Optimising Cloud Cost Management to Maximising ROI

A business’s cloud infrastructure needs will evolve with its growth. A report by the State of Cloud Costs (2024) shares that 58% of companies report that their cloud costs are too high. These costs will continue to increase without strategic cost management and optimisation.

Effective cloud cost management is about optimising cloud resources utilisation, gaining transparency in usage patterns, and minimising waste. In their effort to reduce cloud costs 59% startups and SMEs are bringing architecture changes while 43% are reducing wastage.

Cloud cost optimisation is now essential, but it’s a complex process involving multiple variables. Companies with a multi-cloud environment must figure out how to tackle dynamic pricing, evolving needs, etc. to figure out what strategies are needed and how to implement them for the greater good.

Understanding Types of Cloud Costs

A business’s cloud infrastructure needs will evolve with its growth. A report by the State of Cloud Costs (2024) shares that 58% of companies report that their cloud costs are too high. These costs will continue to increase without strategic cost management and optimisation.

Effective cloud cost management is about optimising cloud resources utilisation, gaining transparency in usage patterns, and minimising waste. In their effort to reduce cloud costs 59% startups and SMEs are bringing architecture changes while 43% are reducing wastage.

Cloud cost optimisation is now essential, but it’s a complex process involving multiple variables. Companies with a multi-cloud environment must figure out how to tackle dynamic pricing, evolving needs, etc. to figure out what strategies are needed and how to implement them for the greater good.

Understanding Types of Cloud Costs

Cloud costs define the expenses associated with using cloud computing services and tools. These costs can vary based on services businesses utilise, pricing models, and organisation needs.

Types of Cloud Costs

Compute Costs: This refers to the cost of using Virtual Machines (VMs), containers, hardware resources, and serverless functions, which are generally grouped into instances.

Customers are charged based on the instance type and their duration. Compute costs have the highest share among all cloud cost types and rightsizing instances and auto-scaling resources to match requirements in real-time can optimise costs.

Storage Costs: Including hot (frequently accessed) and cold (occasionally accessed), storage costs are added when data is stored in cloud memory. Where hot storage has higher costs, cold storage is less expensive, credited to its usage and accessibility.

But as data accumulates overtime, costs can increase substantially, which means effective data management is essential to control costs.

Networking Costs: These costs include bandwidth charges, which are the cost of moving data out of the cloud (egress) and into the cloud (ingress). Customers are also charged based on data transfer between zones, regions, and external services.

Hidden Cloud Costs

Data Transfer Costs: It’s a simple task to cut, copy, and paste data. However, what you might not know is that data transfer is chargeable and the costs can mount up based on the service provider and region.

Organisations with a multi-cloud strategy and globally distributed services completing frequent data transfers can compound over time and lead to higher unexpected costs.

Underutilised Resources: Underutilisation of cloud instances, including virtual machines, storage volumes, etc., amounts to waste of resources. These are resources you are paying for according to the usage.

If you keep servers running 24/7, but they are only needed for a few hours, you will end up paying storage fees when the data stored is rarely accessed. Hence, deallocate resources after project completion or check if they are not running idle.

Mismanaged Licenses: Even though your cloud services provider will offer several operational licenses to run your systems, you may not need all of them. Mismanagement occurs when you purchase more licenses than required or forget to cancel existing licenses, which are no longer needed.

Identifying, understanding, and optimising the internal processes to check and manage cloud and hidden costs is even more important. Doing so will help you save substantial costs while learning ways to mitigate them as you move forward.

Key Strategies for Optimising Cloud Costs

Cloud cost optimisation isn’t a one-time event. It’s a dynamic, ongoing process that must change according to the needs while following the basic structure.

Right Sizing Resources

Right-sizing, as the name suggests, is about analysing cloud resources’ utilisation against your organisation’s performance metrics.

Through this, determine whether you are using all the resources efficiently to decide corrective actions. This includes aligning the usage resources and modifying the infrastructure as needed.

Depending on the requirements, you may upgrade, downgrade, or even downsize cloud resource utilisation. Right-sizing is crucial for cloud cost optimisation as it ensures you only pay for the computing power you are actively using.

Moreover, this ensures right instance size aligns resource allocation with actual demand, effectively removing the barriers caused by underpowered resources.

