3 Ways Cloud Tech Can Help You Work Faster and Smarter
Cloud technology is helping businesses in every industry do more with less. While many of us can already see the key role that this technology is able to play in driving successful digital integration, some are skeptical or simply unclear on the benefits of moving applications and workloads into a cloud model. We speak to Jellyfish Training's Lead Cloud Solutions Trainer Mark Crump to reveal how cloud technology can disrupt your 9 to 5 in the best way possible...
- You can save your business time (and money) by offloading some administrative tasks with PaaS
- You can analyze data faster and make smarter business decisions
- You can simplify scale and development using containers
Generally speaking, most companies that already own an IT estate start their move to the cloud with an Infrastructure as a Service (IaaS) set-up, where they effectively lift and shift what they’ve already got in their data center into the cloud. This means you get some of the benefits of the cloud – such as not owning the data center and the elasticity to easily scale up or down – but you’re still managing operating systems, security patching, and the availability of the machines.
An alternative approach to the IaaS solution in this example is to use Platform as a Service (Paas). PaaS lets you step further away from the day to day administration of the infrastructure elements and focus more on the actual app.
Say you needed to build a database service for your app. You’d have to think about the OS, installation, and configuration of it, the back-up and recovery solution, security patching, and scale before you even start thinking about how you’ll use the app. By using a PaaS database solution such as Google’s Cloud SQL instead, you’ll only need to supply some simple configuration information, then you can sit back and allow Google to build and manage the majority of it for you. If you need to make choices such as whether or not you need high availability, it’s as simple as ticking a box. The back-up and recovery set-up is already taken care of, as is the ability to automatically scale the database size – giving you far more freedom to focus on your app.
Using services like BigQuery, you can now ask complex questions over huge amounts of data incredibly quickly. Where brands were once restricted by their own resources as to whether or not their data could be used to make data-driven decisions, we now have access to the tools that can on a ‘pay as you use’ basis.
As a real-world example, a very large organization in the UK used its own data center resources to run a massive query on a daily basis, which took around 23 hours to complete. Since moving to Google Cloud Platform, they’re able to make the same query in under 20 seconds using BigQuery – giving them the opportunity to interrogate far more data and derive much better insights.
But the benefits don’t stop there. The information returned from tools like BigQuery can be consumed by just about any other service in Google Cloud Platform, so it could be used to trigger another action.For example, say a brand who operates an e-commerce website wants to see which of its visitors are most likely to make a purchase based on advertising, then target these users with specific types of ads. Finding these users and their shopping habits is possible using BigQuery, then they can use a machine learning model to make predictions based on this information. Google has recently made using machine learning far more accessible by adding this capability to BigQuery (BQML).
Over a decade ago, Google developed its container system as a way of simplifying hyper-scale and rapid development. Some years later, a company called Docker open-sourced and popularised container image creation and packaging for developers. Since then, adoption has really picked up speed.
So how does this benefit developers? Traditionally, if you wanted to build an app you needed specifically built machines (web servers, database servers, etc.) to run operating systems, libraries, and content – as well as somewhere to host it all. Then, once your app was built and running, it could be very difficult to make adjustments to it – such as scaling it up for capacity or modifying code to include new features – without disturbing the other component parts.
Containerisation offers a far more modular approach to building and deploying apps. Developers can create apps that are made up of individual parts that communicate with each other by using API calls and IP addresses, rather than relying on a single slab of code. Because of this kind of separation, the developer is able to tweak any part of the app without directly disturbing everything else.
In addition to this, we no longer necessarily need to have dedicated servers to run the different parts or tiers of the app. In the past, we needed a webserver to run a web front-end or a database server to run a database. But now, we can launch the different containerized parts of the app on any machine that has the container optimization technology installed.
So why is containerization only now taking off? A lot of businesses have shied away from it because it’s been difficult to find a universal management solution for multi or hybrid clouds. It has also been challenging to take an existing monolithic app and turn it into a container optimized app. However, with the introduction of new products such as Google Anthos, it’s now possible to take a traditionally built app and turn it into a container optimized app with relative ease – and run it anywhere.
About Jellyfish TrainingFounded in 2014, Jellyfish Training offers over 120 digital classroom and online training courses ranging from digital marketing, SEO, social media, and analytics to cloud technology, cybersecurity, and agile.
As a Google certified training provider, Jellyfish has helped over 50,000 people from global corporations to small businesses, as well as non-profits, charities, and government organizations to upskill their workforces.