servers would need to be acquired for these vital applications due to the decrease in hardware requirements. Additionally, switching to AWS made switching from Akamai CDN to CloudFront simple. This action reduced MPR's yearly expenses by thousands.

Case Study - 2: Platform Modernisation to Deploy to AWS

Foodsby was able to proceed with its expansion goals after receiving a $6 million investment in 2017, but it still needed to modernize its mobile and web applications. For a faster time to launch to AWS, they improved and enhanced their web, iOS, and Android applications.

Sunsetting technology put this project on a surged timeline. Selecting the mobile application platform required serious analysis and expert advice to establish consensus across internal stakeholders.

Improving the creation of front-end and back-end web apps that separated them into microservices to enable AWS hosting, maximizing scalability. Strengthening recommended full Native for iOS and Android and quickly creating and implementing that solution.

Case Study - 3: Cloud Platform with Kubernetes

SPS Commerce hired AWS to assist them with developing a more secure cloud platform, expanding their cloud deployment choices through Kubernetes, and educating their engineers on these advanced technologies.

SPS serves over 90,000 retail, distribution, grocery, and e-commerce businesses. However, to maintain its growth, SPS needs to remove obstacles to deploying new applications on AWS and other cloud providers in the future. They wanted a partner to teach their internal development team DevOps principles and reveal them to Kubernetes best practices, even though they knew Kubernetes would help them achieve this.

To speed up new project cycle times, decrease ramp-up times, and improve the team's Kubernetes proficiency, it assisted with developing a multi-team, Kubernetes-based platform with a uniform development method. The standards for development and deployment and assisted them in establishing the deployment pipeline.

Most teams can plug, play, and get code up and running quickly due to the streamlined deployment interface. SPS Commerce benefits from Kubernetes' flexibility and can avoid vendor lock-in, which they require to switch cloud providers.

Case Study - 4: Using Unified Payment Solutions to Simplify Government Services

The customer, who had a portfolio of firms within its authority, needed to improve experience to overcome the difficulty of combining many payment methods into a single, unified solution.

Due to the customers' varied acquisitions, the payment system landscape became fragmented, making it more difficult for clients to make payments throughout a range of platforms as well as technologies. Providing a streamlined payment experience could have been improved by this lack of coherence and standardization.

It started developing a single, cloud-based payment system that complies with the customers' microservices-based reference design. CRUD services were created after the user interface for client administration was set at the beginning of the project.

With this, the customer can streamline operations and increase efficiency by providing a smooth payment experience.

The new system demonstrated a tremendous improvement over the old capability, demonstrating the ability to handle thousands of transactions per second.

Maintaining system consistency and facilitating scalability and maintenance were made more accessible by aligning with the reference architecture.

Case Study - 5: Accelerated Data Migration to AWS

They selected improvements to create   an   AWS cloud migration case study cloud platform to safely transfer their data from a managed service provider to AWS during the early phases of a worldwide pandemic.

Early in 2020, COVID-19 was discovered, and telemedicine services were used to lessen the strain on hospital infrastructure. The number of telehealth web queries increased dramatically overnight, from 5,000 to 40,000 per minute. Through improvement, Zipnosis was able to change direction and reduce the duration of its AWS migration plan from six to three months. The AWS architecture case study includes HIPAA, SOC2, and HITRUST certification requirements. They also wanted to move their historic database smoothly across several web-facing applications while adhering to service level agreements (SLAs), which limited downtime.

Using Terraform and Elastic Kubernetes Service, the AWS platform creates a modern, infrastructure-as-code, HIPAA-compliant, and HITRUST-certified environment. With the help of serverless components, tools were developed to roll out an Application Envelope, enabling the creation of a HIPAA-compliant environment that could be activated quickly.

Currently, Zipnosis has internal platform management. Now that there is more flexibility, scaling up and down is more affordable and accessible. Their services are more marketable to potential clients because of their scalable, secure, and efficient infrastructure. Their use of modern technologies, such as Kubernetes on Amazon EKS, simplifies hiring top people. Zipnosis is in an excellent position to move forward.

Case Study - 6: Transforming Healthcare Staffing

The customer's outdated application presented difficulties. It was based on the outdated DBROCKET platform and needed an intuitive user interface, testing tools, and extensibility. Modernizing the application was improving the job and giving the customer an improved, scalable, and maintainable solution.

Although the customer's old application was crucial for predicting hospital staffing needs, maintenance, and improvements were challenging due to its reliance on the obscure DBROCKET platform. Hospitals lost money on inefficient staff scheduling due to the application's lack of responsiveness and a mobile-friendly interface.

Choosing Spring Boot and Groovy for back-end development to offer better maintainability and extensibility throughout the improved migration of the application from DBROCKET to a new technology stack. Unit tests were used to increase the reliability and standard of the code.

Efficiency at Catalis increased dramatically when the advanced document redaction technology was put in place. They were able to process papers at a significantly higher rate because the automated procedure cut down the time and effort needed for manual redaction.

Catalis cut infrastructure costs by utilizing serverless architecture and cloud-based services. They saved a significant amount of money because they were no longer required to upgrade and maintain on-premises servers.

The top-notch Knowledgehut best Cloud Computing courses that meet different demands and skill levels are available at KnowledgeHut. Through comprehensive curriculum, hands-on exercises, and expert-led instruction, attendees may learn about and gain practical experience with cloud platforms, including AWS, Azure, Google Cloud, and more. Professionals who complete these courses will be efficient to succeed in the quickly developing sector of cloud computing.

Finally,   a   case study of   AWS retail case studies offers a range of features and advantages. These studies show how firms in various industries use AWS for innovation and growth, from scalability to cost efficiency. AWS offers a robust infrastructure and a range of technologies to satisfy changing business needs, whether related to improving customer experiences with cloud-based solutions or streamlining processes using AI and machine learning. These case studies provide substantial proof of AWS's influence on digital transformation and the success of organizations.

Frequently Asked Questions (FAQs)

From the case study of Amazon web services, companies can learn how other businesses use AWS services to solve real-world problems, increase productivity, cut expenses, and innovate. For those looking to optimize their cloud strategy and operations, these case studies provide insightful information, optimal methodologies, and purpose. 

You can obtain case studies on AWS through the AWS website, which has a special section with a large selection of case studies from different industries. In addition, AWS releases updated case studies regularly via various marketing platforms and on its blog.

The case study of Amazon web services, which offers specific instances of how AWS services have been successfully applied in various settings, can significantly assist in the decision-making process for IT initiatives. Project planning and strategy can be informed by the insights, best practices, and possible solutions these case studies provide.

Kingson Jebaraj

Kingson Jebaraj is a highly respected technology professional, recognized as both a Microsoft Most Valuable Professional (MVP) and an Alibaba Most Valuable Professional. With a wealth of experience in cloud computing, Kingson has collaborated with renowned companies like Microsoft, Reliance Telco, Novartis, Pacific Controls UAE, Alibaba Cloud, and G42 UAE. He specializes in architecting innovative solutions using emerging technologies, including cloud and edge computing, digital transformation, IoT, and programming languages like C, C++, Python, and NLP. 

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