Month: March 2023

Cloud computing has revolutionized the way businesses operate. It offers flexible, scalable, and cost-effective IT solutions. However, as businesses move their operations to the cloud, they need to pay close attention to their cost of goods sold (COGS). This metric is required to make sure they are achieving maximum profitability. COGS represents the direct costs associated with producing and delivering a product or service. It also includes the cost of cloud infrastructure, development costs, and other expenses as part of the cloud computing cost. Businesses that track this metric can understand their profitability better. Also, it helps to make informed decisions about pricing, resource allocation, cost optimization, and investment.

How to calculate COGS

Let’s say a SaaS company provides a project management tool to its customers. This company had $80,000 in allocated cloud infrastructure costs during a particular period. It includes the cost of servers, storage, and other cloud services used to deliver the app. Also, the company incurred $30,000 in other direct costs: salaries for developers and customer support.

Let’s look at COGS formula for a SaaS product. We can calculate the cost of producing and delivering the product for the period with all cloud costs included, as follows:

Allocated Cloud Infrastructure Cost + Other Direct Costs = Cost of Goods Sold

$80,000 + $30,000 = $110,000

So the cost of producing and delivering the project management tool for the period was $110,000. It includes the cost of cloud infrastructure and other direct expenses.

Cost of cloud computing in COGS

Let’s look at reasons why tracking COGS is important for businesses.

Understanding the Cost of Cloud Infrastructure

The cloud computing cost can become unpredictable. It happens because of the flexibility vendors offer to businesses to scale their IT infrastructure. Each company needs to track the cost of its resources to understand the direct costs associated with operating in the cloud. It helps in making informed decisions about resource allocation.

Optimizing Resource Utilization

Also tracking COGS can help to identify areas where the company can optimize its resource utilization. This includes identifying underutilized resources, monitoring resource usage, improving resource allocation, and results in insights for cost optimization.

Improving Pricing Strategies

COGS awareness can help businesses develop more effective pricing strategies. Companies need to monitor direct cloud costs associated with producing and delivering products or services. It allows them to set prices that cover their expenses and generate profit. Businesses can compete more effectively in the market and generate higher revenue.

Identifying Cost Savings

It is much easier to identify areas for potential cost savings while tracking COGS. It requires identifying inefficiencies, waste, and unnecessary expenses associated with cloud costs. By optimizing operations and reducing the cost of cloud computing, businesses can improve profitability and achieve long-term success.

Meeting Financial Reporting Requirements

Tracking COGS is also important for meeting financial reporting requirements. To calculate accurate financial statements, a company needs to track its direct costs and COGS. Both are necessary for gross profit, which is an important metric for investors, lenders, and other stakeholders.

Summary

In summary, tracking COGS in cloud computing is very important for businesses. It provides valuable insights into the direct costs associated with operating in the cloud. Also, it helps businesses to optimize their resource utilization, improve pricing strategies and achieve cost savings. Last but not least – it meets common financial reporting requirements. Moreover, while tracking COGS, businesses can enable cloud cost optimization to achieve higher profitability and compete more effectively in the market.

In our next articles, we’re going to find out what are the possible areas for reducing COGS and show you some of our real-life examples of achieving this goal.

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In today’s fast-paced and competitive business world, lots of organizations are constantly looking for ways to improve their operations along with mastering AWS cost optimization. One approach has merged these goals and gained significant popularity in recent years, it is FinOps. In this article, we’ll take a closer look at what FinOps is, and 5 key facts that can help you better understand it.

What is FinOps?

FinOps (short for Financial Operations) is a practice that aims to optimize cloud costs by bringing together people, processes, and tools. This approach emphasizes collaboration between finance, operations, and engineering teams to ensure that cloud spending is transparent, accurate, and aligned with business objectives. FinOps provides a framework for managing cloud costs by leveraging automation, analytics, and data-driven decision making.

The Role of Automation

Automation is a key component of FinOps. By automating the process of monitoring cloud costs, organizations can gain real-time visibility into their spending and quickly identify areas where cost savings can be achieved. For example, FinOps tools can automate the process of tagging cloud resources, which makes it easier to track costs and attribute them to specific departments or teams. Automation can also be used to enforce policies around cost optimization, such as automatically shutting down unused resources.

