Serverless cloud computing: Introduction

Lately, there's been a buzz in the IT world about "Serverless" technologies. The term can be a bit misleading, because there is still a server machine doing server-side processing; the key difference is that when we talk about a "serverless" environment, the whole server infrastructure is managed by a third party. In a serverless environment, a developer only needs to provide his custom server-side code, and the platform will take care of running it when suitable. This takes the concept of cloud computing taking things off developer's hands a bit further. Let's recall those different kinds of cloud offerings and try to fit serverless there:

  • IaaS: Infastructure as a Service. The cloud vendor offers an interface for the users to manage their infrastructure: servers, databases, and networks, using a special interface. That way, the user can allocate and consume computational resources using a pay-as-you-go model. This is the model where the user has the most power: he can configure applications, their data, runtime, middleware and OSes; some cloud providers also offer databases, messaging queues and other services. Those which do are sometimes called IaaS+-kind of cloud services. The common use case for this type of solution is to offload datacenter infrastructure management to a third party in order to focus on the application itself. Examples: AWS (Amazon Web Services), Microsoft Azure, Google Compute Engine, Joyent.
  • PaaS: Platform as a Service. The cloud vendor offers a programming framework for developers. The vendor takes care of maintaining the framework and its infrastructure, and the developers take care of their applications built using the framework. The common use case for this type of solution is leveraging the existing framework to reduce development time and time-to-market. Example: Apprenda
  • Baas/FaaS/Serverless: Backend as a Service. Here, the only aspect that the user controls is which code gets run on the server/backend. Everything else is handled by the cloud provider. That's why I put this between PaaS and SaaS. However, a distinction must be made between BaaS and FaaS (see next paragraph).
  • SaaS: Software as a Service. The cloud vendor offers a set of pre-made applications hosted in their own cloud which can be used directly. The client only has access to those apps' interface, and the vendor is fully in charge of mantaining those apps and their infrastructure. The common use case for this type of solution is replacing traditional on-device software, which relieves the user from the hassle of installing and updating. Examples: Google Apps, Salesforce, Citrix GTM, Cisco WebEx.

Mike Roberts, from martinfowler.com, makes a distinction between two types of Serverless cloud computing architectures:

  • BaaS: Backend as a Service. An application built on top of a BaaS cloud service delegates most of the server-side logic and state to the cloud provider.
  • FaaS: In a FaaS environment, the user still writes most of the server side code, but unlike the traditional environments, that code is ran by the cloud provider in ephemeral containers, breaking the mold of the "always on" server. Basically, FaaS is about running server-side code without managing your own servers or server applications. This gives the cloud provider higher flexibility in assigning its computing resources.

The most popular FaaS offerings Amazon Lambda (from AWS) and Microsoft Azure functions (from Azure).

Further reading including architecture examples:

Comments

  1. UnknownDecember 18, 2017 at 3:44 AM

    Like To Read your Post Because Your Post Is very interesting thank you so much give us information keep posting good luck ……………….
    http://www.shikharoy.in/air-hostess-call-girls-aerocity.html
    http://www.shikharoy.in/russian-call-girls-dwarka.html
    http://www.shikharoy.in/russian-call-girls-mahipalpur.html
    http://www.shikharoy.in/nehru-place-call-girls.html
    http://www.shikharoy.in/escort-services-in-delhi.html
    http://www.shikharoy.in/call-girls-greater-noida.html
    http://www.shikharoy.in/model-call-girls-saket.html
    http://www.shikharoy.in/call-girls-in-gurgaon.html

    ReplyDelete

Post a Comment

Popular posts from this blog

VB.NET: Raise base class events from a derived class

Spanish version / Versión en Español Say we: Have a class we want to divide into subclasses The future base class has events The refactoring leads us to the need of raising an event declared in the base class, from a derived class. When we try to do point 3, we will get a compile error saying that a derived class cannot raise events from a base class. To get around this, we add a protected method in the base class which encapsulates the RaiseEvent call, and call that method from the derived class using MyBase. This way: In the base class (parameters as needed): Protected Overridable Sub OnMessageGenerated(ByVal NewSender As Object, ByVal NewMessage As String) RaiseEvent MessageGenerated(NewSender, New MessageEventArgs(NewMessage)) End Sub And in the derived class: 'Do stuff 'Raise base class event MyBase.OnMessageGenerated( Me, "Message" ) 'Do more stuff... References: Mark Gilbert post
Keep reading

Apache Kafka - I - High level architecture and concepts

Image
Spanish version / Versión en Español First of all, what is Apache Kafka ? An initial definition for it is "a high-throughput distributed messaging system". Breaking this down a bit: High throughput: One of the main goals of Kafka is to process as much messages per unit of time as possible, in a scalable and fault-tolerant way. For example, LinkedIn , which is where Kafka originated, needs to achieve throughputs in the order of 20 million messages per second and 3 GB of data per second. Distributed messaging system: In a generic distributed system , networked computers work together for a common goal. In Kafka's case, that goal is to send data from points A 1 , A 2 , ... A N , to B 1 , B 2 , ... B M . A common benefit of this kind of system, which is crucial to Kafka's success, is horizontal scalability : the ability to handle higher and higher volumes of data by adding nodes to the system (not to be confused with  vertical scalability , whic
Keep reading

Upgrading Lodash from 3.x to 4.x

Spanish version / Versión en Español There are many breaking changes from version 3.x to 4.x; all changes are detailed in the Lodash changelog . There is also a list of deprecated functions , with a regex you can use to detect usages in your code. However, since it is not an exhaustive list, I will list the changes I encountered when performing my own migration, to help anyone undergoing the same process. Direct renames This section includes functions in which only the name changed, i.e. the arguments and return value are the same. 3.x 4.x contains includes first head rest tail invoke invokeMap padLeft padStart padRight padEnd Direct renames if not using thisArg This section includes functions in which the only change is dropping "thisArg". If you are not using it, you can just rename. If you are using thisArg in 3.x, it can be dropped if you are using iteratee to acce
Keep reading