Cloudability : What's new in 2023

How this feature can help you

GCP had introduced detailed billing across many services which enables you to view granular cost data at a resource level as compared to standard billing which used to provide the cost data at SKU level.

More information about the release

To set up GCP Detailed billing, you will need to:

1. Select “ Settings ” menu item from the Cloudability primary navigation menu and then from the expanded sub-menu select “ Vendor Credential s”.
2. On the Credentials page, select the navigation tab for GCP to start the process of adding GCP credentials into Cloudability.
3. Select GCP Detailed Billing option from the drop down list.
4. Add the GCP detailed billing table id .
5. Indicate the GCP GCS bucket .
6. Add the GCP detailed billing date (start year and month).
7. Download the template, run in GCP console.
8. Once completed click on Verify Credentials . A green tick indicates that the credentialing is successful.

GCP resource level costs will be available in Cloudability under Reports and Dashboards by selecting the resource id column.

How to enable automated credentialing

1. Add your linked accounts under AWS organization in the AWS console.
2. On Cloudability , while credentialing the AWS Master Payer accounts, enable the Automated credentialing of linked accounts checkbox.
3. 
4. Generate the CFT template which should be executed in the AWS console.
5. Add credential for any of your linked accounts under the AWS organization, then save and download the template, and execute for the selected linked account in the AWS console.
6. On individual linked accounts, select Edit > Download > Verify credentials to complete the credentialing of the linked accounts.

How this feature can help you

This release addresses the unique needs of our EU-based clients, ensuring their data remains within the EU boundaries. By localizing our services, we aim to empower organizations to bolster their compliance efforts and align with the regulations regarding cloud cost management data.

More information about the release

The launch of hosting Cloudability in the EU region holds great significance for our customers operating within this region. It provides a reliable and compliant cloud cost management solution that prioritizes data residency, enhances data privacy, and aligns with data protection regulations.

How this feature can help you

This feature enables detailed insights for the container resource utilization and the associated costs for clusters using the ROSA variant operating on these versions of OpenShift.

You can now easily download and deploy our metrics agent via the standard provisioning workflow.

How this feature can help you

This functionality provides the ability to generate ServiceNow request and /or incident tickets containing rightsizing recommendations automatically within your very own ServiceNow instance. This feature closely resembles the current Rightsizing ROI functionality that can integrate with the Jira Cloud.

By integrating Cloudability and ServiceNow, you can now collaborate quickly and efficiently around cloud resources and rightsizing recommendations. This automated ticketing system augments a more efficient rightsizing cadence to promote cloud optimization through normal service processes. You will also have easier accessibility to the records of the details of the recommendations within Cloudability as well as your ServiceNow platform along with actions (if any) taken on the recommendations. You can now automatically calculate and display the realized savings from resulting actions via the Rightsizing ROI page in Cloudability.

More information about the release

You can start by entering your ServiceNow vendor credentials by going to the Cloudability primary navigation menu and navigating to Settings > Vendor Credentials > ServiceNow . You can then set up a Rightsizing ROI policy by navigating to Settings > Rightsizing Policies and defining a policy to start automatically capturing rightsizing recommendations based on the criteria you have defined. This ROI policy criteria is then used to determine which rightsizing recommendations will automatically have tickets created within your ServiceNow instance.

Alternatively, rightsizing recommendations can be captured manually by navigating to the Rightsizing page under Optimize > Rightsizing and manually creating a ServiceNow request (or incident) for an individual recommendation from the menu at the right side of the recommendations table. To view the captured Rightsizing recommendations in Cloudability , navigate to Optimize > Rightsizing ROI .

How this feature can help you

This functionality is the first step towards providing Rightsizing filtering options at page-level that filter both the top recommendations as well the additional recommendation options provided in the details pane. There are new 2 options as part of this release:

1. The " Top Multi-Architecture " option which is available on Compute Rightsizing pages. This option filters the details pane recommendation options by showing at least 1 rightsizing recommendations for each CPU architecture - If there are cost savings available for the CPU architecture. The recommendations in the details pane still display in order of greatest cost savings.

2. The " Count Reduction Only " option available on Compute Group Rightsizing pages (currently ASG, MIG). This option filters all recommendations by showing the ones only which reduce the number of instances in the group.

