This article is the first of our series on AWS cost optimization. In this series, we’ll introduce the challenges with AWS costs. We’ll also offer actionable recommendations on how to solve them and perform efficient AWS cost optimization.
Most businesses spend much more on processing and storage than they need. This is often the case with operating expenses for excess capacity to meet peak demand in their on-site data centers.
Moving to public cloud services such as AWS helps enterprises to maximize the consumption levels of their workloads. At the same time, they reduce their total costs. There are major benefits of substituting conventional up-front hardware purchases for the more effective pay-as-you-go scheme.
The large scale on which AWS works also helps its consumers to continuously reduce the computing and storage facilities costs with economies of scale. AWS has the ability to change the model of running technology and platform services dramatically. However, companies have to use it wisely.
Unfortunately, teams don’t think of resource waste as a major concern, and this is why problems arise. A typical scenario for the implementation of enterprise cloud is that costs pile up before some major cost-related incident or another boiling point arises when AWS costs become a major issue. This results in urgent demand for oversight and monitoring, annoyance with the bill’s complexity, and a heavy incentive to cut costs immediately.
However, without compromising innovation and some benefits that the cloud offers, it could be challenging to attain cloud cost optimization. Instead of solving the root challenges, it may result in guilt and embarrassment. Moreover, it can place obstacles to implement restrictions on application teams who attempt to progress rapidly. In some cases, can even compromise the overall cloud use.
Here are some of the potential challenges with AWS costs:
Cloud costs are hard to forecast
One of the most common challenges with AWS costs is that traditional finance models include signing off expenses before they occur. However, as cloud costs can vary, teams can’t predict them, so the budget can’t be determined up-front. Cloud expenses, even though use habits are well known, are extremely hard to forecast for all applications that are a bit more complex. Teams can, for example, be surprised by extraordinarily high operating expenses for logging, metric compilation, data outflow, or charging models per request.
Billing for the cloud is extremely challenging. For instance, with billions of line-items, certain businesses receive a monthly cost and usage report (CUR) that often contains several rows for the same assets with multiple costs. It can be impossible even to attribute these expenses to the right business segments if there is not a clear account process and tagging plan in advance.
Cloud cost optimization isn’t the priority
Technology teams want to release new features more efficiently and to deliver consumer success. Until the executive team emphasizes a dramatic change, cloud costs are not an evident concern and this is why problems often occur. For example, architectures require compromises between reliability and cost. This and other cost-saving opportunities require engineering commitment that usually focuses on the development itself.
Low cost visibility
Particularly in large companies, application teams don’t even have full visibility of the expense for the cloud they generate. Limited permissions to access the billing and expense explorer console, for instance, is often a case for these organizations with teams for each working segment. The actual expense is also not expressed (e.g. appropriately taking into an account reserved cases and subsidized rates). In fact, for shared resources, adequate expense distribution includes advanced showback or chargeback procedures.
Combined with prioritizing innovation and growth, this lack of visibility will lead to great waste. For example, dev and test environments are only necessary during working hours, while they are often left to run all the time. Or, other resources needed just for a certain project aren’t terminated at the end because the team simply doesn’t focus on actions like these.
Poor financial knowledge and billing complexity
Development teams often don’t consider the broader view of how they use their budgets. The finance teams have a great responsibility. Members can suffer severe consequences if they don’t do expense analysis and financial reporting properly.
Billing complexity also contributes to the lack of financial knowledge. This applies to the confusion created by most cloud service providers’ continually evolving pricing policies, and the invoices they provide.
Cloud vendors typically have a ton enlisted on a single invoice, taking into account all potential cloud configurations generated during the creation of enterprise solutions. It takes a lot of effort to make a transparent bill that all key people in the team will be able to understand. This is necessary to back up all your attempts to optimize costs.
Inadequate architectural design
A well-architected infrastructure can either make or break a system. Designing with cost-effectiveness in mind can help shape future cloud spendings. Companies need well-educated architects to be able to design reliable and secure solutions. AWS has developed the AWS Well-Architected Framework – best practices that can help in understanding the pros and cons of the decisions architects make when they design a complex solution.
In addition to the framework you can also review and measure workloads with the AWS Well-Architected Tool (AWS WA Tool).
The AWS Well-Architected Labs also represent a good resource. This is a repository of code and documentation to give you examples on implementing these best practices.
Problems with manual work
Staying on top of your AWS cloud costs can be time-consuming if you do it manually. Manual activities are complex and prone to errors because we, as humans, can’t perform operations as smartly as machines. Tracking down forgotten instances, writing scripts and manually deploying them, and comparing AWS bills are only some of the things you have to do to keep track with your AWS costs.
However, if you take advantage of an automation tool, you will only need to set up the process once and then only take action when some issues arise. You can define a sleeping schedule for your non-production resources to shut them down when you don’t use them.
Accountability absence
The cloud has the ability to decentralize IT operations. This can result in a lack of accountability if within the cloud environment you do not set up the correct visibility and control mechanisms.
Cloud costs are everyone’s responsibility, from engineering teams, to finance departments to business decision-makers. Many factors impact the budget, so this is why different levels of accountability need to be promoted in the company. Up until recently, not many of the roles in the company were concerned about the responsibility of managing cloud costs. But to have an effective cloud cost optimization strategy everyone needs training and tools to implement them right.
Check out our comprehensive guide on creating an AWS cost optimization strategy.
These were the most common challenges that come up when it comes to AWS costs and their optimization. In the next articles, we’ll dive deep into understanding AWS costs and offer tips on how to solve these challenges.
Top comments (2)
Good post!
Thanks a lot :)