Cloud skills in demand for 2018
Businesses are pushing forward with cloud projects in 2018. The demand for cloud skills is accelerating. Public cloud adoption is expected to climb and the IDC predict spending will reach $250 billion in just three years. As cutting-edge technologies, like machine learning, continue to shape the job market, there is a large skill gap across the industry. With over 350,000 specialists needed to help fill cloud roles there's clearly an opportunity for professionals that can prove their skills. Whether you're taking your first steps into cloud or are attempting to increase your marketability, this is a opportunity to expand your cloud skill set in 2018.
Businesses are more comfortable storing their data with public cloud providers. The idea that a company's data is not secure in the cloud just isn't true anymore. Most companies can't provide the same level of security expertise as the leading cloud providers. Microsoft, for example, plan to invest over $1 billion dollars annually on cyber security. But businesses must pay attention to their cloud security. Cloud providers operate under the shared responsibility model, outlining the security responsibilities between vendor and business. Businesses cannot rely on their vendor to ensure the security of their data and services, their staff must also understand and work towards security. That means it's crucial for IT professionals to understand cloud security. To ensure their organizations are protected, professionals must learn how to utilize the security tools offered by Amazon Web Services, Microsoft Azure and other cloud providers. For professionals attempting to specialize their cloud security skills, there are a number of industry standard qualifications available. The most well-known is (ISC)2's CCSP ( Certified Cloud Security Professional ) which builds on the knowledge taught through the popular CISSP certification.
Machine learning, AI and big data are now at the heart of an increasing number of IT projects. Analyst firm IDC predicts tremendous growth for machine learning and AI, with spend with increasing by 50% over the next three years. As a result, every major cloud vendor is now developing or expanding services that allow organizations to leverage these technologies in their applications. he two largest cloud platforms, Amazon Web Services (AWS) and Microsoft Azure, both provide Machine Learning tools. These tools are easy to set up and there are plenty of tutorials available online. You will need strong data science skills to get valuable information out of them. Microsoft is pushing ahead of the competition in data science training for professionals, creating the Professional Program for Data Science alongside a new certification, the MCSA Machine Learning that aligns to the expert-level MCSE: Data Management & Analytics certification.
Serverless architecture removes the need for developers to manage underlying infrastructure when they want to run or build an application. The idea that applications should be deployed to a server or two is an old way of thinking. By adopting serverless architecture, developers can build services that are scalable and easier to patch or upgrade. This is often cheaper than designs that are based on servers. Businesses were previously concerned about vendor lock-in when adopting serverless architecture but today, major cloud platforms use industry standard technologies and programming languages which means moving serverless applications from one vendor to another is no longer an obstacle. Professionals can dive into learning serverless application development online but will need to choose a platform first. If you favour AWS, consider following their Lambda tutorials and webinars to get started.
According to IDC, public cloud migration is accelerating and businesses will need professionals knowledgeable in cloud to shift their apps and services. Businesses that are struggling to scale resources to meet demand or are aiming to save time on menial tasks like database backup or maintenance will benefit from moving to the cloud. Cloud migration isn't a fast process and it's by no means risk-free. Without skilled professionals, businesses risk downtime on critical applications and incorrect implementation could open them up to security vulnerabilities. In enterprises, multi-cloud deployments are common. Enterprises want the flexibility to choose different environments based on performance and cost. Because of this, professionals will want to consider expanding their skills across multiple platforms, particularly Azure, AWS and Google Cloud Platform.
Automation is key to providing a cloud service for business. Auto-scaling, Infrastructure as code, automated monitoring and reporting all play a part in good cloud design. There's currently a move to 3rd party services that allow us to automate across multiple platforms using the same tool set. Jenkins, Terraform and Chef are all popular tools that allow automation across multiple platforms and professionals trying to increase their marketability should consider adding these skills to their learning path as soon as possible.