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.
AWS EC2 (Elastic Compute Cloud)
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.
What is Amazon EC2 (Elastic Compute Cloud)?
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).
Use Cases of Amazon EC2 (Elastic Compute 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
AWS EC2 Instance Types
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.
Features of AWS EC2 (Elastic Compute Cloud)
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.
Windows Server
Ubuntu Server
SUSE Linux
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.
Pricing of AWS EC2 (Elastic Compute Cloud) Instance
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.
Create AWS Free Tier Account
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.
Get Started With Amazon EC2 (Elastic Compute Cloud) Linux Instances
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.
Benefits of Amazon EC2
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.
Best Practices of Amazon EC2
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.
Use Cases of Amazon EC2 (Elastic Compute 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
Introduction to AWS Simple Storage Service (AWS S3).
AWS offers a wide range of storage services that can be configured depending on your project requirements and use cases. AWS comes up with different types of storage services for maintaining highly confidential data, frequently accessed data, and often accessed storage data. You can choose from various storage service types such as Object Storage as a Service(Amazon S3), File Storage as a Service (Amazon EFS), Block Storage as a Service (Amazon EBS), backups, and data migration options.
What is Amazon S3?
Amazon S3 is a Simple Storage Service in AWS that stores files of different types like Photos, Audio, and Videos as Objects providing more scalability and security to. It allows the users to store and retrieve any amount of data at any point in time from anywhere on the web. It facilitates features such as extremely high availability, security, and simple connection to other AWS Services.
What is Amazon S3 Used for?
Amazon S3 is used for various purposes in the Cloud because of its robust features with scaling and Securing of data. It helps people with all kinds of use cases from fields such as Mobile/Web applications, Big data, Machine Learning and many more. The following are a few Wide Usage of Amazon S3 service.
Data Storage: Amazon s3 acts as the best option for scaling both small and large storage applications. It helps in storing and retrieving the data-intensitive applications as per needs in ideal time.
Backup and Recovery: Many Organizations are using Amazon S3 to backup their critical data and maintain the data durability and availability for recovery needs.
Hosting Static Websites: Amazon S3 facilitates in storing HTML, CSS and other web content from Users/developers allowing them for hosting Static Websites benefiting with low-latency access and cost-effectiveness. To know more detailing refer this Article – How to host static websites using Amazon S3
Data Archiving: Amazon S3 Glacier service integration helps as a cost-effective solution for long-term data storing which are less frequently accessed applications.
Big Data Analytics: Amazon S3 is often considered as data lake because of its capacity to store large amounts of both structured and unstructured data offering seamless integration with other AWS Analytics and AWS Machine Learning Services.
What is an Amazon S3 bucket?
Amazon S3 bucket is a fundamental Storage Container feature in AWS S3 Service. It provides a secure and scalable repository for storing of Objects such as Text data, Images, Audio and Video files over AWS Cloud. Each S3 bucket name should be named globally unique and should be configured with ACL (Access Control List).
How Does Amazon S3 works?
Amazon S3 works on organizing the data into unique S3 Buckets, customizing the buckets with Acccess controls. It allows the users to store objects inside the S3 buckets with facilitating features like versioning and lifecycle management of data storage with scaling. The following are a few main features of Amazon s3:
1. Amazon S3 Buckets and Objects
Amazon S3 Bucket: Data, in S3, is stored in containers called buckets. Each bucket will have its own set of policies and configurations. This enables users to have more control over their data. Bucket Names must be unique. Can be thought of as a parent folder of data. There is a limit of 100 buckets per AWS account. But it can be increased if requested by AWS support.
