Top 5 cloud cost optimization issues to avoid in 2022

What makes cloud cost optimization so difficult?

Every year, a large number of engineering teams devote their time and effort to cloud optimization, even after this research shows that most firms are unable to keep up with their rising cloud costs. What exactly is going wrong?

There are a variety of reasons why it continues to happen. Low-cost visibility, complicated cloud pricing, and problems anticipating future demand are all likely reasons. We waste cloud resources, time, and money as a result of all of these issues.

It’s difficult enough just to interpret a cloud bill and cloud providers aren’t exactly helping in cost reduction.

Continue reading if you don’t want your cloud bills to scare you and surprise you with bad news at the end of the month.

  1. Getting rid of idle cloud resources?
    It’s all too simple to create a project instance and then forget to shut it down. For example, when development servers are left operating overnight or on weekends when they aren’t needed. Because compute resources are charged by the minute or second, so here they are paid for but not utilized for a big chunk of the week (and yes, this applies even if you have reservations.

    As a result, many teams are dealing with orphaned instances, which have no owner and keep on incurring charges. This issue is especially apparent in large organizations with multiple projects running at the same time and no central resource visibility.

    Shadow IT (initiatives managed outside of and without the knowledge of the IT department) can account for up to 40% of a company’s total IT spending. It might be difficult to ensure that you are only running the resources you absolutely require, especially in large organizations.So how can you spot and delete instances that are no longer in use? Opslyft helps you to optimize your resources through actionable insights and hence take control of your growing cloud expenses. Cost-saving opportunities provided for idle resources save a considerable amount of developer time and money. These insights will be delivered to your inbox or Slack in real-time. You can then set your own criteria and thresholds for idle and underutilized resources based on your own requirements. Moreover, multiple data streams,
    such as CloudWatch, Stackdriver, Prometheus, pgBadger, and others, can be integrated.
  2. Problem with reservations and savings plans?
    To get substantial discounts compared to the on-demand pricing model, choosing savings plans or reservations is not a wise option.Paying less for the services your team utilizes seems wonderful, but paying upfront for a seemingly predictable cloud spend isn’t the best option. If you look closely, you’ll notice that instead of solving the problem, you’re getting a discount on the issue and committing to it for another few years.

    Where are you going wrong and what can be done?

    Predicting how much capacity you’ll use in one to three years is a difficult task.By committing to a single provider for an extended period of time, you lose freedom, get locked in, and may be forced to pay a premium price if your needs change. The best solution, of course, is to avoid any savings plans! Instead of purchasing resources in advance, consider options that address cloud expenditures, such as rightsizing, bin packing, and resource allocation.
  3. Why overprovisioning?
    When your team chooses resources that are larger than what you actually need to operate your workloads, this is called overprovisioning. This is driven by a sense of security, as no one wants their apps to be interrupted. In some business environments, teams are accustomed to receiving more resources than they require ‘just in case.’ Although engineers may find this method to be ideal in terms of performance, it has a negative impact on cloud waste and expenses. Given the elasticity of the cloud, the overprovisioning that is occurring is considerably beyond what is required. Approximately 40% of instances are at least one size larger than what is required for their workloads. By downsizing an instance by one size, the cost is decreased in half, while downsizing by two sizes saves 75%.

    In the long term, making overprovisioning a habit in your team is a bad idea. Consider how this will play out when your company develops if you get in the habit of selecting an instance larger than what your workload requires just to “play on the safer side”. It will lead to cloud waste and wasteful costs that can quickly spiral out of control. Because overprovisioning is ingrained in many firms’ cultures so tailored monitoring and cost management solutions have become necessary, their rightsizing recommendations help you in reducing your dependence on overprovisioned resources.
  4. How to handle spot instances?
    When compared to their typical on-demand offering, cloud service providers sell their unused capacity at drastically lower pricing. Spot instances on AWS are available at a savings of up to 90%.However, using spot instances is not as simple as it appears. Because you’re bidding on spare computing resources, you never know how long they’ll be available. There are spot instances with a predetermined duration; for example, AWS has a type that guarantees an uninterrupted time guarantee of up to 6 hours.However, providers can reclaim the spot instance you’re using at any time, with as little time as 2 minutes. 

    If you want to use spot instances, you must accept that they are definitely not the best option for workloads that are critical or cannot endure downtime.Despite the drawbacks, spot instances are ideal for stateless systems that can be scaled out, i.e. have a replica. Fortunately, because Kubernetes was created for this type of setup, most services in current systems are stateless.The following is an example of how to work with spot instances:
    • You must qualify your workloads and their ability to deal with interruptions.
    • Then you should look over the options provided by your seller and choose the ones that will best suit your demands. As a basic rule, select less popular instances and monitor their frequency of interruptions.
    • Now is the time to deliberately establish the maximum bid to avoid any potential delays if the price rises.
    • To maximize your chances of getting spot instances filled, consider managing them in groups and requesting different types.
  5. Unable to handle drops and spikes in demand?
    Engineers working on large infrastructures understand how quickly things can change. Instant sales surges can cause a website to crash as a result of the increased traffic. If you keep your tab open, traffic surges can result in a large and unexpected cloud bill, or they can cause your app to fail if you set severe resource limits.

    There are many changes in usage over time, but finding a balance between costs and performance has remained a challenge.Cloud cost management systems keep track of your consumption and notify you in real-time if it exceeds certain thresholds or if there are any anomalies. They provide you with useful recommendations on adjusting your cloud resources to your current demand.

Want to know more?

If you are struggling with/facing any of the cloud problems we’ve discussed above, schedule a demo and take a look at the solutions we have built to handle the same for you.
We will give you a complete walkthrough of it and tell you more about how it can benefit your organization.
Feel free to contact us for other DevOps-related queries at

We are hopeful that we maintain our rate of innovation, brainstorm with a lot of developers and engineers and keep delivering the latest features of our product to you. See you soon!

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