Why is your cloud spend getting out of control?

Is your monthly cloud spend in line with your budget?

Are you able to decode the invoices that your cloud providers send you? And can you accurately anticipate how much money you’ll spend in the future?

For many companies today, the answer to these questions is “NO, not really”

Cloud spends quickly go out of hand. According to the research, organizations can overspend by 70% without attaining expected value. 

For today’s CFOs, cloud management is no longer a “nice to have” — it’s mission critical. Prominent companies like Adobe, Pinterest, capital one, and Intuit have evidently struggled with managing their cloud. All of them have been surprised by sudden increases in their bills from AWS- Adobe’s bill reportedly rose 64% from 2017 to 2018, while Pinterest’s increased by 41%, and Capital One’s spiked by 73%. And it’s not just the high-end brands.

Across the board, companies are boosting their cloud spending. Small-to-medium firms spend an average of $120,000 on cloud computing, with 10% of SMBs spending $1.2 million or more. 

What that means is that getting a handle on cloud spending is easier said than done. 

Why Optimizing Your Cloud is needed?

Failing to plan for or properly forecast cloud computing costs can set you up for a surprise hike in costs. The main driver behind cloud cost optimization is likely decreased spending. But other than decreasing costs, there are also several other reasons you need to start optimizing your cloud.

– Efficiency and Performance

Choosing the right fit for the needs of your business is crucial – cloud computing services that don’t fit your business can cause overspending or underperformance. Wasted resources are inefficient resources. Taking advantage of things like load balancing and on-demand scaling can help ensure your business is using cloud computing resources efficiently and optimizing cloud cost.

Biggest contributors to huge cloud bills- 

Cloud cost management is lately the new imperative for every software company these days. Despite the numerous cloud providers or platforms available, such as Amazon Web Services (AWS), Google Cloud Platform (GCP), or Microsoft Azure, it appears that none of them adequately equip engineering teams to manage cloud expenditures. 

The reality is that cloud bills are exploding and everyone is looking for ways to bring them down. The public cloud providers probably aren’t complaining about that, but engineering and finance teams definitely are. Let’s walk through some of the mistakes that contribute to crazy cloud bills.

  • Oversee Unused Resources

Unused resources include unattached storage volumes, idle load balancers, obsolete snapshots, (which get charged per Gigabyte (GB) per month), and unused but running instances which get charged by the hour. 

If you are a developer, you might know the feeling where you are guilty of spinning up a few new EC2 instances every now and then for a small test application and then letting them run even if you’re not using them anymore. That, of course, means you’re still paying for these unused EC2 instances and it’ll hit the wallet later. This situation, where there is an uncontrolled proliferation of cloud instances is known as Cloud Sprawl. 

When a company experiences cloud sprawl, it incurs significant costs for uncontrolled instances, which are typically the consequence of development testing or shadow IT projects.

What can be done

Developers should carefully monitor their sandbox environments to ensure that compute instances that have been spun up are cleaned up or shut down when they are no longer required.

  • Taking Kubernetes Cost Visibility lightly:

Kubernetes allows developers and administrators to manage and assign computing resources to Kubernetes resources such as pods, nodes, and namespaces in container environments. However, in the context of native Kubernetes concepts such as deployment, namespace, labels, and so on, software developers are unable to visualize infrastructure expenses. Due to this lack of visibility- costs surge occurs. For example, it’s a fairly common practice to specify a resource limit on the amount of CPU (measured in cores) and memory (measured in bytes) an application can use within an ecosystem. For public cloud costs, however, this can lead to idle costs where applications are over-allocated and do not use all the resources that are reserved. Likewise, empty clusters, environments, and workspaces contribute to unallocated costs.

What can be done

Developers should use tools to monitor the performance of their applications. Keeping track of your computer’s memory, network, and storage usage can help you optimize cloud resource utilization and allocation. OpsLyft Kubernetes Cost Visibility allows you to break down allocated costs across all native Kubernetes concepts, allowing you to offer transparent, precise cost data to your teams that is reconciled with your actual cloud bill.

  • Not Right-Sizing the Resources 

Consistently reviewing and modifying your cloud computing resources to fit your needs is a bit of a task that cannot be ignored. There is no one-size-fits-all solution for each company’s unique problems and requirements. It can wreak havoc on the budget and performance if the cloud environment has incorrectly sized cloud instances. So, determining the type and size of the instance is critical.

What can be done

Companies can customize the instances based on specific use cases or start scheduling them so that they can scale up or down, as the requirement strikes. 

  • Not paying attention to the Hidden Costs of Storage Services 

Although it’s obvious that storage costs money (per GB/month), many developers overlook the fact that I/O (input/output) activities on storage files also cost money. Many of us are used to freely using read/write operations on files while developing and testing in local environments, so it’s natural that we might treat reading and writing to an AWS S3 bucket in the same way. But that’s where we have to be cautious since while working in the cloud, each of those reads and writes costs money. The cost of a request or an API call is charged by the service provider. When transferring data across regions or out of the cloud, data transfers are also charged per GB.

What can be done-

When developing data transfer jobs, developers should keep the hidden costs of storage in mind. One solution is to limit I/O to local files until you’re sure they’re cloud-ready or meet the architectural requirements to minimize these processes.

How OpsLyft can help you reduce cloud waste and cut cloud costs significantly?

As developers take on an increasing amount of responsibility for optimizing cloud costs as part of their CI/CD process, it’s critical that they have the tools to analyze their own usage and avoid expensive cloud bill mistakes before they get out of hand. OpsLyft’s platform is built with the needs of developers in mind, making it easy to get visibility at any level they need. Schedule a demo today and see how we make Cloud management a breeze for you!

Leave a Comment

Your email address will not be published.