Amazon S3 Objects: Fundamental entity type stored in AWS S3.You can store as many objects as you want to store. The maximum size of an AWS S3 bucket is 5TB. It consists of the following:
Key
Version ID
Value
Metadata
Subresources
Access control information
Tags
2. Amazon S3 Versioning and Access Control
S3 Versioning: Versioning means always keeping a record of previously uploaded files in S3. Points to Versioning are not enabled by default. Once enabled, it is enabled for all objects in a bucket. Versioning keeps all the copies of your file, so, it adds cost for storing multiple copies of your data. For example, 10 copies of a file of size 1GB will have you charged for using 10GBs for S3 space. Versioning is helpful to prevent unintended overwrites and deletions. Objects with the same key can be stored in a bucket if versioning is enabled (since they have a unique version ID). To know more about versioning refer this article – Amazon S3 Versioning
Access control lists (ACLs): A document for verifying access to S3 buckets from outside your AWS account. An ACL is specific to each bucket. You can utilize S3 Object Ownership, an Amazon S3 bucket-level feature, to manage who owns the objects you upload to your bucket and to enable or disable ACLs.
3. Bucket policies and Life Cycles
Bucket Policies: A document for verifying the access to S3 buckets from within your AWS account, controls which services and users have what kind of access to your S3 bucket. Each bucket has its own Bucket Policies.
Lifecycle Rules: This is a cost-saving practice that can move your files to AWS Glacier (The AWS Data Archive Service) or to some other S3 storage class for cheaper storage of old data or completely delete the data after the specified time. To know more about refer this article – Amazon S3 Life Cycle Management
4. Keys and Null Objects
Keys: The key, in S3, is a unique identifier for an object in a bucket. For example in a bucket ‘ABC’ your GFG.java file is stored at javaPrograms/GFG.java then ‘javaPrograms/GFG.java’ is your object key for GFG.java.
Null Object: Version ID for objects in a bucket where versioning is suspended is null. Such objects may be referred to as null objects.List) and Other settings for managing data efficiently.
How To Use an Amazon S3 Bucket?
You can use the Amazon S3 buckets by following the simple steps which are mentioned below. To know more how to configure about Amazon S3 refer to the Amazon S3 – Creating a S3 Bucket.
Step 1: Login into the Amazon account with your credentials and search form S3 and click on the S3. Now click on the option which is “Create bucket” and configure all the options which are shown while configuring.
Step 2: After configuring the AWS bucket now upload the objects into the buckets based upon your requirement. By using the AWS console or by using AWS CLI following is the command to upload the object into the AWS S3 bucket.
aws s3 cp <local-file-path> s3://<bucket-name>/
Step 3: You can control the permissions of the objects which was uploaded into the S3 buckets and also who can access the bucket. You can make the bucket public or private by default the S3 buckets will be in private mode.
Step 4: You can manage the S3 bucket lifecycle management by transitioning. Based upon the rules that you defined S3 bucket will be transitioning into different storage classes based on the age of the object which is uploaded into the S3 bucket.
Step 5: You need to turn to enable the services to monitor and analyze S3. You need to enable the S3 access logging to record who was requesting the objects which are in the S3 buckets.
What are the types of S3 Storage Classes?
AWS S3 provides multiple storage types that offer different performance and features and different cost structures.
Standard: Suitable for frequently accessed data, that needs to be highly available and durable.
Standard Infrequent Access (Standard IA): This is a cheaper data-storage class and as the name suggests, this class is best suited for storing infrequently accessed data like log files or data archives. Note that there may be a per GB data retrieval fee associated with the Standard IA class.
Intelligent Tiering: This service class classifies your files automatically into frequently accessed and infrequently accessed and stores the infrequently accessed data in infrequent access storage to save costs. This is useful for unpredictable data access to an S3 bucket.
One Zone Infrequent Access (One Zone IA): All the files on your S3 have their copies stored in a minimum of 3 Availability Zones. One Zone IA stores this data in a single availability zone. It is only recommended to use this storage class for infrequently accessed, non-essential data. There may be a per GB cost for data retrieval.
Reduced Redundancy Storage (RRS): All the other S3 classes ensure the durability of 99.999999999%. RRS only ensures 99.99% durability. AWS no longer recommends RRS due to its less durability. However, it can be used to store non-essential data.
To know more about , refer this article – Amazon S3 Storage Classes
How to Upload and Manage Files on Amazon S3?
