October 2024

DigitalEx is pleased to announce the general availability of our October 2024 release. These release notes outline the new features and changes included. Please review the release notes to stay informed on changes to the platform and to take advantage of the new features and improvements. If you have any questions, please reach out to your dedicated DigitalEx representative.

Amazon Elastic Kubernetes Service (EKS) Support

We are pleased to announce the addition of Amazon Elastic Kubernetes Service (EKS) support to our existing Kubernetes Cost dashboard feature, which already supports AKS and on-premises Kubernetes environments. This latest addition allows users to seamlessly integrate their EKS clusters and instantly gain full visibility and detailed breakdowns of costs, providing a single, unified, and comprehensive view of Kubernetes workloads and infrastructure expenses on AWS. This feature streamlines Kubernetes cost management, enabling users to optimize their EKS environments, identify cost-saving opportunities, and improve overall efficiency.

Azure DevOps Integration

DigitalEx has further advanced the recommendation tracking and backlog management feature by adding a new integration option for Azure DevOps. This new integration option provides a greater flexibility for users to choose and use their preferred and/or existing ticket backlog and workflow management tools. Users can now manage their ticket backlogs within DigitalEx’s internal ticketing system, Jira, ServiceNow, or Azure DevOps - providing four integration options in total. This expanded integration ensures that users can seamlessly align their workflows with their preferred ticketing solution, optimizing their efficiency and workflow management.

Cost Allocations Advanced RI/SP Distribution BETA

We have enhanced our Cost Allocations feature with a new RI/SP distribution shared cost option, providing multiple ways to allocate shared commitment costs and discounts across multiple teams or departments. Users can now distribute these costs evenly, proportionally, using custom rules, or fairly based on each resource’s actual on-demand usage. This flexibility allows organizations to choose the allocation method that best aligns with their cost management goals, whether aiming for simplicity, precise tracking, or equitable distribution based on usage. These allocation methods empowers finance and operations teams to customize cost distribution more effectively, leading to more accurate reporting, deeper insights into resource consumption across teams or departments, and the identification of further optimization opportunities.

Other Enhancements

We've also made several other enhancements across the platform to improve your experience with DigitalEx. Some of these improvements include:

Cost Allocations Unit Economics PREVIEW

We have enhanced our Cost Allocations feature by introducing the ability to apply Unit Economics through the definition of ‘Number of Units’, which can represent metrics such as number of users, transactions, and more. These metrics units can be updated monthly, either through the user interface or via APIs, offering flexibility in tracking and managing cost allocations.

Cost Allocations Advanced Filters

We have also introduced advanced filtering option within the Cost Allocations feature, where users can now create more precise and flexible cost allocations by applying complex filters. These advanced filters provide greater customization, allowing users to define specific allocation criteria using various operators to meet their unique needs.

Advanced Filter: NOT CONTAINS Operator

We have enhanced our Advanced Filter capabilities by introducing the NOT CONTAINS operator option. These new additions offer users greater precision and flexibility when searching for specific data or resources, allowing them to filter results based on values that doesn’t contain certain characters or strings. This makes it easier for users to target and locate data or resources that match specific patterns, significantly improving the efficiency of searches across large datasets.