Working with Engineering to Reduce Cloud Costs

Cloud platforms provide organizations the opportunity for dynamic decision-making and rapid innovation with no capital investment. Plus, there are many other benefits. Organizations need to adopt the cloud and rethink their operational expenditure with the pay-as-you-go model to gain a competitive edge in an increasingly aggressive digital economy.

The pay-as-you-go model enables development teams to deploy new services or increase the capacity of existing services by quickly spinning up more resources — like virtual machines (VMs), memory, and disks. This model enables lead times of hours rather than days and weeks without getting stuck with outdated infrastructure.

In this model, cloud providers charge for all created resources, not just actual use. Engineers rarely go back to validate the actual usage of the infrastructure they built. Usually, they’ll only review resources once the finance team raises concerns about a hefty monthly bill. Then, all teams are tasked with optimizing their infrastructure use.

Traditionally, organizations have used on-premises infrastructure with a central data center team that controlled and maintained all infrastructure. These physical resources were associated with the enterprise’s different development teams. Infrastructure expansion was complex and only happened a few times throughout the year. With this method, calculating the overall cost was reasonably straightforward, as costs aggregated across different teams. This method allowed organizations to budget their spending across various groups in a controlled manner.

However, cloud spending complicates this cost allocation, as individuals spin up new resources as needed. In this article, we’ll discuss how the right tools can help FinOps allocate costs to the correct teams, and how we can reduce cloud costs to ensure the budgeted spend focuses on value-added projects.

Delivery Priorities

Engineering teams understandably place top priority on features and performance. These priorities align well with the modern distributed cloud architecture, which offers agility, scalability, extensibility, and redundancy. The benefits require a decentralized self-service approach that empowers all teams to create infrastructure as per their demands.

Often, these teams are unaware of any budget constraints, so they don’t consider infrastructure costs. As a result, teams might provide more redundancy resources than they need to ensure applications run without interruption.

Typically, infrastructure costs gain attention when bill shock occurs, but that is quite late to consider application design and usage changes. At that time, FinOps assigns teams the task of understanding their cloud use to cut back on non-optimal resources. However, this remains a one-time activity, and development teams still don’t prioritize cost management.

Enterprises performing digital transformation programs need an effective cost tracking and optimization process to migrate their legacy applications to the cloud infrastructure. The traditional approach of allocating and reporting costs doesn’t work with the cloud, as the complete infrastructure is dynamic.

Instead, organizations must invest in creating mature practices that can deliver effective cost management as an integral part of their cloud adoption plans. Analyzing operational data and determining cost optimization opportunities can help overcome cloud spending challenges.

Cost Allocation

The best way to raise cost awareness is to make users aware of the expense and the associated resource use. Start making costs visible in the organization. While this may sound obvious, it’s challenging to do well — especially as infrastructure resources change regularly.

Organizations must reasonably attribute costs to their origins, depending on the business context. The organization may look to the level of the developer, project, application, service, business unit, or anything else. There are many ways to do this, but infrastructure tagging is the most mature practice. Various cloud services and vendors support this practice. As a result, organizations can build visibility into these costs and uncover potential inefficiencies that help drive management decisions. Managers may decide to keep spending piles of money on cloud resources that drive revenue while cutting unused resources or unprofitable projects.


When organizations know how much they are spending, they can attribute this spending to the correct stakeholders. Users of each resource (development team) should have ownership of their respective cloud resources. Supporting teams with an accurate view of their resource use empowers them to build their infrastructure use strategy. Organizations can also use this spending data to generate notifications of deviations and irregularities, such as idle data processing nodes.

Effective cost control requires ownership and accountability. Organizations can only reach their cost reduction objective if teams take ownership and responsibility for the cloud resources they use and are accountable for their costs.

Cost-Control Recommendations

After the organization lays down the foundations of cost monitoring, the next step is flagging and resolving cost inefficiencies. Teams tend to highly over-provision their resources, causing significant resource waste and cost inefficiencies. This approach may work in the shorter run to address traffic spikes but leads to high usage costs. Proactively rightsizing resources, in contrast, can produce significant cost savings.

Enterprises need to invest in building their recommended best practices, creating a knowledge pool of practical guidelines. These policies’ main goals are to speed the time to market (TTM) with acceptable product performance and profitability. The guidelines form the basis of cloud capacity planning, application design, and deployment. Leadership must communicate with teams to adopt the guideline principles for effective product development.

Engineering for Profitability

The responsibility for preventing cloud infrastructure budget overruns doesn’t rest on a single team: It requires close collaboration between development, operations, and finance teams. This collaboration establishes a direct link between product margins and cost-optimized engineering solutions. Enterprises need to develop tools and processes to segment the total cost and use operational data to determine its correlation with resource use.

Operations teams should be able to correlate the cost with the different environments they own. DevOps teams create automation scripts to spin up and upgrade environments, and they can use the same techniques to lower the costs of running these environments.

Development teams often need many environments such as development, quality assurance (QA), user acceptance testing (UAT), production, and disaster recovery (DR), to name a few. Creating environments with sizes that match production is helpful for only a few of these environments, like UAT and DR. The remaining environments can work on far fewer resources. Also, controlling the uptime of all environments, including production, can lead to significant cost benefits.

Moreover, the operations teams are well aware of inefficiencies in resource use. They often monitor the application use and thus can flag under-utilization. Development teams can employ this empirical data to optimize application resources.

Empowering development teams with spending and resource use information enables them to plan capacity, like sizing cloud deployments and sharing capacity across multiple environments. The ecosystem also allows developers to build alternative designs and evaluate these designs for cost-effectiveness. As a result, the information helps instill a mindset that costs are another set of non-functional requirements.

Particularly as cloud costs rise, improving processes enables organizations to enhance cloud efficiencies and optimize costs. To do this, organizations need a coherent solution that performs cost allocation and reporting, manages budgets, and forecasts future spends without restricting developers’ technical autonomy.

Cost allocation can be time-consuming to organize manually, so cloud cost management must provide automated resource tagging that allocates costs to match the organization’s hierarchy of divisions, projects, teams, and more. Rich reporting dashboards must offer a single pane to correlate the price with cloud use patterns and derive actionable outcomes.

Next Steps

Cloud only works if you have effective governance around resource use. Without this discipline, organizations end up paying for resources that they no longer use.

As FinOps and engineering access spending information, both teams work together to pinpoint opportunities for cost savings. This cooperation helps everyone as budgets increase for projects that add value for customers and the company.

Yotascale provides a comprehensive cloud cost management solution that enables enterprises to better understand their cost metrics through automated resource tagging, informative cost projections, overspend alerts, and many more features. Even if you don’t think your cloud spending is out of control, breaking down your spending and tracking it over time can help you pinpoint cost-saving opportunities. Visit Yotascale for a demo and free trial to find cost-saving opportunities within your organization.

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