The Importance of Collaboration

Collaboration is another essential aspect of FinOps. To effectively manage cloud costs, finance, operations, and engineering teams must work together towards common goals. By breaking down silos between these teams, organizations can achieve a more holistic view of their cloud spending and identify opportunities for optimization. Collaboration can also lead to better decision making, as teams can leverage their diverse perspectives and expertise to make informed choices about cloud resource allocation.

The Role of Analytics

FinOps relies heavily on data analytics to inform decision making. By collecting and analyzing data about cloud spending, organizations can gain insights into where their money is going and identify areas where costs can be reduced. For example, analytics tools can be used to identify unused resources, spot trends in spending, and forecast future costs. By using data to drive decision making, organizations can optimize their cloud spending and achieve better financial outcomes.

The Benefits of FinOps

By adopting a FinOps approach, organizations can achieve greater cost transparency, which allows them to better understand their cloud spending and make informed decisions about resource allocation. FinOps also promotes collaboration and alignment between finance, operations, and engineering teams, which can lead to more efficient and effective use of cloud resources. And by leveraging automation and analytics, organizations can achieve significant cost savings, which can free up resources for other strategic initiatives.

Summary

In summary, FinOps is a practice that brings together people, processes, and tools to optimize cloud costs. It relies on automation, collaboration, and data analytics to achieve greater cost transparency and identify opportunities for cost savings. By adopting a FinOps approach, organizations can achieve better financial outcomes and free up resources for other strategic initiatives. If you’re looking to improve your organization’s cloud cost management, FinOps is definitely worth exploring.

Elastic Compute Cloud is a cloud computing service provided by Amazon Web Services (AWS) that offers users the ability to rent virtual machines in the cloud via the scalable computing service known as EC2. EC2 instances are virtual servers that provide users with various computing resources such as CPU, memory, and storage. These instances can be tailored to a user’s needs and utilized for various tasks including program operation, website hosting, and big data analysis. One of the popular cloud cost optimization questions we get is if one can really save money by choosing appropriate instance type? Yes, its possible, but you need alway track the latest updates on types and generations to make the most appropriate choice that fits your needs and of course be aware of current pricing models. Our team prepared a short cheat sheet that may be useful for beginners. 

Existing EC2 Types

Currently, there are over 200 different EC2 instance types available through Amazon, each with distinctive features and costs. These instances can be divided into several categories including general-purpose, compute-, memory-, storage-, and GPU- and FPGA-optimized instances. 

General-purpose instances	This type can be used for a variety of workloads, including development and test environments, small- to medium-sized databases, and web and application servers.
Compute-optimized instances	These are best for high-performance computing applications including batch processing, video transcoding, and scientific modeling.
Memory-optimized instances	This type of instances is designed for memory-intensive applications like high-performance databases, large data analytics, and in-memory caches
Storage-optimized instances	Instances of this type is an ideal choice for databases, data warehouses, and big data processing.
GPU instances	This is a good item to choose when searching something tailored for demanding graphic workloads such as machine learning, scientific simulations, and video rendering.
FPGA instances	A type of instances that are optimized to accelerate specialized applications such as financial modeling and genomics research.

Instance generation

Remember, that EC2 instance generations are a way to group comparable instance types that are released at the same time. Each instance creation includes several instance types tailored for specific workloads and or use cases. For example, the M5 generation of general-purpose instances includes the M5d, M5a, and M5n instance types.The M5d instance type is optimized for applications that require high-speed, low-latency local storage, while the M5a instance type is designed for applications that require a balance of compute and memory resources. The M5n instance type, on the other hand, is optimized for applications that require high-speed networking. By grouping these instances into a generation, users can easily compare and choose the best instance type for their workload.

Remember about pricing model

AWS provides users with three pricing tiers for EC2 instances: on-demand, reserved, and spot. With on-demand instances, users can pay for compute power by the hour without any upfront payments or long-term obligations. Reserved instances offer a considerable hourly cost savings in exchange for a one- or three-year commitment. Spot instances allow users to bid on available EC2 capacity, and the hourly price is determined by supply and demand. Choose pricing wisely to get the most benefit from the instances you’ve chosen. 

Summary

In conclusion, EC2 instance types offer users a variety of choices to meet their computing needs. Understanding the various instance types and how they can be optimized will enable users to select the best instance type for their workload. AWS also offers pricing options that allow users to tailor their charges based on their needs. EC2 instances enable users to create scalable and cost-effective cloud applications.