Cloud storage works on a client-server model, in which a client sends the request to the subscribed cloud service storage and the server at the data center gives the appropriate response. The main objective of the cloud, instead of saving data at local storage, the data of the user can be collected at some data center so the user could retrieve his or her data from any device.
What if the data center of the cloud service provider collapses or gets destroyed, would the user data also be destroyed? The answer is no. The cloud storage depends on hundreds of data centers, so even if one of the data centers collapses, there are hundreds of centers that would help you to retrieve and save your data.
S3 in AWS
Amazon Simple Storage Service (Amazon S3) is an object storage service that offers industry-leading scalability, data availability, security, and performance. You can use Amazon S3 to store and retrieve any amount of data at any time, from anywhere.
Amazon Simple Storage Service (Amazon S3) is an object storage service that offers industry-leading scalability, data availability, security, and performance. Customers of all sizes and industries can use Amazon S3 to store and protect any amount of data for a range of use cases, such as data lakes, websites, mobile applications, backup and restore, archive, enterprise applications, IoT devices, and big data analytics. Amazon S3 provides management features so that you can optimize, organize, and configure access to your data to meet your specific business, organizational, and compliance requirements.
Features of Amazon S3
Amazon S3 offers a range of storage classes designed for different use cases. For example, you can store mission-critical production data in S3 Standard for frequent access, save costs by storing infrequently accessed data in S3 Standard-IA or S3 One Zone-IA, and archive data at the lowest costs in S3 Glacier Instant Retrieval, S3 Glacier Flexible Retrieval, and S3 Glacier Deep Archive.
Amazon S3 has storage management features that you can use to manage costs, meet regulatory requirements, reduce latency, and save multiple distinct copies of your data for compliance requirements.
- S3 Lifecycle: Configure a lifecycle policy to manage your objects and store them cost effectively throughout their lifecycle. You can transition objects to other S3 storage classes or expire objects that reach the end of their lifetimes.
- S3 Object Lock: Prevent Amazon S3 objects from being deleted or overwritten for a fixed amount of time or indefinitely. You can use Object Lock to help meet regulatory requirements that require write-once-read-many (WORM) storage or to simply add another layer of protection against object changes and deletions.
- S3 Replication: Replicate objects and their respective metadata and object tags to one or more destination buckets in the same or different AWS Regions for reduced latency, compliance, security, and other use cases.
- S3 Batch Operations: Manage billions of objects at scale with a single S3 API request or a few clicks in the Amazon S3 console. You can use Batch Operations to perform operations such as Copy, Invoke AWS Lambda function, and Restore on millions or billions of objects.
Google App Engine
Google App Engine (often referred to as GAE or simply App Engine) is a cloud computing platform as a service for developing and hosting web applications in Google-managed data centers. Applications are sandboxed and run across multiple servers. App Engine offers automatic scaling for web applications as the number of requests increases for an application, App Engine automatically allocates more resources for the web application to handle the additional demand.
Google App Engine primarily supports Go, PHP, Java, Python, Node.js, .NET, and Ruby applications, although it can also support other languages via “custom runtimes”. The service is free up to a certain level of consumed resources and only in standard environment but not in flexible environment. Fees are charged for additional storage, bandwidth, or instance hours required by the application. It was first released as a preview version in April 2008 and came out of preview in September 2011.
- Developers have read-only access to the filesystem on App Engine. Applications can use only virtual filesystems, like gae-filestore.
- App Engine can only execute code called from an HTTP request (scheduled background tasks allow for self calling HTTP requests).
- Users may upload arbitrary Python modules, but only if they are pure-Python; C and Pyrex modules are not supported.
- Java applications may only use a subset (The JRE Class White List) of the classes from the JRE standard edition. This restriction does not exist with the App Engine Standard Java8 runtime.
- A process started on the server to answer a request can’t last more than 60 seconds (with the 1.4.0 release, this restriction does not apply to background jobs anymore).
- Does not support sticky sessions (a.k.a. session affinity), only replicated sessions are supported including limitation of the amount of data being serialized and time for session serialization.
Microsoft Azure, often referred to as Azure is a cloud computing service operated by Microsoft for application management via Microsoft-managed data centers. It provides software as a service (SaaS), platform as a service (PaaS) and infrastructure as a service (IaaS) and supports many different programming languages, tools, and frameworks, including both Microsoft-specific and third-party software and systems.
Azure, announced at Microsoft’s Professional Developers Conference (PDC) in October 2008, went by the internal project codename “Project Red Dog”, and formally released in February 2010, as Windows Azure before being renamed to Microsoft Azure on March 25, 2014.
Microsoft Azure uses a specialized operating system, called Microsoft Azure, to run its “fabric layer”: a cluster hosted at Microsoft’s data centers that manage computing and storage resources of the computers and provisions the resources (or a subset of them) to applications running on top of Microsoft Azure. Microsoft Azure has been described as a “cloud layer” on top of a number of Windows Server systems, which use Windows Server 2008 and a customized version of Hyper-V, known as the Microsoft Azure Hypervisor to provide virtualization of services.
Scaling and reliability are controlled by the Microsoft Azure Fabric Controller, which ensures the services and environment do not fail if one or more of the servers fails within the Microsoft data center, and which also provides the management of the user’s Web application such as memory allocation and load balancing.
Azure provides an API built on REST, HTTP, and XML that allows a developer to interact with the services provided by Microsoft Azure. Microsoft also provides a client-side managed class library that encapsulates the functions of interacting with the services. It also integrates with Microsoft Visual Studio, Git, and Eclipse.
In addition to interacting with services via API, users can manage Azure services using the Web-based Azure Portal, which reached General Availability in December 2015. The portal allows users to browse active resources, modify settings, launch new resources, and view basic monitoring data from active virtual machines and services.