Amazon S3 - Amazon Web Services - Amazon Cloud

Amazon S3 - Amazon Web Services - Amazon Cloud

Amazon Web Services

     Amazon Simple Storage Service (Amazon S3), AWS cloud is an object storage service that offers scalability, data availability, security, and performance. 

     Customers of all sizes and industries can use the service to store and protect any amount of data for a wide range of use cases such as websites, mobile applications, backup and recovery, archiving, enterprise applications, IoT devices, and big data analytics. 

     Amazon S3 provides easy-to-use management features to allow you to organize your data and configure refined access controls for your specific business, organizational, and compliance requirements.

     Amazon S3 is designed to deliver 99.999999999% (11 9) durability and store data from millions of applications for businesses around the world.

State-of-the-art performance, scalability, availability, and durability

     Scale your resources up or down to meet fluctuations in demand without up-front investments or resource acquisition cycles. 

     Amazon S3 is designed to offer 99.999999999% (11 9) data durability, as it automatically creates and stores copies of all S3 objects across multiple systems. 


     This means your data is available when you need it and is protected against failures, errors, and threats.

Wide range of economical storage classes

     Reduce costs without sacrificing performance by storing data in different S3 storage classes that support different levels of data access at corresponding rates. 

     You can use the S3 storage class analysis functionality to discover which data should be transferred to a lower-cost storage class based on access patterns and configure an S3 lifecycle strategy to execute the transfer. 


     You can also store data with changing or unknown access patterns in S3 Intelligent-Tiering, which prioritizes objects based on changing access patterns and allows you to automatically take advantage of cost savings.

On-site query services for analysis

     Run Big Data analyses on your S3 objects (and other datasets in AWS) with on-site query services. 

     Use Amazon Athena - AWS Athena - to query S3 data with standard SQL expressions and Amazon Redshift Spectrum to analyze data that is stored in your AWS data warehouses and S3 resources. 


     You can also use S3 Select to extract subsets of object data, instead of the entire object, and improve query performance by up to 400%.

How it works - S3 access points

     Amazon S3 Access Points simplify the overall management of data access for applications by using shared data sets on S3. 

     With S3 Access Points, you can now easily create hundreds of access points per compartment and benefit from a new way to provide access to shared datasets. 


     Access Points provide a personalized path to a compartment, with a unique user name and an access policy that enforces specific network permissions and controls for any queries made through the Access Point.

Use cases

Backup and restore

     Create scalable, sustainable, and secure backup and recovery solutions with Amazon S3 and other AWS services, such as S3 Glacier, Amazon EFS, and Amazon EBS, to augment or replace your existing onsite capabilities. 

    AWS and APN partners can help you meet your recovery time objective (RTO), recovery point objective (RPO) and compliance requirements. 


     With AWS, you can back up data already in the AWS cloud, or use AWS Storage Gateway, a hybrid storage service, to send onsite backups to AWS.

Disaster Recovery

     Protect critical data, applications, and IT systems running in the AWS cloud or your on-premises environment without the expense of a second physical site. 


     With Amazon S3 storage, S3 region-to-region replication, and other AWS computing, networking, and database services, you can create disaster recovery architectures to recover quickly and easily from outages caused by natural disasters, system failures, and human error.

Data Lakes and Big Data Analysis

     Accelerate innovation by developing a data lake in Amazon S3, and extract valuable information using on-site queries, analysis, and machine learning tools. 

     As your data lake grows, use S3 Access Points to easily configure access to your data, with specific permissions for each application or set of applications. 

     You can also use AWS Lake Formation to quickly create a data lake and centrally define and enforce security, governance, and auditing policies. 

     The service collects data from your S3 databases and resources, transfers it to a new data lake in Amazon S3, and cleans and classifies it using automated learning algorithms. 


     All AWS resources can be scaled up to accommodate the expansion of your data stores, with no up-front investment.

Hybrid storage in the cloud

     
     Create a seamless connection between on-premise applications and Amazon S3 with AWS Storage Gateway to reduce your data center footprint, and take advantage of AWS's scale, reliability, and durability, as well as AWS's innovative auto-learning and analysis capabilities. 

     You can also automate data transfers between on-site storage and Amazon S3 using AWS DataSync, which can transfer data at speeds up to 10 times faster than open-source tools. 

     Another way to set up a hybrid cloud storage environment is to collaborate with an APN gateway provider. 


     You can also transfer files directly to and from Amazon S3 with AWS Transfer for SFTP, a managed service that enables secure file exchanges with third parties.

Native Cloud Application Data

     Create cost-effective, mobile, and Internet-based applications using AWS and Amazon S3 to store production data. 

     With Amazon S3, you can upload and access any amount of data from anywhere to deploy applications faster and reach more end users. 


