CAST AI
Cut your cloud bill in half
We have released an updated version of the Terraform provider (v0.8.1), it now supports EKS clusters. Release and example projects can be found on GitHub.
In our UI menu “Policies” page is now called “Autoscaler”. We have started the work on improving the experience of setting up and controlling the autoscaler, more changes will come.
Implemented the following Node list improvements:
The list is sorted in descending order by date and there is now a possibility to sort the list on most of the columns.
Ability to view labels attached to each node.
Spot fall-back nodes are now identified with an icon.
Improved error handling in Rebalancer, providing screens with more details about the encountered error and possible remediation.
New version of CAST AI agent v.0.22.5 is now available. To update the agent in your cluster follow these steps.
Fixed a bug in GCP custom spot instances pricing.
Fixed a bug in the Available savings report where sometimes workloads that are already running on spot instances would be suggested to be run on on-demand nodes.
Added records of spot fallback events to the audit log.
Evictor now has a setting to run in more “aggressive” mode, where it would also evict pods with a single replica. Check the documentation for more details.
Improved performance of our console UI and fixed various small bugs.
All release notes - https://cast.ai/release-notes/
Have you ever experienced Spot instance drought, when instances you need are temporarily not available and so your workloads become unschedulable? The Spot fallback feature guarantees capacity by temporarily moving impacted workloads onto on-demand nodes. After a period of time, CAST AI will check for Spot availability and move the workloads back to spot instances. This feature is available on the Policies page under the Spot instance section and supports EKS, Kops, and GKE clusters.
Added support for private kOps clusters that do not have K8s API IP exposed to the internet. CAST AI agent now supports "call-home mechanism" for private IP K8s clusters.
Node list went through a major upgrade and now contains much more detailed information about individual nodes in the cluster.
Autoscaler can now be instructed to scale the cluster with instances that have locally attached SSD disks, when the storage-optimized label is used in a workload spec. For details, please refer to the documentation.
Minor improvements to UI and bug fixes.
We have launched a new feature that we call Rebalancer. It allows users to automatically migrate clusters from the current state to the most optimal configuration. The migration is performed via three distinct phases: 1) during the preparation, the user can inspect all impacted workloads; 2) later the user gets a migration plan so they understand what nodes will be added & removed and what cost impact can be expected; 3) lastly - the migration plan is executed by adding new nodes, migrating workloads and deleting obsolete nodes.
The Available savings report is now enhanced with a graph that displays point in time actual and optimal cluster costs as well as other dimensions (i.e. CPU, Memory, node count).
For kOps clusters, we no longer consider master nodes in our available savings report recommendations.
Added support for kOps version 1.20.
For AWS/kOps clusters we previously deployed a Lambda function per cluster, its no longer the case. From now on a single Lambda function is deployed per account.
Implemented the handling of cases when customer has removed some permissions (or the cluster itself) in their cloud provider account. In such a scenario, the cluster would be displayed with status “Failed” in our console and user would have two options: remove the cluster from the console or fix the error in their cloud provider’s account.
Fixed various reported bugs and implemented other UI improvements.
GKE cluster optimization. Customers running unshielded GKE clusters can now onboard them into CAST AI and benefit from all cost optimization policies.
Cluster metrics endpoint – we have released the first version of the metrics endpoint that provides visibility into the CAST AI-captured metrics. The initial description of metrics and setup guide can be found in Github. We will continue expanding the list of exposed metrics, so stay tuned.
Implemented Node Root Volume Policy policy that allows the configuration of root volume size based on the CPU count. This way nodes with a high CPU count can have a larger root disk allocated upon node creation.
We have enhanced the Spot policy for EKS and kOps, so customers can instruct CAST AI to provision the least interrupted spot instances, most cost-effective ones, or simply leave the default – balanced approach. We also support an ability to override this cluster-wide policy on the deployment level.
CAST AI agent v.0.20.0 was released – the agent now supports auto-discovery of GKE clusters, users are no longer required to enter any cluster details manually.
Cluster headroom and Node constraints policies are now separated and can be used simultaneously.
We made it easier for users to set correct node CPU and Memory constraints that adhere to supported ratios.
Bug fixes and small interface improvements.
Implemented a new feature that allows users to set the time for how long an empty node should be kept alive before deletion. This “empty node time-to-live” setting makes node deletion policy less aggressive in case users do not want to delete empty nodes right away. Read more about this feature in our docs.
Our Savings Estimator as well Autoscaler are now able to target higher variety of instance types when recommending SPOT instances. This improvement allows customers to unlock more savings from the use of instance families that previously would not be considered.
CAST AI now supports Organizations! Multiple team members from a company can now join CAST AI, create organization inside our console and collaboratively manage K8s clusters.
GCP customers can connect GKE clusters to CAST AI and see how much they could save by using CAST AI optimization engine. As always this is completely free and safe as our agent operates in read only mode. Try it out now. Functionality to optimize GKE cluster using CAST AI is currently in development.
Users running kOps clusters on AWS can now fully benefit from CAST AI cost analysis and optimization functionality. Connect your kOps cluster now, to see how much you can save and realize those savings by turning on AI driven optimization policies.
Connected AWS (EKS and kOps) clusters can now be paused and resumed as easily as CAST AI created clusters. Functionality to pause and resume on pre-set schedule is coming soon as well.
Node list is now accessible as soon as cluster is connected, customers no longer need to onboard cluster to access this functionality.
Additional Control plane nodes can now be added to CAST AI created clusters.
Clusters that were onboarded to CAST AI can now be disconnected via UI, customers have an option to delete or leave CAST AI created nodes.
We have reacted to user feedback and made minor adjustments in UI as well as fixed bugs.
We have released the Add-ons management functionality for CAST AI clusters. Now CAST AI clusters will be created faster without any add-ons pre-installed. Afterward, users will be able to choose the add-ons they wish to use. The Add-ons feature is available in the cluster dashboard, try it out!
We increased the frequency of communication between the agent deployed on the client’s cluster and CAST AI and reduced the amount of data the agent sends via the network. Now CAST AI can react in as little as 15 seconds and scale the cluster as required.
We have applied minor improvements and fixes to increase the accuracy of our Available savings report.
Improved experience for selecting and managing your subscription.
Created a guide on how to disconnect your EKS cluster from CAST AI.
Last but not least, we fixed some bugs and made small improvements to the UI.
We have made cost optimization policies available to EKS clusters created outside of CAST AI! On top of the previously released “Connect your cluster” functionality, users can now onboard EKS credentials and start using CAST AI policies to reduce their cloud bills.
Created a guide on how to migrate out of EKS nodes into CAST AI selected nodes in AWS.
We have also uplifted the design of the Available Savings report, so users can better understand CAST AI recommendations and the next steps required to achieve an optimal cluster configuration.
Streamlined the workflow by reducing the number of actions required to onboard an EKS cluster and access the Available Savings report
Created a guide for the installation and configuration of VPA for pod rightsizing.
As always, we hunted down and fixed various bugs.
Launched an agent to connect the EKS cluster (that was not created by CAST AI) to our console. Users can now connect clusters in read-only mode and use the “Savings” feature to analyze proposed optimizations and their impact on the cloud bill.
Revamped dashboard UI.
Node interruptions made visible in the logs data via Audit log UI.
Canada East (Montréal) is now a supported region in our cluster creation flow.
Fixed minor bugs.
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