More information about the release

This release benefits by providing you more options for which rightsizing recommendations can be filtered in order to meet your use cases and enhance usability. Additionally, having page-level filtering options that can filter both the top recommendations provided on the page as well as the additional recommendation options provided in the details pane allows more comprehensive filtering possibilities when you require this level of granularity to take appropriate cost saving actions.

From the Cloudability primary navigation menu, under the Optimize menu item select the option for Rightsizing . The " Top Multi-Architecture " option is available on the Compute Rightsizing page for each vendor (for example, AWS’s compute rightsizing page is EC2). The " Count Reduction Only " option is available on the Compute Group Rightsizing page for each vendor (for example, AWS’s compute group rightsizing page is EC2 ASG). Both options will be located near the top of their respective pages next to the current “Filters” that are already provided.

Users can now seamlessly map and manage all their Kubernetes (K8s) clusters across OCI, AWS, Azure, and GCP, as we are extending support to OKE.

Key highlights of this release include:

• Container Cost Allocation: Explore and visualize costs for all OKE clusters, categorized by Namespaces and Labels.
• Enhanced Reporting: Cluster Name, Namespace, and Label dimensions are available in core reporting, including reports, dashboards, and TrueCost Explorer.
• Business Mapping & Views: Allocate and categorize containerized costs in tandem with regular cloud costs.
• Rightsizing Recommendations: Optimize resource utilization and cost efficiency by receiving recommendations to align request and limit values with the actual workload requirements, reducing waste and expenses.

How this feature can help you

As an Azure user, you have the flexibility to build this list from resources spanning multiple accounts and choose from different measures (dimensions and metrics) to surface the details relevant to them. This information available for each cloud resource unifies billing, utilization and descriptive meta data to provide you with a more comprehensive inventory view.

Azure Resource Inventory reporting feature must be explicitly enabled for your Cloudability Org. You must reach out to your TAM/CSM/account point of contact from Apptio to get this done. By default, only Admin or Cloudability Admin roles will be able to access this feature. However, inventory access can also be granted to any custom role by assigning the custom role with AWSResourceInventoryFullAccess permissions.

More information about the release

You can view month-to-date inventory data for each service. Upon enabling this feature, resource inventory data will be back filled to the beginning of the current month. Over time, inventory data will be available on a three-month rolling window. That is at any point in time, you will be able to access resource inventory data for the current month along with the previous two months. You have the option to export the reports in CSV format. These exports include all the columns supported for the particular service (i.e., there is no 20 column limit).

How this feature can help you

Typically, when you modify your business strategy, there is a need to adjust Business Mappings, Account Groups, and Tags & Labels in Cloudability with a retrospective refresh of historical data. This is where a data reprocess comes into the picture. If you are a Cloudability customer you might only need reprocessing within Cloudability , however if you use Costing & Planning as well, your actions involve exporting data to Costing & Planning too.

The existing daily reprocess job is mostly focused on reprocessing the current month data. To reprocess the historical data, the current process requires you need to raise a support ticket. This manual process is both support dependent and time-consuming, and is something we are looking at eliminating with this release.

More information about the release

The feature can be accessed by navigating to Organize > Data Reprocess in Cloudability or Cloud Data Ingestion (CDI).

The feature has two different workflows for two different user personas: Cloudability Only Data Reprocess and Cloudability - Costing & Planning Data Reprocess.

The feature has the following limitations in terms of the number of requests that can be submitted in a month.

• Only Cloudability users with an "Admin" role and Cloud Data Ingestion (CDI) users with a "Cloud Data Ingestion" role will be able to access the feature.
• Customers will have a pre-defined number of Month-units/month.
• Customers will have a pre-defined lookback period of 12 months.
• Two reprocess requests cannot be submitted at the same time, if they have overlapping periods.

If you use only Cloudability : This is a two-step process where you can select the Period and submit the job. You can also monitor the status of the job in the Job Status tab. For detailed steps, refer to Data Reprocess for Cloudability users .

New Apptio BI Reports

This release includes the following new out-of-the-box Apptio BI Reports. These reports leverage data from the Cloudability TotalCost data source. You can find these reports on the Reports page.

TotalCost Spend - Invoice View

TotalCost Spend - Consumer View

New regions supported

The following are the newly supported Datadog regions:

• ap1.datadoghq.com

• us3.datadoghq.com
• us5.datadoghq.com

Support for the existing Datadog regions remains intact, and Cloudability users using these do not require any updates at their ends.

