To scale the cloud means to adjust your IT infrastructure, software or any other service by adding or removing resources to/from the cloud. With an excellent XaaS offering, anything and everything can technically be scaled on the cloud at an optimum cost; while you only pay for the add-ons or as per your usage. Scalability, combined with the option of subscription billing, justifies the massive industrial shift to the cloud. Here are the top reasons why businesses need to scale the cloud.
This is the easiest and oft-repeated reason that comes up. When a business grows, there is obviously a need for more servers, networks, software, data storage facilities, etc. If you have deployed a cloud for your business, the next thing to do is to increase the number of systems, software or update your software etc. This is where scaling comes in.
Cost Savings on Hardware
The reason why most cloud users wish to scale their cloud is to cut hardware costs. Most often, organisations need only those computer systems or networks that are necessary to access the web. If their data storage is on the cloud, then they use only lower volume arrays at lesser cost at their end.
When organisations take on new operations, their data storage or hardware requirements increase. This means they have to scale the cloud in order to cut hardware costs. On the other hand, if enterprises do not scale their cloud, they might incur heavy losses on software updates and system upgrades which are now handled efficiently by the cloud. Scaling the cloud works best in this case as you can just pay the marginal costs of additional system upgrades, software updates or extra storage.
Increasing Network Access
At their initial stages, small start-ups and SMEs have limited network resources. As they grow, traffic increases internally (users, employees, smartphones etc.) as well as externally (customers). To increase their network access and provide functionality to the users, scaling the cloud becomes an absolute necessity as network traffic increases manyfold and loads on the cloud increase.
Hardware and Software Customisation
Every enterprise has its own hierarchy and operation levels. Certain employees have access to data that others don’t. This segregation of data access involves customisation of hardware and software according to the specific needs. This is when you need to scale the cloud to provide additional data security by hardware and software customisation.
Optimising Performance and Handling Excess Workload
Workloads increase when there is:
- More traffic
- More data queued up
- System crash or failure
- Saturation of networks
Each of these situations calls for a need to scale the cloud.
How to Scale the Cloud
Scalability is a definite value addition to cloud computing. If you understand the various options of scalability in a cloud, you can use it to your advantage. Cloud computing has shown us that scalability would be a key-performance indicator for its success. If so, it is important to know the means by which you can scale the cloud and the various types of scaling.
There are two major scaling strategies for cloud:
- Vertical Scaling
Vertical scaling goes from low to high. With this type of scaling, you add resources like RAM or cache to the existing work unit. You could also replace the server with a bigger one. You scale up by increasing the power of the individual server and enhance its capabilities. A typical use case could be the need to increase compute power or RAM to run bulky end-of-month reports. This allows it to handle the load better in case of a traffic or data intensive needs. Vertical scaling works best when you purchase and install software that is capable of central control.
- Horizontal Scaling
Horizontal scaling goes from side to side. With this type of scaling, you add multiple resources to work alongside the existing unit. In this case, you would add an extra server without getting rid of the original one. Now there are two of them and they can handle traffic effectively. With horizontal scaling, you scale out by linking together many minor machines so they can collectively do the work of an advanced machine. A load balancer that routes traffic across multiple virtual machines on a network is an example of using scale-out. Horizontal scaling works best with machines that can be easily connected.
In both these methods, you are including additional resources to the cloud infrastructure to help with load distribution. While these are both about enhancing the server capacity versus decreasing one server’s load, the approaches are what differ.
Examples and Techniques of Scaling
Autoscaling (short for ‘automatic scaling’) involves the amount of resources increasing or decreasing automatically based on the total load. It is similar to load balancing, but in autoscale, you can configure a host of parameters on which you trigger a scale event. Autoscaling lets companies save on costs as it makes sure that not all the servers are running during times of low load. This can also extend the life of the machines as a whole as they are only up when necessary. Autoscaling is reactive and works well for unpredictable workloads.
When a company uses scheduled scaling, they make changes to size and capacity beforehand. You are being proactive and scheduling the dates and times based on when you know there will be an increase or decrease in traffic and therefore load. Some changes may occur too fast for autoscaling to deal with accordingly. This is when scheduled scaling becomes the preferred option. You need to know your server well enough to use this.
By combining recent usage trends with historical data and statistics on usage, you can predict the data usage in the future. All that’s left is to scale based on this data. You can identify demand spikes, prevent large-scale server outages, and establish traffic patterns. Of course, as with any predictive analytics methods, this requires a meaty chunk of historical data to make predictions on.
While not a direct scaling technique, containerisation acts as a more efficient alternative to virtualisation. It increases the efficiency in the deployment and functioning of distributed applications as you do not need to launch the entire virtual machine every time. Containers share resources without a full OS. Docker is a popular container technology. Containerisation, however, requires a development workflow and engineering mindset that is relatively new and the shift to move to this mindset is a resistive force.
We help enterprises scale the cloud seamlessly. Our product apiculus offers manual, scheduled and automated scaling of virtual machines. Additionally, we also have customisable solutions that let you use containers in a powerful fashion to manage your dev workflows. Hit us up for a chat!