Cloud has seen a rapid development in recent years which has created a competition on prices in the global market. Cloud providers are trying to maximize their revenue by their price schemes, while consumers are trying to achieve a cost-effective solution with a good quality of services (QoS). But with the growing demand for resources from their users’ companies are struggling in devising a cost-efficient strategy. This article aims to help you to find an optimal solution with which you can minimize the operational costs incurred in using a cloud platform.
Basic price model in the cloud platform:
Before we look at the ways of optimizing the costs incurred in using the cloud, we should take a look at how cloud service providers charge their users. By analyzing what, why, and where we are charged, we can find ways to reduce it. Cloud providers offer fixed and dynamic prices for using their services. Organizations prefer cloud platform because of easy scalability and flexibility over existing resources. Though the pricing model is different for each cloud provider, it can be summarized in a few basic ways by which a provider incurs charges.
- Time-based pricing: The pricing is based on how long you have used a cloud service. Most cloud platforms charges hourly for usage of the RAM, CPU and other resources.
- Volume-based pricing: Volume of a metric such as storage is used to charge the users. Generally, you pay for each additional gigabyte storage you require.
- Traffic-based pricing: A cloud provider charges you for the outbound traffic of your application from the cloud server. You are charged on per transferred GB basis.
Cloud providers then charge its customers on the above criteria with a pay-per-use or subscription-based pricing.
Cloud Cost Optimization:
Multi-cloud cost management can make the biggest difference to your overall IT expenditure. By optimizing your network infrastructure, cloud practices, pricing models and multi-cloud complexity, you can achieve a cost-effective solution.
The following tactics will help you to create an effective cloud cost optimization strategy. But each one of them is highly dependent on the need of cloud computing for your business. Therefore, it is advised to analyze your needs before applying any of the following cloud cost optimizations.
Reduce multi-cloud networking costs:
Organizations generally prefer a multi-cloud ecosystem for their business because of the different services provided by each cloud platform. But without careful monitoring, costs can begin to rise. Usually, you are not charged for transferring data into your cloud platform. But transferring it out onto another platform will not be free. Google cloud platform charges $0.12 for each GB in the outgoing network traffic. Outbound network charges vary from vendor to vendor and also within a single vendor between a geographical region to region. Therefore, you should aim for internal as well as external data transfer costs in single and multi-cloud architecture.
You need to strategically select regions across your multi-cloud. The selection can be carried out by considering scale and resource consumption of your applications, logistical complexity and the cost of other vendor services you need.
Utilize your on-premise network:
You should put your on-premise infrastructure at the center of all data workflows. Every data that flows between multiple clouds should go through your on-premise server. Why? because cloud will charge for outgoing network traffic. By collecting data at your data center, you can then transfer it to other cloud platforms. Since for them, it will be an inbound traffic, you won’t be charged for it. Use this strategy only if your network traffic and Internet Service Provider (ISP) charges can afford this process because data will usually be in 100s of GBs.
Move backups and archives to a less costly cloud platform:
Security Information and Event Management (SIEM) systems collect hundreds of GBs of security logs each day to identify patterns and vulnerabilities in real time. This data needs to be stored somewhere because of certain compliance regulations like HIPAA and PCI. For companies that have a complete cloud- infrastructure, it is necessary to reduce the per GB cost of storing logs and application backups. One way to reduce it is to use a multi-cloud architecture and host your backups and archives on a less costly cloud platform. Another way is to use effective data compression algorithms. With efficient ways to compress and decompress data, you will require less storage and the cost of transferring it to another cloud platform.
Use machine learning to predict your future needs:
As stated earlier, in order to implement any cost and performance optimization, you need to analyze your needs and predict future resource requirements. Since the cloud is a dynamic environment that scales up and down to meet demand, it requires instance management. Network administrators can monitor the cloud to identify and scale back any unused cloud resources to reduce costs.
Another way is to use auto-scaling and machine learning. Machine learning provides a proactive solution for cloud cost optimization. By feeding some resources and historical usage data, it can learn meaningful patterns and predicts future usage. It will notify you when it foresees ups or downs in usage so that you can increase or decrease the allocated cloud resources. This process can also be automated once you are satisfied with its accuracy.
Startups and enterprises are using cloud computing technology to offer multiple products and services to their customers. To meet the growing demand from users, they need to avoid reliance on a single cloud provider. A wider range of services and features can be selected from different vendors at a reasonable price that suits their applications. But, achieving a cost-efficient solution is relatively tough. Companies need to do their homework before selecting a cloud provider.