• datadoghq.com

• datadoghq.eu

The process of credentialing Datadog into Cloudability remains the same, with the only addition being be the new regions which you can choose from the dropdown list. For more information on connecting Datadog in Cloudability , see Connect Datadog to Cloudability .

How this feature can help you

Azure Cache for Redis and Synapse Analytics customers optimizing their spend through reservations (both Redis and Synapse Analytics), and pre-purchase plans (Synapse Analytics) can now view and manage their reservations in the Reservation Portfolio. Cloudability expands the services that Reservation Portfolio supports on the Azure Cloud in response to the growing number of customers who utilize Azure. By incorporating Azure Redis and Synapse Analytics, Cloudability provides these customers with additional benefits in terms of realizing the value of purchasing reservations on the Azure Cloud.

More information about the release

Reservations for Azure Cache for Redis and Synapse Analytics dedicated to SQL pools function similarly to Azure Compute, SQL, and Cosmos DB reservations. They are maintained regularly, and are billed hourly.

Pre-purchase plans for Azure Synapse Analytics function similarly to Databricks. These reservations are interchangeable credits that can be used across the duration of the reservation. Unlike most of the reservations, they are not maintained regularly. Our KPIs and table headers have been adjusted to properly reflect the information around the pre-purchase plan credits, and SCUs. Similar to Databricks, we've added a third chart to the details panel to help understand the burn-down on a given commitment.

These newly introduced metrics are as follows:

• Burst Balance  - Provides information about the percentage of I/O credits (for gp2) or throughput credits (for st1 and sc1) remaining in the burst bucket. Used with General Purpose SSD (gp2), Throughput Optimized HDD (st1), and Cold HDD (sc1) volumes only.

• Volume Consumed Read Write Ops  -  The total amount of read and write operations (normalized to 256K capacity units) consumed in a specified period of time. Used with Provisioned IOPS SSD volumes only.

• Volume Throughput Percentage  -  The percentage of I/O operations per second (IOPS) delivered of the total IOPS provisioned for an Amazon EBS volume. Used with Provisioned IOPS SSD volumes only.

  This metric is not supported with Multi-Attach enabled volumes

• GPU Utilization - Percentage of time over a sample period where one or more kernels on the GPU was running.

• GPU Memory Utilization - Percentage of time over a sample period where memory was being written or read.

  For successful results with GPU metrics, make sure you have configured minimal GPU metrics as a prerequisite.

How this feature can help you

This release enhances the support for AWS utilization metrics in Cloudability and enables customers to get insights into AWS EBS and GPU utilization metrics.

How this feature can help you

For current (and future) customers of both Cloudability and Turbonomic , there is optimization-related functionality & data that exist in one product but not the other. Previously there was no Out-of-the-Box integration between Cloudability and Turbonomic and therefore customers of both products would need to go to each product separately in order to utilize the functionality contained in each one. This feature will initiate the process of enhancing Cloudability allowing customers of both products to have additional Turbonomic functionality & data displayed directly in Cloudability itself.

More information about the release

In order to set up Turbonomic credentialling, select “ Settings ” menu item from the Cloudability primary navigation menu and then from the expanded sub-menu select “ Vendor Credentials ”. On the Credentials page, select the navigation tab for Turbonomic to start the process of hooking Turbonomic account credentials into Cloudability. Once the Cloudability/Turbonomic integration is set up, navigate to the new Turbonomic page by selecting " Optimize " menu item from the Cloudability primary navigation menu item and then from the expanded sub-menu select “ Turbonomic ”. The new functionality & data will be displayed starting with the Necessary Investments & Potential Savings Cloud charts and accompanying values from Turbonomic .

How this feature can help you

Currently, when container-associated metadata including namespace labels, service labels, deployment labels, and node labels shares the same label key but features different label values, these values are merged together. To enhance this, we are introducing a change to our pipeline. This change will ensure that only the most relevant label value is displayed, eliminating label concatenation.

In scenarios where container-associated metadata possesses label keys with conflicting label values, our system will prioritize the most relevant label value. The determination of relevance is based on the granularity of the resource. Here is the order of relevance (from highest to lowest):

1. Pod

2. 1st-level pod owner (e.g., ReplicaSets, Daemonsets, Jobs)

3. 2nd-level pod owner (e.g., Deployments)

4. Kubernetes Service

5. Namespace

6. Node

More information about the release

Following the release of this change to production, users will no longer encounter concatenated values under the Labels tab on the Container Insights page for data received after the release date. Additionally, users may notice higher cost allocations for label values that were previously artificially lowered due to cost being assigned to concatenated values.

