Recently, many enterprises have moved their data from traditional datacenters to the cloud. There has also been a growing consensus among leaders about staying prepared for unforeseen circumstances, mainly by cutting unnecessary spending. These events have led to the question – are we efficiently using every resource, especially the cloud?
Getting the most out of their cloud solutions requires organizations to invest significant time and resources to understand how their cloud environment works and then determine how to optimize their cloud costs. Cloud cost optimization is not a one-off exercise that you can implement and be over with. It is all about pausing, analyzing and making conscious decisions throughout your cloud journey.
Through my experience working on various cloud platforms over the years, I’d like to highlight some cost optimization best practices.
A developer might create a temporary server to perform an activity and forget to turn it off afterward. Sometimes they might delete the instance but forget to remove storage attached to the terminated instance. If the resources are not shut down completely, you will continue to pay for them.
The first step to optimizing cloud costs is regularly identifying and removing unused resources.
Choose Suitable Instances
Every cloud provider offers different computing instances that cater to varying workload requirements.
Most providers give heavily discounted instances based on the instance term, region, and type. You can get 25% – 75% discounts on these instances, so it’s essential to know your past usage and have a long-term cloud strategy before you invest in such instances.
Organizations tend to purchase too small or too big of an instance and compromise on quality or performance. Therefore, it is crucial to take your time and identify the right-sized instance that does not require any compromise and will perfectly meet your cloud computing needs.
Make Use of Spot Instances
You can bid and get spot instances for temporary jobs at a meager cost. Spot instances are different from regular instances, but you can save more by using them for your short-term needs.
Spot instances are most suitable for batch jobs and jobs that will be quickly terminated.
Design Scalable Workloads
When you configure a flat workload, unless you plan for maximum utilization at all times, you end up spending needlessly. Ensure that your cloud solution allows for automatic scaling. If you set the appropriate autoscaling rules, you can then scale up when needed and down when not needed. This way, you only end up paying according to your workload.
Turn Off Idle Resources
Many enterprises have deployed multiple environments on the cloud, such as production, pre-production, development, test, etc. While you can auto-scale the production instances according to the demand, the best strategy for other trivial instances is to turn them off when not required.
Identify when the development, test, and other unimportant instances are not in use, and then turn them off during such times. Off periods could be timings such as weekends, evenings, or whenever the developers are not working on them. Leveraging automation to turn instances on and off based on need is the best way to consolidate idle resources.
Many enterprises running on the cloud follow a multi-cloud strategy and avoid vendor lock-in. There are both upsides and downsides to such an approach. When it comes to availability and up-time, multi-cloud might seem like an intelligent choice, but you also risk losing the volume discounts and high-tier status when going with a single cloud vendor.
Additionally, a multi-cloud strategy comes with a lot of administrative challenges. You have to pay the network cost for every transaction between regions or distributed databases. You also have to train the users to use each platform effectively.
Ultimately, your organization’s priorities should determine your cloud vendor strategy.
Analytics and Notifications
It’s essential to understand your organization’s usage history to forecast your future needs before purchasing. Having a good analytics setup in place will give you the necessary visibility.
Another way analytics can come in handy is by setting up notifications for specific thresholds. You can keep an eye on usage and billing and avoid overshooting your cloud spending through timely notifications. Multiple inbuilt and third-party analytical tools are available for every cloud environment.
Other cost optimization strategies for the cloud include tagging and containerization. A good tagging policy helps streamline your cloud resources and restricts unnecessary spending. You could also take advantage of containers such as Kubernetes and Dockers to keep cloud costs down.
There are many more ways to save costs on the cloud, and I have shared some based on my experience. Depending on your workload setup, application design, and cloud vendor – you can use some or all of the above recommendations to design the perfect cloud cost optimization strategy for your team.