If you work in software development and are looking for your next challenge, then look no further than a career in cloud computing!
Simply put, cloud computing is the delivery of computing services – including servers, storage, databases, networking, software, analytics and intelligence – over the Internet (“the cloud”) to offer faster innovation, flexible resources and economies of scale. Typically, you only pay for cloud services you use, helping you lower your operating costs, run your infrastructure more efficiently and scale as your business needs change.
2019 was a banner year for the cloud-native community, and in 2020 it just looks set to grow. Take a look at our 4 trends that will shape the cloud-native world in 2020 post for more information on this.
A history of cloud computing
Where did the cloud-native world come from?
In 2014, Google announced it was embracing Docker and open-sourcing a new tool to manage computing workloads and cover large scale computing infrastructure. At the time, this was hailed as revolutionary….it was believed to be the “secret weapon” in cloud computing.
Now, we know this tool as Kubernetes. It was the dawning of a new community and would instigate a seismic shift in cloud computing technologies. Kubernetes has been pivotal in waging the war against dominant player Amazon Web Services for the cloud computing market share. Weapon indeed. Google, Microsoft and Alibaba have long been chasing the crown, looking to rip it from the head of AWS.
Kubernetes held significant promise. Docker allowed the delivery of standardised and portable software. Developers could enter code, libraries and configurations into a Docker container and then run it anywhere regardless of the computing platform as long as it had Docker installed on it.
How does cloud-native technology work?
Picture the scene. You have several applications, packaged in several containers. These are running across a fleet of different computers in data centres and cloud environments. In this scenario, who is going to tell which container where to run? How are these different forms of hardware going to function as one unified computer to run your workload? In the business, this is known as Orchestration, and Kubernetes can do this for you.
The benefits of cloud-native technology
Even back then, this wasn’t considered to be groundbreaking. However, what it did promise was the ability for the community to benefit from Google’s many years of experience. Suddenly, we were able to run intensive workloads over cheap infrastructure and REALLY take advantage of it. In short, enterprises could gain access to Google level technology and up its digital game.
Kubernetes was also a brilliant strategic business move from Google. To standardise orchestration would make it far easier for users to run Docker-ised workloads, thus encouraging a shift to the new model.
“Cloud-native” Docker-ised workloads were easier to run ‘in the cloud’ than older, legacy applications. They are also “portable”; able to be moved from ‘cloud to cloud’. These progressions held significant implications for business. It would get easier and easier to persuade enterprise customers to transition their computing “to the cloud” and to migrate from cloud to cloud – i.e leave the dominant AWS and move across to Google. These features were great for both growing the cloud computing market in general and for boosting Google’s market share. It also heralded an age of alignment; Kubernetes also worked to standardise the compatibility of cloud vendors.
What are some of the top skills for cloud computing careers?
Seasoned IT pros can definitely leverage their prior tech experience in a cloud career, but they’ll also need to add some new skills. For instance, you’ll be hard-pressed to get anywhere in the cloud without expertise in at least one of the public cloud behemoths: Amazon Web Services, Google Cloud Platform, and Microsoft Azure.
Based on the jobs posted on Indeed, the top 10 must-have skills you need to have a successful cloud computing career are:
Amazon Web Services (AWS): The pioneer in affordable cloud services and enjoys the largest market share in the field.
Python: The most rapidly growing language on the cloud.
Java: One of the most popular programming languages in the cloud and its latest cloud-friendly enhancements are bound to increase its usage.
Azure: Usage of Microsoft Azure has grown from 34% in 2017 to 45% in 2018. It’s gaining on AWS every year.
Agile: Agile project management practices and its adoption in cloud development cycles are growing each year.
Puppet: Employed in DevOps environments to automate AWS, a time-saving option of immense value to most enterprises.
Chef: Another technology deployed in DevOps It offers analytics at the enterprise level through its Automate tool.
Ansible: An open-source centralized server management system that makes setting up a cloud-based application cost-effective.
Docker: An open-source containerization technology that automates the process of setting up and use of software programs
VMware: Software to virtualize cloud environments used for computing. This is also popular in all types of domains.
Containerisation
Containerisation expertise is increasingly another must-have, especially for developers building and running applications in the cloud. Docker and Kubernetes lead the pack in the containerization field right now but there are plenty of alternatives worth keeping an eye on.
Automation
Automation software is another technology category gaining steam in cloud-first environments, especially those that have adopted DevOps. This includes tools like Puppet, Chef, Ansible, and many others, and as their usage grows in cloud shops, so does employer demand for people who know their way around these platforms.
Integration
Integration of data across applications—including data acquired from different vendors and platforms or residing in different data centres—is a big deal in the cloud. It gets even more complicated when your cloud systems need to talk to your legacy systems. Smart cloud architects and other cloud-first professionals include integration as a first step. Scrambling to address integration after the fact is like building a house and adding the wiring and plumbing after you’ve already put in the flooring and walls.
