Many organizations reap the benefits of hosting workloads in the cloud, yet this infrastructure model is not sustainable if you can't keep your cloud bills under control. As COVID-19 continues to affect businesses, companies need to reevaluate their spending, including cloud services fees.
Cloud bills skyrocket for multiple reasons, such as overprovisioned resources, unnecessary capacity and poor visibility into the environment. Fortunately, there are tools and cost optimization practices that can help eliminate unnecessary spending.
Learn how to reduce cloud costs with the following tools and practices.
Opt for reserved instances
In the cloud, organizations will find cheaper alternatives to on-demand resources if they're willing to commit to making certain tradeoffs. Utilize these discounted pricing schemes when possible:
- Reserved. Organizations that make an upfront commitment to use a certain amount of capacity over a one- to three-year period can save on cloud resources with reserved instances. Reserved instances can come in at one-third the price of on-demand instances, depending on the platform and other variables. Each major cloud provider offers this pricing option, with Amazon EC2 Reserved Instances (RIs), Azure Reserved VM Instances and the Google Cloud Committed Use program. AWS also has a Savings Plans program with similar discounts but more flexibility in usage than its standard EC2 RIs. Reserved instances are best suited for workloads with consistent, predictable capacity.
- Spot. Developers can access unused capacity for a deeply discounted price with Amazon EC2 Spot Instances, Azure Spot VM and Google Cloud Preemitble VMs. Savings with these pricing models depend on what type of resource is purchased and the price at the time of purchase. The cost of these instances is subject to frequent changes that can differ on an hourly basis. If the instance exceeds a cloud user's maximum price point, it will be terminated. Low-priority instances can reach up to 90% savings, but these are more limited in availability and subject to abrupt cutoffs, depending on overall capacity demands in a region. They're best used for stateless workloads, batch jobs and other tasks that can tolerate disruption.
Even though organizations can quickly spin up or down instances in the cloud, they still end up paying for unused capacity all the time. IT teams need to ensure enough capacity is available to handle unexpected traffic spikes and load fluctuations but not so much that they overspend on unnecessary resources. Capacity planning can help reduce overall cloud costs.
Autoscaling resources can help organizations ensure they don't pay for unused cloud capacity. Cloud providers offer native services with autoscaling features, such as AWS Auto Scaling. These features automatically monitor and adjust application scale to meet demands and can be used to prioritize cost, availability or performance.
Set up autoscaling parameters with cost in mind. For example, put performance limits on lower-priority workloads that don't require extensive scaling. Configure autoscaling settings to use the minimum number of necessary resources to meet demand. And incorporate some of the previously mentioned discount programs as appropriate.
Serverless computing can help remove many scaling issues as well, but it still requires some upfront planning to avoid runaway costs. You can also use techniques such as queuing and caching to accommodate unexpected traffic spikes without paying for idle capacity.
Limit data transfer fees
The cost to move data to and from a public cloud can be expensive. Cloud providers charge data egress fees to move data off their platforms or even between regions. To cut costs in this area, avoid unnecessary data transfers.
Start with an assessment of your cloud provider's transfer fees. Then, adjust your cloud architecture to reduce the number of necessary data transfers. For example, you could move on-premises applications that frequently access cloud-hosted data into the cloud to eliminate those hops.
Also, evaluate the fees of different transfer methods intended to accelerate and secure the movement of data between the cloud and your private data center. For example, compare the cost to use a dedicated network connection service, such as AWS Direct Connect, Azure ExpressRoute or Google Cloud Interconnect, to the cost of a physical transfer device, such as AWS Snowball or Azure Data Box.
Utilize cost monitoring tools
An effective cost management strategy requires the right tools in place to monitor spending.
AWS offers various cost monitoring tools. One tool, AWS Cost Explorer, analyzes your past spending -- up to 13 months prior -- and forecasts your cloud expenses for the next three months. Another option, AWS Budgets, sets custom alerts to notify users when spending exceeds a certain point. It also can automatically limit resources to reduce cloud costs.
Microsoft cloud users can monitor their spending with Azure Cost Management + Billing. This tool tracks spending across individual Azure services, provides future bill forecasts and alerts users when they go over budget. Similarly, Google Cost Management enables Google Cloud Platform users to identify cost spikes and set up spending reports for cost optimization.
In addition to cloud-native options, third-party cost monitoring tools help organizations make smart spending decisions. For example, CloudCheckr tracks spending across cloud resources and provides recommendations on where to cut costs. Scalr is another third-party tool that offers cost analytics as part of its cloud management platform.
Prevent cloud sprawl
Cloud sprawl is the uncontrolled proliferation of cloud resources and is to blame for many cloud bill spikes. When organizations fail to eliminate cloud services that are no longer part of their overall strategy, they still continue to pay for them.
To avoid this issue, establish proper visibility into your cloud environment with infrastructure and application monitoring and management tools. Set up company policies on how and when to decommission cloud resources that are no longer needed. Use automated provisioning to shut down old workloads.
In addition to cloud policies, carefully monitor cloud bills and contracts to identify if your organization is paying for cloud services that are no longer in use.