Firstly you have to Amazon s3 bucket for uploading and managing the files on Amazon S3. Try to create the S3 Bucket as discussed above. Once the S3 Bucket is created, you can upload the files through various ways such as AWS SDKs, AWS CLI, and Amazon S3 Management Console. Try managing the files by organizing them into folders within the S3 Bucket and applying access controls to secure the access. Features like Versioning and Lifecycle policies provide the management of data efficiently with optimization of storage classes.
To know more detailing refer this article – How to Store and Download Obejcts in Amazon S3?
How to Access Amazon S3 Bucket?
You can work and access the Amazon S3 bucket by using any one of the following methods
AWS Management Console
AWS CLI Commands
Programming Scripts ( Using boto3 library of Python )
1. AWS Management Console
You can access the AWS S3 bucket using the AWS management console which is a web-based user interface. Firstly you need to create an AWS account and login to the Web console and from there you can choose the S3 bucket option from Amazon S3 service. ( AWS Console >> Amazon S3 >> S3 Buckets )
2. AWS CLI Commands
In this methods firstly you have to install the aws cli software in the terminal and try on configuring the aws account with access key, secret key and the default region. Then on taking the aws –help , you can figure out the s3 service usage. For example , To view try on running following command:
aws s3 ls
3. Programming scripts
You can configure the Amazon S3 bucket by using a scripting programing languages like Python and with using libraries such as boto3 library you can perform the AWS S3 tasks. To know more about refer this article – How to access Amazon S3 using python script.
AWS S3 Bucket Permissions
You can manage the permission of S3 buckets by using several methods following are a few of them.
Bucket Policies: Bucket policies can be attached directly to the S3 bucket and they are in JSON format which can perform the bucket level operations. With the help of bucket policies, you can grant permissions to the users who can access the objects present in the bucket. If you grant permissions to any user he can download, and upload the objects to the bucket. You can create the bucket policy by using Python.
Access Control Lists (ACLs): ACLs are legacy access control mechanisms for S3 buckets instead of ACLs we are using the bucket policies to control the permissions of the S3 bucket. By using ACL you can grant the read, and access to the S3 bucket or you can make the objects public based on the requirements.
IAM Policies: IAM policies are mostly used to manage the permissions to the users and groups and resources available in the AWS by using the IAM roles options. You can attach an IAM policy to an IAM entity (user, group, or role) granting them access to specific S3 buckets and operations.
The most effective way to control the permissions to the S3 buckets is by using bucket policies.
Features of Amazon S3
Durability: AWS claims Amazon S3 to have a 99.999999999% of durability (11 9’s). This means the possibility of losing your data stored on S3 is one in a billion.
Availability: AWS ensures that the up-time of AWS S3 is 99.99% for standard access.
- Note that availability is related to being able to access data and durability is related to losing data altogether.
Server-Side-Encryption (SSE): AWS S3 supports three types of SSE models:
SSE-S3: AWS S3 manages encryption keys.
SSE-C: The customer manages encryption keys.
SSE-KMS: The AWS Key Management Service (KMS) manages the encryption keys.
File Size support: AWS S3 can hold files of size ranging from 0 bytes to 5 terabytes. A 5TB limit on file size should not be a blocker for most of the applications in the world.
Infinite storage space: Theoretically AWS S3 is supposed to have infinite storage space. This makes S3 infinitely scalable for all kinds of use cases.
Pay as you use: The users are charged according to the S3 storage they hold.
Advantages of Amazon S3
Scalability: Amazon S3 can be scalable horizontally which makes it handle a large amount of data. It can be scaled automatically without human intervention.
High availability: AmazonS3 bucket is famous for its high availability nature you can access the data whenever you required it from any region. It offers a Service Level Agreement (SLA) guaranteeing 99.9% uptime.
Data Lifecycle Management: You can manage the data which is stored in the S3 bucket by automating the transition and expiration of objects based on predefined rules. You can automatically move the data to the Standard-IA or Glacier, after a specified period.
Integration with Other AWS Services: You can integrate the S3 bucket service with different services in the AWS like you can integrate with the AWS lambda function where the lambda will be triggered based upon the files or objects added to the S3 bucket.