• Historical data containing concatenated label values will remain unaltered.

• GKE clusters may still display concatenated label values in Reporting.

We believe this enhancement will significantly improve the clarity and precision of label representation in Container Insights, offering a more streamlined and informative user experience. We appreciate your continued support as we work to enhance our platform.

If you have any questions or require further information, please do not hesitate to contact your account team or support.

How this feature can help you

This release enables OCI customers to:

• Automatically allocate all OCI costs back to the business based on their specific rules, leveraging Cloudability business dimensions

• Analyze their OCI spend and improve team ownership by leveraging resource-level analytics, interactive multi-cloud dashboards and personalized views

• Drive financial accountability by setting up OCI budgets and event notifications

  

More information about the release

If you are already an OCI customer, you can start your cost management journey by adding credentials for your tenancy following the instructions for Connect Oracle Cloud .

By default, Cloudability will ingest the current month of OCI data after your credentials are validated. If you would like additional months of data ingested, please reach out to the Apptio team who will be happy to assist you.

For those looking for programmatic access for managing their OCI credentials please check out our public API documentation .

For more information about managing OCI costs in Cloudability please join the conversation on the Apptio Community .

How this feature can help you

Previously, Cloudability only provided instance type/ family filtering for compute rightsizing recommendations at the page level and only for the top recommendations given, with no way to filter globally or on an individual recommendation basis. This release provides a new global setting for you within Rightsizing Preferences to exclude compute recommendations containing specific instance types/ families based on exclusion values as entered.

More information about the release

Instance-related filtering and/ or exclusion already exists locally on the compute rightsizing pages using the Instance Family (New) & Instance Type (New) filters. However, these only filter recommendations that have a top recommendation with these values. This new global Rightsizing Preferences functionality provides you a mechanism to exclude all compute recommendations that meet the criteria (values) entered by you regardless of the recommendation being a top recommendation or one of the many recommendation options contained in the rightsizing details pane. There are intentional limitations that are by design on which recommendations are applicable to this exclusion mechanism– recommendations of “terminate” and “no action” will not be bound by the exclusion list as a change to the instance type/family is not actually being recommended.

From the Cloudability primary navigation menu, under the Settings menu item select the option for Rightsizing Preferences. Under Compute (VM) Preferences, there is an option to “Exclude recommendations where the recommended instance type contains the following values”. Under this option, there will be text boxes where you can enter additional values which will then exclude any compute recommendations where the instance type/ family contains these values.

You can access all your Apptio BI reports, including reports based on common FinOps use cases, innovative features, and analyze all data sources directly within Cloudability.

How this feature can help you

These dimensions provide enhanced insights and granularity into your Azure spending. These Azure-specific dimensions are:

1. Azure Reservation Order Name : This dimension allows you to track and analyze costs associated with different Azure Reservation Order names. It also helps in gaining a deeper understanding of how various reservation orders impact your overall spending and thereby, optimize your reservations accordingly.

2. Part Number : The Part Number dimension provides detailed visibility into costs based on the specific Azure part numbers associated with your resources. By using this dimension, you can better allocate costs and make informed decisions about resource utilization.

3. Reservation Name : With the Reservation Name dimension, you can now analyze and manage costs related to different Azure reservations. It also helps gaining insights into how reservations are utilized across various resources and thereby, take proactive steps to optimize your reservation utilization.

More information about the release

These new dimensions are specific to Azure cost data and will be available exclusively for Azure resources. They are part of our ongoing efforts to provide comprehensive, Azure-focused cost management capabilities.

How this feature can help you

This release introduces a new metric "GPU" in the usage table of the Container Insights page. With this addition, you can easily view the number of GPUs allocated at the cluster, namespace, and label level. The costs allocated to namespace and label values now consider an updated set of weightings accounting for the relative price of GPUs on each node. Since different VMs use varying hardware, the cost of a GPU is therefore tied to each VM family and the specific GPU type utilized by that family.

More information about the release

To provide a better understanding of these changes, let us illustrate a comparison of how costs were previously distributed versus how they are allocated after this update.

Previously, our model considered CPU, Memory, Network, and Disk utilization which proved sufficient for standard VMs. However, on GPU-backed VMs costs can be substantially higher, often two to three times that of similar VMs without GPUs. Without considering the impact of the GPUs and who were using them meant a part of the story was missing. The table below shows how the weightings have been improved for a particular GPU-backed EC2 instance with this launch.

