Data Management Glossary
Cloud Cost Optimization
Cloud cost optimization is a process to reduce operating costs in the cloud while maintaining or improving the quality of cloud services. It involves identifying and addressing areas to reduce the use of cloud resources, select more cost-effective cloud services, or deploy better management practices, including data management.
The cloud is highly flexible and scalable, but it also involves ongoing and sometimes hidden costs, including usage fees, egress fees, storage costs, and network fees. If not managed properly, these costs can quickly become a significant burden for organizations.
In one of our 2023 data management predictions posts, we noted:
Managing the cost and complexity of cloud infrastructure will be Job No. 1 for enterprise IT in 2023. Cloud spending will continue, although at perhaps a more measured pace during uncertain economic times. What will be paramount is to have the best data possible on cloud assets to make sound decisions on where to move data and how to manage it for cost efficiency, performance, and analytics projects. Data insights will also be important for migration planning, spend management (FinOps), and to meet governance requirements for unstructured data management. These are the trends we’re tracking for cloud data management, which will give IT directors precise guidance to maximize data value and minimize cloud waste.
Steps to Optimize Cloud Costs
To optimize cloud costs, organizations can take several steps, including:
- Right-sizing: Choose the correct size and configuration of cloud resources to meet the needs of the application, avoiding overprovisioning or underprovisioning.
- Resource utilization: Monitor the use of cloud resources to reduce waste and improve cost efficiency.
- Cost allocation: Implement cost allocation and tracking practices to better understand cloud costs and improve accountability.
- Reserved instances: Use reserved instances to reduce costs by committing to a certain level of usage for a longer term.
- Cost optimization tools: These tools identify areas for savings and help manage cloud expenses.
The Challenge of Managing Cloud Data
Managing cloud data costs takes significant manual effort, multiple tools, and constant monitoring. As a result, companies are using less than 20% of the cloud cost-saving options available to them. “Bucket sprawl” makes matter worse, as users easily create accounts and buckets and fill them with data—some of which is never accessed again.
When trying to optimize cloud data, cloud administrators contend with poor visibility and complexity of data management:
- How can you know your cloud data?
- How fast is cloud data growing and who’s using it?
- How much is active vs. how much is cold?
- How can you dig deeper to optimize across object sizes and storage classes?
How can you make managing data and costs manageable?
- It’s hard to decipher complicated cost structures.
- Need more information to manage data better, e.g., when was an object last accessed?
- Factoring in multiple billable dimensions and costs is extremely complex: storage, access, retrievals, API,
transitions, initial transfer, and minimal storage-time costs.
- There are unexpected costs of moving data across different storage classes (e.g., Amazon S3 Standard to S3
Glacier). If access isn’t continually monitored, and data is not moved back up when it gets hot, you will face
expensive retrieval fees
These issues are further compounded as enterprises move toward a multicloud approach and require a single set
of tools, policies, and workflow to optimize and manage data residing within and across clouds.
Komprise Cloud Data Management
Reduce cloud storage costs by more than 50% with Komprise.
Cloud providers offer a range of storage services. Generally, there are storage classes with higher performance
and costs for hot and warm data, such as Amazon S3 Standard and S3 Standard-IA, and there are storage classes
with much lower performance and costs that are appropriate for cold data, such as S3 Glacier and S3 Glacier Deep
Archive. Data access fees and retrieval fees for the lower cost storage classes are much higher than that of the
higher performance and higher cost storage classes. To maximize savings, you need an automated unstructured data management solution that takes into account data access patterns to dynamically and cost optimally move data across storage classes (e.g., Amazon S3 Standard to S3 Standard-IA or S3 Standard-IA to S3 Glacier) and across multi-vendor storage services (e.g., NetApp Cloud Volumes ONTAP to Amazon S3 Standard to S3 Standard-IA to S3 Glacier to S3 Glacier Deep Archive). While some limited manual data movement through Object Lifecycle Management policies based on modified times
or intelligent tiering is available from the cloud providers, these approaches offer limited savings and involve hidden
Komprise automates full lifecycle management across multi-vendor cloud storage classes using intelligence from data
usage patterns to maximize your savings without heavy lifting. Read the white paper to see how you can save +50% on cloud storage cost savings.