4. TOP SKILLS
(ORDERED BY ANTICIPATED DEMAND)
Programming
Languages
1. Java : Cloud Services,
Big-Data, IoT
2. Python : IaaS, Cloud
Services, IoT
3. C#/.Net : Cloud Services
4. Javascript : Cloud
Services
Platforms/
Products
1. Hadoop : Big Data, IoT
2. OpenStack : IaaS
3. AWS : Cloud Services,
Big Data, IoT
4. LAMP : Big Data, Cloud
Services
5. Mongo DB : IoT, Cloud
Services
6. Xively : IOT
Concepts/Design
Patterns
1. Virtualization : IaaS
2. Web Services : Cloud
Services, IoT
3. ETL : Big Data, IoT
4. Messaging : IoT, Big
Data
5. NoSQL : IoT, Big Data
Hinweis der Redaktion
IaaS: a software layer that runs across multiple compute/storage nodes in a data center. All hardware is abstracted into one big pool of resources. IaaS then allocates the resources as of Virtual Machines and Storage containers. Though hardware is abstracted, users still interact with discrete machines with complete OS level access. PaaS : Adds a layer of software on top of the IaaS to provide a hosting environment. PaaS saves application developers from having to deal with individual VMs. Instead, the developers deploy their application into a environment that is ready with all the required software and services required to run the application. Computing resources are dynamically allocated behind the scenes. In a PaaS environment, OS level access is limited so it is not a good choice for any application with bespoke hosting requirements. SaaS: Providing software and services to the end users on pay-per-view basis. Instead of customers purchasing a software outright, they only pay for what they use. Customers do not have to worry about developing, deploying & maintaining the software or services. The infrastructure and scaling is taken care of by the Software/Service provider as well.Cloud Computing Wikipedia page : http://en.wikipedia.org/wiki/Cloud_computing
IoT and cloud : Internet of things involves gathering large amount of data in small bits from millions of small devices. This typically involves having an API to which devices can connect and push data to and a Messaging service which then publishes data to those who require it. Simply due to the numbers (devices, messages) involved, it makes perfect sense to use cloud to ensure the system can easily scale.Big-Data and Cloud : Big-data typically means gathering large amount of data, processing it and glean useful information. Such systems handle data in petabyte scale and need clusters with hundreds or thousands of machines to store and process the data. Cloud makes it much easier to provision and manage such large clusters. Both in IoT space and Big Data space, number of product choices available is very wide, with many of the products optimized for specific use cases. This is because, performance is seen as the overwhelmingly key consideration. Thus architectural choices will make or break a project. Many of the available products/components choices are open source options. This and the fact that focus is on performance means other aspects like security are weak and will need more work than usual when implementing a solution.
Above represent only a small subset of cloud related technologies but likely to be in demand at the given moment.Many of the above require basic Linux skills as a pre-requisite.LAMP – Linux-Apache-MySql-PHP