     Storing data in Amazon S3 also means you have access to the latest developer tools and AWS services for machine learning and analysis to innovate and optimize your native cloud applications.

Case Studies

     Netflix delivers billions of hours of content from Amazon S3 to customers around the world. Amazon S3 also serves as the data lake for the company's Big Data analytics solution.

     FINRA uses Amazon S3 to integrate and store data for more than 75 billion market events every day with AWS Lambda functions to format and validate data according to more than 200 rules.

     Airbnb hosts backup data and static files on Amazon S3, including more than 10 petabytes of user images.

Born in the cloud, the solution is constantly innovating to find new ways to analyze data stored on Amazon S3.

    GE uses Amazon S3 to store and protect one petabyte of sensitive medical imaging data for its GE Health Cloud service, which connects hundreds of thousands of imaging machines and other medical devices.

Share:

Read More

Understanding Cloud Services

          Understanding Cloud Services

     Cloud Computing is a general term used to refer to the delivery of on-demand resources and services over the Internet.

     When you watch a streaming movie on Netflix, all you need is your PC's browser and an internet connection, nothing else! That's because all the movies you have available are hosted on Netflix! And Netflix provides you with this on-demand movie catalog as a service and you pay for this service.

     So when we say that a service is in the cloud it means that the production resources to provide that service are hosted by the cloud provider.

     So the cloud is a model where we consume computing resources like any other utility... Well, now you can consume computing power, servers, applications or storage space. 

     In short, all types of computing resources and all this without having the technical infrastructure that is at the cloud provider and these computing services are accessible via a wide area network such as the Internet.

     The first thing to remember about the cloud is that it is above all a business model that uses existing technologies.

     Because of the technical side, there's really nothing new, but what is new are the concepts on which this cloud model is based.

          The four essential characteristics of the cloud 

     The first characteristic is that cloud service is, first of all, an on-demand service. This means that a customer must be able to make a request for any type of resource at any time, the response from the cloud must be immediate, and all this is possible because everything is computerized in the cloud.

     The second essential characteristic is that the cloud is a measurable service, which means that both the customer and the supplier must be able to measure the use made of resources. 

     For the customer, this allows him to know what all the resources they consume are, and this is all the more important because, in the cloud model, a customer only pays for what he uses, the other strength of the cloud is that it allows the pooling of resources.

     A cloud host has huge IT resources and its resources are shared between all its customers according to demand. And all this without anyone knowing where the consumed resource is located.

     Pooling allows elasticity in cloud resources by automatically adapting resources to variations in demand.

     And the last principle of the cloud precisely resources elasticity, and the elasticity of cloud resources is the ability to dynamically allocate resources according to needs, whether upwards, downwards, permanently or temporarily, and very quickly.

     Now that you have understood what the cloud is, let's focus a little more on the services that the cloud provides, there are several types of services and these services are categorized according to the technical layer provided, there are three models of cloud use, each of these models plays a specific role.

     The IAAS (Infrastructure As A Service) corresponds to the infrastructure part of the cloud More concretely, it provides OS instances and the entire underlying infrastructure, such as servers, network or storage. 

     In the case of use, for example, a temporary VM is made available for testing or storage expansion in this model, the user or customer of the service has to manage the addition of middleware and applications and the rest is managed by the cloud provider.

     Given the use case, the target population for the IAAS is IT operators.

     The PAAS (Platform As A Service) provides, in addition to the technical infrastructure such as the IAAS, integrated software components such as middleware instances and runtime bases, e.g. application servers or databases. 

     In this model, the service user or customer has to manage the addition of the applications - this offer, therefore, allows us to focus on the development of the applications.

     Developers are therefore the target population of the PAAS In PAAS, we have for example open-shift and Windows Azure platforms. 

     Finally, SAAS (Software As A Service) provides ready-to-use applications running on the cloud provider's infrastructure and accessible via the customer's browser. 

     As a use case one has for example access to online or office messaging, of course, the end-users are the target population of SAAS. In SAAS, we have everything that is google docs or office 365.          

Hosting mode

      The cloud comes in different hosting modes, each hosting mode will have an impact on the essential characteristics of the cloud.

     First of all, there is the public cloud, which is a model where the technical infrastructure will be outsourced to a third-party provider, in which case the IT resources will be open to all and shared. This is the flagship model of the cloud and the one we have seen so far.

     Then there is the private cloud, which corresponds to a model where all resources are reserved for the exclusive use of a single company. In this case, the main limitation is the resources and means that the company will make available for its own cloud.

     The main interest of the private cloud is that it allows meeting legal constraints, security needs or simply a desire of the company to keep control of its technical infrastructure. 

     Finally, there is the hybrid cloud, which is a mix of private and public clouds, i.e. having dedicated resources internally and public resources externally. The aim is to be able to respond to occasional peaks in load.

Share:

Read More