With the updated weightings the GPU has been determined to contribute 50% of the VM cost with memory reduced to 37.5% and CPU to 12.5%. The example below shows how this impacts the cost allocation to three hypothetical workloads that are consuming such a VM.

As evident from the above example, the updated model now reflects the true cost of GPU utilization, resulting in more accurate and fair cost allocation across different workloads. Workloads A and B show an increase in price, reflecting their utilization of the relatively expensive GPU resource. This improvement provides you with greater visibility into your resource costs and enable better cost management.

Previously, Rightsizing recommendations were provided for each individual resource only, even if the machine was generated by and used solely within a single ‘cluster’ such as a GCP Managed Instance Group. With this release, Cloudability Rightsizing provides recommendations for GCP GCE MIGs. Customers can take actions to implement on the group itself, which will then automatically apply to resources created by that group.

How this feature can help you

GCP customers that use MIGs can now automatically see specific recommended actions for savings at the group configuration level as opposed to only at the individual resource level.

The savings of the group will potentially be much larger than each resource within the group. Additionally, resources that are a part of managed instance groups are configured as a group, so providing recommendations at the group level and at the individual virtual machine level is optimal since these groups are configured as a whole entity.

More information about the release

GCE MIG is available under the GCP tab under Rightsizing . GCP MIG data and rightsizing recommendations are automatically displayed if the customer uses GCP MIGs.

This user experience is similar to Apptio’s existing rightsizing functionality for individual GCE resources. The main table shows all groups with spend in the time specified. Groups are sorted by cost savings by default. Customers can start at the top of the list to see the groups with the highest potential savings.

For modern workloads such as machine learning, customers are finding cloud virtual machines with not only CPUs, but also GPUs increasingly useful. With this release, GCP customers that have their data ingested by Apptio via GCP or Datadog will also be able to have their GPU data included to receive enhanced rightsizing recommendations.

How this feature can help you

It will now be possible for GCP customers with compute instances with GPUs to get savings recommendations based on GPU metrics ingested by Apptio, as well as instance type recommendations based on these metrics for instance types with GPUs. These metrics supply a new dimension for the Cloudability recommendations engine to provide additional savings for our customers. Previously, GPU data was not taken into consideration when providing GCP compute rightsizing recommendations.

More information about the release

From the Cloudability primary navigation menu, select Optimize menu item > select Rightsizing , then select the tab for GCP . Prerequisites

1. Each VM must have GPUs attached .
2. Each VM must have a GPU driver installed .
3. Each VM must have Python 3.6 or newer installed.
4. Each VM must have the packages required for creation of Python virtual environments installed.

   N1 machine type support will not be part of this release.

How this feature can help you

Azure Databricks customers optimizing their spend through pre-purchase plans can now view and manage their reservations in the Reservation Portfolio. Cloudability expands the services that Reservation Portfolio supports on the Azure Cloud in response to the growing number of customers who utilize Azure. By incorporating Azure Databricks, Cloudability provides these customers with additional value in terms of realizing the value of purchasing reservations on the Azure Cloud.

More information about this release

Due to the difference in how these reservations are applied to usage, our KPI's and table headers have been adjusted to properly reflect the information around the pre-purchase plan credits, DBCUs. Additionally, we've added a third chat on the details panel to help understand the burn-down on a given commitment.

Note: No support for the Reserved Instance Planner is available at this time.

Earlier, Rightsizing ROI was only available with a Jira Cloud integration. After native Rightsizing ROI functionality was released last year, email notifications for ticket assignees were not available since this mechanism was handled via Jira. A separate native mechanism is being added to notify ticket assignees who are part of the native integration when a ticket is assigned to review and/or process.

How this feature can help you

This functionality allows Cloudability users to attach an email address to native Rightsizing ROI ticket assignees so that those assignees can be notified via email when they get assigned a Rightsizing ROI ticket. Available email addresses will be selected from existing Frontdoor users.

More information about this release

The functionality is available when assigning native ROI tickets. On the Rightsizing ROI page, the user can select the details button of a tracked rightsizing ROI recommendation and then select an assignee with an email address which allows for corresponding email notifications. In addition to this, the functionality is available when the user hovers over the details of the recommendation to be tracked in Rightsizing ROI and selects Create Cloudability Issue .

