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By eliminating the traditional barriers to computing resources, the cloud has created a level playing field to compete regardless of organizational size or clout. But organizations that move to the cloud often find themselves grappling with cost inefficiencies created by unrestrained spending. Optimizing cloud costs is, without a doubt, a top priority as it directly impacts the bottom line. As your cloud partner, we help you identify and address inefficiencies and maximize the benefit of the cloud.
Studies point out that 35% of cloud expenses are of wasteful nature. Eliminating this waste is an uphill task for many organizations.
More than a hundred instance types are available today with varying system and network configurations and prices. It can be difficult for organizations to make the most economical choice from this perplexing array.
Users provision resources on demand but don’t remember to decommission them when they are no longer required. Similarly, they allow instances to run 24x7 rather than when they are needed, leading to revenue leakage.
Many users have trouble determining the capacity of the instance they need and this leads to overprovisioning. Some may provision the wrong type of cloud server. All this results in wasteful expenditure.
Finding the right storage is problematic when a plethora of vendors crowd the market with diverse features and pricing models. The most cost-efficient one is not easily apparent.
The technological strategies for cloud cost optimization revolve around allocating the right resources in the right capacity and at the right time. This involves analyzing requirements before deploying resources as well as making changes to the deployments as requirements evolve.
Instance types are optimized for memory, database, computing, graphics, storage capacity, throughput, etc. The right choice depends on the nature of your application.
For workloads that demand resources for select periods of time (such as batch processing of data) spot instances created at the time of demand are a more economical option. Opportunistically turning instances on and off based on actual usage is a great way to save up to 75% on costs. Automated scheduling makes this more efficient. Cloud platforms can be configured to auto-scale resources based on a set of rules.
The selection of GPU over CPU is another decision that has cost implications. GPUs are preferred over CPUs if the applications involve large computations (such as machine learning and 3D rendering). Appropriate CPU or GPU instances can be created depending on the requirement.
Moving data in and out of storage is expensive, so the choice of storage must be decided at the outset and must be guided by your requirements. Amazon S3 Standard is an object store for data that needs to be retrieved often. Amazon S3 Standard - IA and related variants are better for backing up data that is not likely to be accessed for a very long time. For compliance backups and archival storage, Amazon Glacier is a cheaper choice. You can also reduce the costs of data access by selectively retrieving objects from S3 using SQL expressions, thereby reducing transfer and compute costs.
Lambda, with its server-less nature, is a cost-saving option that can be adopted for workloads that are time-limited, low-memory, and stateless. Since failed Lambda executions and retries are expensive, attention needs to be paid to how they are implemented.
Containers are a lightweight alternative to isolated application execution. By running multiple containers on a dedicated or virtual machine, better utilization of servers can be achieved. The key is, again, correct implementation, such as ensuring the use of lightweight OS images.
Containers can be run on virtual machine instances like EC2, where you pay for the capacity of instance and not how much of the instance is used. Specialized platforms like Fargate allow you to deploy the container in a dedicated container host environment.
The licensing cost of the base operating system can spike the total cost of running an application so it needs to be managed carefully. An instance of a Linux system like Debian or Ubuntu on a virtual machine costs less than Windows or a supported RHEL instance.
Several imperatives push enterprises towards a multi-cloud model—varying department needs, pricing schemes, SLAs, security, and so on. But managing the diverse products from multiple vendors requires specialized tools and additional training, which makes it cost-intensive. A single cloud, on the other hand, eliminates the administrative hassle of switching between platforms and paying for network traffic between clouds.
Lambda, with its server-less nature, is a cost-saving option that can be adopted for workloads that are time-limited, low-memory, and stateless. Since failed Lambda executions and retries are expensive, attention needs to be paid to how they are implemented.
Containers are a lightweight alternative to isolated application execution. By running multiple containers on a dedicated or virtual machine, better utilization of servers can be achieved. The key is, again, correct implementation, such as ensuring the use of lightweight OS images.
Containers can be run on virtual machine instances like EC2, where you pay for the capacity of instance and not how much of the instance is used. Specialized platforms like Fargate allow you to deploy the container in a dedicated container host environment.
It is easy to lose sight of the various cloud deployments as they grow in number and complexity. As idle instances accumulate, they lead to what is called virtualization sprawl (in case of virtual machines), with adverse effects on cloud spend, performance, security, etc. By having cloud cost governance policies and mechanisms in place, you can exercise a level of control over your cloud journey and prevent cost overruns.
Computational resources no longer constitute one-time capital building decisions. As computing resource allocation becomes dynamic, so will budget allocation. In such a dynamic environment, interdepartmental collaboration—between development, operations, and finance—is pivotal to keep the pace of innovation going without hurting the financials.
We recognize that the cloud is the key driver of your innovation and growth. Our focus as a cloud partner is on getting you the best of the cloud without letting overspend break the financial edifice of your operations.