AWS offers a myriad of tools like AWS Cost Explorer, AWS CloudWatch, and AWS Compute Optimiser to help organisations identify gaps and optimise resource utilisation. Using these resources, you can choose the right size based on the following:

• Usage patterns
• Variable and predictable load
• Temporary workloads
• Turn off idle instances
• Select the right instance cohort.

Discovery saved 61% in Total Cost of Ownership (TCO) after analysis done with AWS Cloud Economics. The analysis led the organisation, which stores 15 petabytes of broadcast content at any given time, to downsize server racks and use reserved instances.

Reserved Instances and Spot Instances

Reserve instances are about holding a specific amount of computing power for a fixed time. Committing to a long-term contract leads to significant cost-savings on the monthly or hourly usage prices.

However, the savings are subject to all costs paid upfront. You can also choose from partial or zero upfront payments accompanied by a higher hourly rate compared to all upfront transactions.

Spot instances are about bidding on excess resources or unused capacity with a cloud service provider. They are generally used for non-critical workloads and often come with a heavy discount, up to 90%, but there’s a catch.

Cloud service providers can terminate the spot instances contract within a short notice period. For AWS, it’s only 2 minutes. These two minutes are supposed to help organisations save application state and update log files.

How to Use Spot and Reserved Instances Together for Best Cost Optimisation?

The best approach is to move forward and use both reserved and spot instances together in a way that saves you the maximum money without compromising on work.

Identify Critical vs Non-Critical Workloads: Use reserved instances for workloads that require constant uptime and uninterrupted server access. Go for spot instances with workloads with flexible time schedules and which can be restarted when interrupted.

Use Auto Scaling Policies: Auto-scaling automatically scales spot instances when they are available at a lower price without affecting the core workloads on reserved instances.

Automating Cost Management

When manual cloud cost management gets challenging, try automating cost monitoring, resource allocation, and optimisation. Whether with in-built monitoring tools or third-party integrations, these tools can track usage patterns and detect inefficiencies to automatically adjust settings or send notifications about the same.

Popular tools include:

• AWS Cost Explorer: Let’s organisations visualise trends in usage patterns and forecast cloud costs based on existing usage patterns.
• Azure Cost Management: Offers detailed cost analysis and recommendations for optimizing budgets.
• Google Cloud Cost Management: Scales cloud resources based on demand with preemptive budget setting and cost alerts.
• When combining automation with scheduled scaling, you can get an even better execution of cloud resources. Scaling cloud resources for a growing organization is a necessary activity, but it requires careful planning to prevent cost overruns.

In scheduled scaling, you can set rules to automatically increase or decrease cloud resource utilisation. It not only reduces wastage of resources but also ensures you deliver services with maximum efficiency.

All of this works in real time based on predefined triggers. For instance, if memory usage exceeds 80%, the cloud services platform will automatically provision additional resources and reduce them when demand decreases.

Infrastructure Monitoring and Optimisation

Infrastructure monitoring includes managing and optimising cloud computing costs, including resources and service analysis and whether they align with performance metrics. This information is used to identify inefficiencies and underutilised resources to implement cost-saving measures.

Offers Detailed Visibility in Real-Time: Continuous infrastructure monitoring provides up-to-date insights into the usage of cloud resources. This information lets organisations spot resource consumption trends and patterns, ensuring the costs paid are according to the resource utilised.

Proactive Performance Optimisation: Monitoring CPU utilisation, memory usage, disk I/O, and network bandwidth makes it easier to identify performance issues and bottlenecks. Knowing these, allows for changes in the resource requirements and optimizing usage of instances, leading to cost savings.

Infrastructure Monitoring Tools for Resource and Cost Optimisation

Regardless of their location, infrastructure monitoring has crucial implications for I&O leaders and helps collate the availability of resources and ensure effective utilisation.

Middleware: Middleware offers a full-stack cloud observability platform, assisting you with real-time on cloud performance facilitating tracking network throughput, memory usage, and CPU utilisation, along with disk I/O. This lets you track the health of servers, containers, and the applications working on the cloud in real-time.

With this information, you can identify performance bottlenecks and optimise resources to ensure optimal utilisation and prevent downtime. Middleware lets you customise dashboards for extracting information on Kubernetes performance. Lastly, use Middleware’s automated alert system to receive notifications on potential issues and make quick changes to ensure perk system efficiency and performance.

How Middleware Helped Revenium in Optimising Observability Costs?