How this feature can help you

This feature available for each cloud resource unifies billing, utilization, and descriptive meta data and provides a comprehensive inventory view for the first time within Cloudability reporting for non-EC2 resources.

More information about the release

As part of this release, the AWS Resource Inventory feature has to be enabled for a Cloudability organization from the Active Admin console. By default, only Admin or Cloudability Admin roles will be able to access this feature. However, it can also be granted to any custom role by assigning the permission titled AWSResourceInventoryFullAccess to it.

Inventory Report Measures

• Measures refer to dimensions, metrics or tags pulled from the billing data. You can include up to 20 such columns for an individual report.

• Each AWS service support a specific set of dimensions and metrics.

• You are able to filter the inventory reports using any of the measures available within the feature.

• Inventory data is sorted by Cost (Total) in descending order (By default).

Clickable KPIs for Quick Filtering

For each service (eg: EC2, EBS etc.), KPIs are displayed at the top providing you with key summary information like new or idle resources for the current month.

You can view and filter the Inventory reports based on these KPIs for further analysis.

Inventory Reporting Date Windows

Upon enabling this feature, resource inventory data will be back filled to the beginning of the current month. The Inventory data is usually available for three months including the current and earlier two months.

How this feature can help you

Earlier, Filesystem was the combination of ephemeral and persistent storage for various Kubernetes constructs, including Cluster, Namespace, labels, and Services. With these updates, Doing this allows us to provide state-of-the-art cost allocations of one of the most significant cost drivers (EBS) to your EKS clusters.

These enhancements aim to offer a more detailed and holistic view of resource utilization and cost allocation within containerized environments, allowing for better optimization and management of cloud expenses. In this release, we will specifically support EBS (AWS) resources.

As part of these changes, Cloudability introduces an additional dimension called Persistent Volume as a column on the insights page. This new dimension will accurately represent the allocations related to Filesystems.

With these updates, all ephemeral storage will be categorized under the existing Filesystem metric, while Persistent Volume usage will be reflected under the new Persistent Volume metric.

You may also notice cost allocations change around namespaces, services, and labels, especially around workloads that use a very large or a very small amount of Filesystem.

To clarify the distinction in EKS clusters:

How this feature can help you

Customers can view the savings and benefits of the proposed RI purchase, and filter the recommendations based on look back period, region, scope, terms, and accounts. The Reservation Portfolio will provide Cloudability customers with their current reservation portfolio for Azure Cosmos DB instances to go along with the other services we currently provide support for.

Cloudability expands the services that Reservation Portfolio and Reserved Instance Planner support on the Azure Cloud in response to the growing number of customers who utilize Azure. By incorporating Azure Cosmos DB, Cloudability provides these customers with additional value in terms of realizing the value of purchasing reservations on the Azure Cloud. Also, the addition of Azure Cosmos DB support provides customers with actionable insights and recommendations that improve their business outcomes, all from a single pane of glass.

More information about the release

As part of this release, the Planner/Recommendation feature will now be located under the Optimize > Reserved Instance Planner menu item while the Portfolio feature will continue to be located under the Insights > Reservation Portfolio menu Item. For more details, see Generate you recommendations .

How this feature can help you

This capability will enable customers to gain visibility into their container resource usages, and the cost for their clusters running on both those Kubernetes versions.

Customers should now be able to download and deploy our metrics agent using the regular provisioning workflow.

By incorporating ROSA into the Cloudability ecosystem, users can now effectively track and allocate costs associated with their OpenShift clusters, bringing them in line with the capabilities already available for EKS, GKE, and AKS users.

This will allow Cloudability customers leveraging ROSA to access detailed cost allocation information specifically tailored to their OpenShift container resources.

How this feature can help you

With this release, users can easily identify and select their preferred OpenShift cluster version when provisioning resources. This enhancement provides users with greater flexibility and enables them to leverage the specific features and improvements offered by different OpenShift versions.

More information about this release

Follow these steps to view and choose OpenShift cluster versions during the provisioning process:

1. Go to the Cloudability platform and navigate to the Insights section.
2. Select Container and then select Provision Cluster . You will notice that instead of the Kubernetes Version option, there is now a Cluster Version option.
3. Select Cluster Version to proceed.
4. In the drop-down menu that appears, you will not only see the existing Kubernetes versions but also the available OpenShift versions.
5. Choose the desired OpenShift version from the dropdown menu.

