Why Optimizing Cloud Costs Become A Priority For Enterprises?

Market Insights


With consumption-based cost models of cloud computing services for infrastructure and operations management, you pay for what you use, but you also pay for what you provision and don’t use. Organizations have quickly realized this transition and identified the strategic gap that traditional methods of managing infrastructure spending in the physical world don’t translate to the cloud. And it is leading to an unexpected and increasingly heavy bill.

In the world of cost optimization, it’s not about just cutting costs. It’s about identifying waste and ensuring you are maximizing the value of every dollar spent.

Advocating for and establishing continuous governance and optimization practices within organizations is a timely endeavor as 61 percent of cloud users affirm that cost optimization is a priority – stated Statista.

As a result, IT organizations are driving cost optimization by monitoring resources’ utilization and capacity metrics or rightsizing allocation-based services. Adopting the cost optimization initiatives enables them to make the maximum usage of cloud services, continue the momentum of innovation, and have a repeated cost-cutting cycle.

Let’s discuss more mature cloud cost management strategies that enterprises can use and adjust cloud application costs in different sections such as Compute, Storage, Network, and Database.


Compute Infrastructure is one of the largest parts of an organization’s cloud bill, and as a result, it is also one of the most significant opportunities to reduce costs. Here are some key ways to reduce those costs.

Adopt lean provisioning and rightsizing

In most of the cases, companies are running instances 24*7. To optimize the cost, you can release unused capacity while eliminating zombie assets with low utilization and identify over provisioned instances through monitoring or regular load testing used for instance standardization.

Leverage Auto-scaling

To meet the variable demand over time, you can scale up/down workloads. Adopting horizontal auto-scaling helps you increase or decrease resources in response to traffic and demand.

Long-term Commitment

Cloud service providers offer discounts in return for long-term commitment via reserved instances and savings plans and help you save up to 70% depending on the duration and product. You can go with the technique and optimize your workloads that are required to be running 24*7.

Utilize spot instances

You can save up to 90% on the spot instances by switching a portion of the workload to discounted instances which are known as spot instances. Using spot instances is a good practice for low-priority computing tasks that do not require high availability such as batch jobs, background processing, etc. CSPs can help you identify workloads that are fit for discounted spot instances.

Schedule Infra availability

You can schedule infrastructure availability for the selected workloads experiencing low demand for e.g. at night and during weekends. Dev/Test environments can be a good example and you can turn on/off resource consumption as you require.

Automate provision with guardrails

For non-production environments, you can provision high-tier instances to prevent engineering mistakes and avoid misconfigurations that can lead to downtime. Also, you should set up automated rules to hamper these kinds of activities.


From data lakes to repositories, storage is used heavily in various scenarios in the cloud. Also, there is an opportunity to cut the unnecessary storage costs. Let’s explore some and optimize them to reduce cloud costs.

Reduce storage buffer

Reducing storage infrastructure costs has been the opportunity for businesses to optimize the cost as it is used in a wide-ranging set of scenarios in the cloud. For storage management and monitoring utilities, you can identify orphaned volumes or snapshots and can remove them from Amazon EBS volumes, Azure Virtual Disks, or GCP Block Storage.

Storage Tiering

You can choose best-fit storage tiers and move data among them to significantly reduce cloud storage costs. For low latency and provisioned throughput, you can use solid-state disks (SSDs) and warm data to store on lower-cost spinning disks. Additional storage tiers such as Amazon S3, Azure Blob Storage, or Google Cloud Storage can be used for the workloads where latency is less demanding. Hence, you can save on an average cost reduction of 10%.


Cloud computing budgets vary significantly based on your data transfer requirements. Still, there is a way to reduce the costs without re-architecting the application. Follow the below techniques and cut some costs on unwanted networking and data transfer needs.

Reduce internet traffic across regions and zones

Network traffic plays a significant role in cloud costs. There is a need to ensure redundancy and resiliency when you transfer data between regions or availability zones. By eliminating the redundancies and duplications in data transferred, you can achieve a 10% reduction in GB transferred per day. Rebalancing services across regions and zones to minimize data transfers also provides one way to reduce these costs.

Optimize network configuration

The amount of data transfer not only impacts the cost, but also the way the network is configured. Using network services or modifying network configuration can have a huge impact on data transfer costs without affecting available throughput. For eg- Opting private IP addresses over public or elastic IP addresses wherever possible can have an impact on data transfer costs.

Managed Database

Monitoring resource utilization and capacity metrics help drive cost optimization for managed databases. You can lower unnecessary costs by scheduling/rightsizing allocation-based services and leveraging programmatic discounts. Here are some key steps to optimize database footprints in your cloud infrastructure.

Tag and track resource utilization

You can just identify the database instance and start tagging and tracking the utilization of resources. Database and application owners can quickly identify the opportunity for cost optimization. For eg- Amazon RDS sends metrics to Amazon CloudWatch every minute for each active database instance.

Define utilize policies

You would be able to know about under-utilized resources by defining the policies that include read replicas, unused instances, and primary instances. It enhances scalability and durability to right-size DB instances.

Educate and implement

After implementing above techniques, application and database owners would know about the cost optimization best practices and you can implement policies across organizations.

Learn and optimize

Finally, you can continuously monitor and identify areas for improvement while evolving policies and processes to match your workloads and organizational needs. Automation of autoscaling and right-size the instances will also make the changes in workload.

Discover how to control and align costs to your business with our Cost Optimization E-book

Reduce Cloud Cost with Successive Cloud Services

Adopting the right strategy to reduce cloud infrastructure costs demands ongoing efforts and monitoring for the resources in the cloud-environment. With the help of cloud-based tools, Successive cloud monitors cloud resources and different workloads to have better visibility, framework, guidance, and automation that could continuously optimize cloud infrastructure costs without any disruption or compromise on performance, availability, and flexibility. We enable you to lower your cloud spending by suggesting the on-going improvements in your cloud-environment.

Successive Cloud’s solutions are accessible in all the cloud environments be it public, private, or hybrid/multi-cloud. Our certified experts expand our cloud cost optimization solution for our customers to automatically optimize reserved instances, saving plans, and spot instances. We ensure your infrastructure is optimized for containers, Kubernetes, autoscaling applications, and many more.

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