Cloud cost management is a challenging process for businesses, given the complexity of multitude of variables involved in the process. One of these variables are observability costs, which takes up to 30% of the total infrastructure monitoring costs. This is the amount spent on tools and services employed to monitor (observe) the performance and availability of the cloud infrastructure.

Middleware is enabling Revenium to reduce their observability costs by over 10X. Taking advantage of Middleware’s friendly features and tools, Revenium connected its business data with Middleware’s telemetry data.

Middleware helps Revenium overcome observability challenges including ECS monitoring, track critical business events, and gain insights into customer interaction, transaction volume, and error rates. Access to this information, allow the client to make changes and reduce observability costs by 10X.

Grafana: An open-source platform popular for its visualisation and integrations, Grafana brings together data from multiple sources to help you decipher cloud infrastructure metrics. As you visualise data from customisable dashboards that update in real time, it’s easier to track KPIs, detect trends, and set up anomaly detection alerts.

Prometheus: Prometheus automatically collects metrics about different tools and services in real-time and stores the data in a time-series format. This makes data analysis at a later date easier and lets you identify trends for resource utilisation and issues and trigger alerts according to predefined rules. Prometheus and Grafana can be paired for advanced data visualisation analytics for a detailed analysis of the cloud infrastructure.

Datadog: Datadog is popular for real-time visibility into the cloud infrastructure, applications, and cloud services. With support for multi-cloud environments, Datadog also offers a unified dashboard to group information from various cloud providers and analyze their usage, performance, and costs. You can also set real-time alerts to detect anomalies, schedule scaling, and set notification alerts to monitor usage patterns.

Implementing a Cloud Cost Management Framework

Experts recommend taking the “Crawl, Walk, and Run” approach prompting organisations to take quick action but gradually expand the size of their cloud strategy as the situation requires. Cloud cost management framework is implemented in two parts;

Develop a Cost Management Strategy

Assessment: Consider the existing cloud storage utilisation of every department, application, and resource to understand the existing cloud spend. Don’t miss EC2 instances, spot instances, Storage costs, reserved instances, data ingress, egress costs, and others.

This will help:

• Review existing cloud infrastructure and workloads.
• Identify areas of inefficiency like knowing underutilised and idle resources and unexpected cost spikes.
• Calculate the Total Cost of Ownership (TCO).

Goal Setting: Set realistic, measurable, and specific goals regarding cost reduction and visibility. Following this approach, the goals you set will be easier to track and measure. Combine these with cost management-related performance goals, like improving resource utilisation, avoiding cost overruns, and achieving better cost visibility.

Tools Selection: You can track and assess set goals easily only with the right tools. Choose a tool that can help you monitor, optimise, and automate your cloud infrastructure. Consider tools with the following features:

• Cost management
• Automation
• Real-time monitoring
• Scheduled scaling
• Expense visibility
• Security
• Compliance
• Unified view
• Budgeting
• Forecasting

Incorporating Infrastructure Monitoring

Infrastructure monitoring includes tracking performance and health of IT infrastructure components to ensure their continuous operation and reliability to maintain overall efficiency. Track metrics like memory and CPU usage along with network traffic and disk performance to analyse system health and make changes with the best-fit tools to obtain crucial information in real-time.

Implementing infrastructure monitoring ensures improved system uptime and proactive issue resolution. Furthermore, effective analysis leads to optimise resource utilisation and improve capacity planning.

With Middleware infrastructure monitoring, you can monitor website, web application, and serverless functions performance and availability. Infrastructure monitoring tool integrates with GitLab CI/CD, AWS Lambda or S3 Triggers, ensuring you can monitor all cloud-enabled applications.

Regular Review and Adjustment

Cloud cost management is an ongoing process. Don’t expect it to deliver results with one-time execution. Regular review of usage, costs, and performance metrics can ensure your cost management strategy is working as intended.

As a part of the review process, stay up-to-date with the latest technological advancements, pricing models, and dynamics of business requirements.

Conclusion

Cloud cost optimisation is an evolving process and businesses are now focusing on using automation and AI-driven analytics to further enhance cost efficiency. Going forward, AI-powered assistants will help keep an eye on the cloud management systems 24/7 and provide real-time information for cost-analysis and predict future expenses.

While using advanced technologies will be crucial, ensure you are also updating the existing systems for smooth integration and run a cost-benefit analysis before implementation to maximise benefits.