Previously, savings plan recommendations were provided only for AWS in Cloudability. Azure savings plans provide an additional option to reduce costs for customers with consistent compute spend by committing to a fixed hourly spend on compute services for one-year or three-year terms.

How this feature can help you

Azure customers can now view their Savings Plan inventory as well as receive purchase recommendations within the Cloudability platform. Customers can view an inventory of their current Azure Savings Plans along with summary KPIs for the total quantity and hourly commit of their Savings Plans. Customers can also view Azure Savings Plan purchase recommendations as well as summary KPI totals for all the recommendations given including the total number of recommended purchases, the total upfront fees, the estimated net savings, and the estimated savings rate.

More information about this release

From the Cloudability primary navigation menu,

• Under Insights , select Savings Plans and then select the Azure tab to access your savings plan portfolio.
• Under Optimize , select Reserved Instance Planner and then select the Azure SP tab to access your savings plan recommendations.

How this feature can help you

This functionality allows Cloudability users to utilize Rightsizing ROI functionality for calculating the realized savings of actioned recommendations when the action is termination of the resource. Once a rightsizing recommendation has been added via Rightsizing ROI and the resource has been terminated, the realized savings from the termination will be calculated and displayed both for the individual resource as well as added to the rolled-up total of all realized savings.

This is in addition to the support already provided for realized savings calculations when a resource is rightsized. Support will be provided for all services currently supported by Rightsizing ROI.

More information about this release

From the Cloudability primary navigation menu,

• Under the Optimize menu, select Rightsizing ROI .
• Whenever the resource was terminated, a Realized Savings amount appears at the bottom of the list of tracked rightsizing recommendations.
• Note: The Realized Savings amount will also be added to the realized savings total displayed at the top of the page.

It’s inevitable that containerized infrastructure runs a certain amount of overhead capacity that is not used by underlying workloads. This “idle” usage has an associated cost (for the backing VMs and volumes) that needs to be accounted for. We have introduced the ability to distribute these idle container costs within Cloudability core analytics (reports and dashboards). While this is a capability that already exists in the dedicated Container Cost Allocation feature, adding it to core analytics can help users streamline chargeback processes and enables more flexible cost reporting. This distribution is done in the context of the Kubernetes constructs namespace and label.

This support is implemented through the introduction of a new metric category “Containers”, which makes available six new metrics. These metrics enable users to view separately the utilized, idle and fairshare costs either with a cash or amortized basis. For customers with custom pricing enabled these will all be represented as “adjusted” metrics.

How this feature can help you

The Container Cost Allocation feature evaluates resource utilization on each node and marries this to the billing data to calculate the cost of each cluster and to associate a direct, “utilized cost”, to K8s namespace and label values (this has been available within core reporting by using the namespace or a label dimension). With this enhancement you can also report on the idle cost via the new metric, which is allocated to the namespace and label values proportionally based on their direct cost contribution of each node. The Fairshare Cost is simply the Utilized Cost and Idle Cost combined - you could think of it as the total cost.

More information about this release

Some considerations and reporting ideas to keep in mind with these new metrics:

• For non-container costs these new metrics will all return as $0. To filter to container only data try a filter such as “Cluster Name not equals (not set)”
• Use these metrics with different dimensions to easily visualize utilized vs idle. For example, list out by Cluster Name or resource ID.
• For the first time you can use cash and amortized cost basis together for detailed container cost reporting.

With this release, the new metrics introduced will reflect cost data from 1st May 2023. To update additional historical data, reach out to your account team or support for the reprocess to be completed.

Previously, Cloudability users ran into page performance issues when they tried to render 500 or more data points in their chart visualizations. Inarguably, 500 or more data points in a single chart do not serve its purpose due to poor readability, the rendering of the same often slowed down the entire Dashboards page for our users.

How this feature can help you

Cloudability will now display a prompt when users try to render 500 or more data points in their charts, which will prevent them from running into page performance issues. At the time of chart creation, users may not be aware that they’re trying to render visualization for a high cardinality measure like Resource ID but a prompt like this would help them flag the potential risks ahead if they decide to proceed with their action. This prompt will be displayed on all the charts where the limit is exceeded and upon each time the Dashboards page is loaded in Cloudability.

More information about this release

The prompt will have two CTAs:

• Edit Query - Allows to go back to edit window and reduce the data points (to below 500).
• Graph Anyway – Users can proceed to render with the chosen number of data points.

