Most cloud environments are not optimized for cost. Despite the best intentions, it is extremely difficult for cloud architects and cloud engineers to create and maintain cloud environments that are completely optimized for the lowest possible spend and the least operational overhead.
Often, cost reductions can be accomplished by optimizing elements such as:
- Traditional Applications and Infrastructures
- Unknown Values Beforehand
- Unexpected Peak Loads
- Inefficient Architecture
- Operational Overhead
Five Ways to Minimize Your Cloud Spend
In this article, we discuss five actions cloud engineers can take to reduce the cost of their cloud environment.
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Cost Reduction 1. Refactoring Traditional Applications and Infrastructures
Traditional applications and infrastructures usually are not designed by the latest cloud principles and best practices. This makes them bulky, heavy, and inefficient.
Contemporary cloud infrastructures and applications scale when demand increases. This can be realized by designing processes that are horizontally scalable, are as compartmentalized as possible, and are preferably serverless so that you do not pay for idle but for actual use only. This means breaking up monoliths into a microservices architecture, statelessness of your application landscape, and minimizing the blast radius of any component to improve resiliency.
If not, a workload is likely to be inefficient, a tax on operations, and not cost-effective.
By refactoring these workloads, costs can be reduced significantly.
Cost Reduction 2. Filling in the Unknown Values
When architecting a cloud environment, it is usually difficult to calculate the actual operational cost of the workloads. Cloud services are invoiced on a pay per use basis. Despite calculation tools as the AWS Simple Monthly Calculator or the Google Cloud Platform Pricing Calculator, certain values are simply not known upfront.
For this reason, most companies start building their platform first. Based on the actual load or traffic, organizations experience the price associated with the process. Still, the return on investment (ROI) can differ per service for each use case of the platform.
As soon as a workload is live, it is wise to check the actual consumption and cost. A cloud expert usually is able to point out the room for optimization.
Cost Reduction 3. Engineering for the Right Load
In development, engineers need to make certain assumptions of the expected load on a service. In practice, the load on a workload or service can be much higher than originally anticipated. Services that are designed to be spun up only occasionally are not always well-designed to run continuously or to hit certain peak loads.
In addition, traditional architecture is not very well suited to deal with a sudden surge in traffic. In practice this means companies either provision resources for anticipated peak capacity, or run underutilized. This often leads to an exponential increase in cost, or a damage to reputation: downtime.
Cost reduction and being ready for peak loads do go hand in hand, however. For example, costs can be reduced by moving workloads to a container orchestration platform, and by migrating services to a pay per use model. Using the right data store for the right data can be a huge saving, and using a CDN to cushion your instances from sudden spikes of traffic, allowing for sufficient time to scale out.
Cost Reduction 4. Streamlining the Architecture
Most cloud environments are not isolated, but continuously evolve. In practice, added workloads and processes can lead to a more inefficient performance of an environment. It is smart to regularly review your workloads and infrastructure to get rid of inefficient use of services. It is even smarter to monitor these workloads and evolve the architecture through automation.
Cost Reduction 5. Operational Overhead
An often underestimated reduction in cost is operational overhead. Rarely, the human cost is taken into consideration: after all, it isn’t visible on your cloud vendor’s bill. Operational overhead can be reduced by opting for services offered by a cloud vendor that require no management whatsoever. Do not reinvent the wheel. The time saved by reducing operational overhead is time that can be spent on interesting and productive stuff. As such, you need less staff to do the same work while at the same time increasing the job satisfaction tremendously.
Example 1: Reducing Operational Overhead
Being in an operations engineering team of two is not fun, particularly when you have to maintain infrastructure that is built on legacy and good intentions. This was the case at Amsterdam-based Asellion, the developer of a global platform that makes the global chemical trade transparent and sustainable.
To reduce their cloud spend as well as the operational overhead, I set the operational overhead as THE metric for success. During weekly retrospectives we assessed if we were on the right path. By doing so I’ve been able to help Asellion by transitioning their architecture to a modern architecture based on best practices. While the team grew from 10 employees to over 50, employee satisfaction scores (eNPS) went through the roof. In addition, their developers are now deploying and maintaining their own applications and enjoy doing so. Asellion is definitely on my list as a cool cloud-based company now.
Example 2: Handle Peak Loads Gracefully
Some organizations experience the need for optimization as soon as they start scaling. At that moment, it becomes clear that processes are way too expensive. Stranded Flight Solutions (SFS) experienced this first hand.
SFS is a start-to-end global service recovery platform for airlines to improve the guest experience when these are challenged the most. I was asked to assess their infrastructure with a particular focus on the cost. I found that their applications were under-provisioned for peak capacity, while being over-provisioned for idleness. In other words: While most of the team the platform aw little traffic, as soon as passengers would find themselves stranded at an airport, the services could not handle the peak load. I helped Stranded Flight Solutions to transition to a mature architecture that is scalable by using serverless, CDNs and container orchestration. This has led to a substantial cost reduction
Free Review of Potential Cost Savings
To support organizations in the current challenging times, we offer a free intake where we explore potential cost savings. This call takes between 30-60 minutes. During the call, we will try to uncover potential savings on your monthly cloud bill. If potential savings are indicated, we can support you with an optional extensive review and remediation.
This cost optimization review helps you to identify the potential measurements you can take to minimize the cost of every individual use case.
After remediation, organizations save up to thousands of euros per month on their cloud bill.
Request your free cost optimization intake >>