Prior to this release, the GPU data was not considered when recommending AWS auto scaling group rightsizing. With this release, AWS customers who utilize auto scaling groups and whose data is ingested by Apptio via Cloudwatch or Datadog will now be able to have their GPU data included to receive enhanced rightsizing recommendations that take this data into account.

How this feature can help you

AWS customers who use auto scaling groups with GPUs will now receive savings recommendations based on GPU metrics ingested by Apptio. In addition to providing additional savings for our customers, these metrics provide a new dimension for our recommendation engine.

More information about this release

1. From the Cloudability primary navigation menu, Select Optimize > Rightsizing

2. Select the AWS tab, and then select AWS ASG .
   Rightsizing recommendations for auto scaling groups with GPUs will automatically be displayed once properly set up and available. The "details" view of the recommendation for auto scaling groups utilizing GPUs will now include additional charts for GPU (%) and GPU memory utilization, just as in the AWS EC2 rightsizing recommendations.

   No additional setup is required for customers who already have AWS Auto Scaling Group rightsizing recommendations and GPU utilization ingestion set up with Cloudability.

• Connecting to AWS & Getting Recommendations Based on GPU Data
• Rightsizing for AWS EC2 ASG

Cloudability now offers recommendations for GCP CUDs using its own custom engine and new analysis interface. With this new interface, customers can perform what-if analysis, and can have more control over the recommendation generated, allowing them to adjust the recommendations based on their future usage, business strategy, and factor in their risk.

How this feature can help you

Firstly, customers can filter their usage for analysis, which allows them to include or exclude usage for a more accurate analysis that represents their future usage. If a workload was running during the analysis period but should not be covered – such as a testing or development workload, then it can be removed from the analysis. Also, if a workload is being decommissioned or you are going to replace a particular type of usage such as an operating system or database software, then you can exclude that usage from the analysis. In this way, your business strategy will be aligned with more accurate recommendations for future usage.

Customers can add up to 10 Cloudability dimensions to their analysis for filtering. These dimensions can be any of the configured Tags & Labels , Account Groups , or Business Mappings .

Secondly, customers can view their selected usage for analysis, and adjust recommendations in real time. This will enable them to view potential outcomes based on different commitment amounts. This helps customers to view the impact of lower commitment levels in case of decreasing usage trend or sustained periods of lower usage.

Steps to credential Azure using the new Cost management APIs:

Steps for a new customer:

1. Go to the Cloudability credentialing page and select Azure .
2. Select EA as the Azure account type.
3. Enter the Azure Enrollment ID and Subscription ID .
4. Enter NA in all other fields.
5. Select Generate Setup Script and install the PowerShell script. This power shell script will have a new role called as Enrollment reader which is used to access the Cost Management API.
6. Once done, verify the credentials on the Cloudability UI.

Steps for existing EA customers with Reporting APIs:

1. If Enrollment reader role access is already available, then enter NA in API Access Key and verify credentials.
2. If Enrollment reader role access is unavailable, then follow the steps as for a new customer.

Steps for existing EA customers with Blob storage:

Nothing needs to be done. In case of billing exports via blob, Cloudability will continue fetching the billing files from there.

Memory/GPU recommendation settings in Rightsizing Preferences

Cloudability users with global settings can turn on/off recommendations that would result in a reduction in capacity of specific components (memory and GPU) even if metrics for these components are unavailable to Cloudability.

For each of these settings, if the setting is enabled, then the customer receives recommendations that could potentially provide extra savings by reducing the capacity of the component but without taking the current metrics of the component into consideration if the metrics are unavailable to Cloudability.

For each of these settings, if the setting is disabled and the metrics of the component are unavailable to Cloudability , then recommendations will be limited to equivalent capacity or greater (with the GPU setting only applying to GPU-based instances and utilizing instance family).

How this feature can help you

These recommendations help customers to save money by reducing the capacity of particular components, even if those recommendations do not consider the current metrics of those components. As an example, a customer’s familiarity with the resource would allow the customer to know that reducing the component’s capacity would not affect the workload.

More information about this release

1. From the Cloudability primary navigation menu, select Settings > Rightsizing Preferences .
2. Under Compute (VM) Preferences , select Capacity Reduction section.
3. Within Capacity Reduction section, see Allow memory-reducing recommendations without memory utilization metrics and Allow GPU-reducing recommendations without GPU utilization metrics . These options are unchecked by default.