In a cloud-native environment, managing resources efficiently is crucial for organizations to optimize their infrastructure, reduce costs, and avoid operational disruptions. Kubernetes, as one of the most widely used container orchestration platforms, is no exception. However, as Kubernetes clusters grow and evolve, they often accumulate unused or orphaned resources. These resources, if left unchecked, can lead to increased costs, operational inefficiencies, and even security vulnerabilities.

Sedai offers intelligent solutions that provide visibility and actionable insights into managing orphaned and unused resources within Kubernetes environments. By leveraging Sedai's tools, organizations can ensure more effective resource optimization and avoid the risks associated with unmanaged infrastructure.

Understanding Unused and Orphaned Resources

Source: Clean Up Unused and Orphaned Persistent Disks 

Managing resources in Kubernetes can be complex, especially when dealing with unused or orphaned resources. Both terms refer to resources that are no longer performing their intended functions, but there are key differences between the two.

Sedai provides advanced monitoring tools that automatically detect unused and orphaned resources, helping organizations reduce unnecessary costs and improve resource allocation within their Kubernetes clusters.

What Are Orphaned Resources in Kubernetes?

Orphaned resources in Kubernetes refer to resources that no longer have any associated parent or controlling entities but still exist within the cluster. These resources might be created as part of a larger process, such as deploying an application or a service, but later become disconnected from the original controller, application, or namespace. Without proper management, orphaned resources can accumulate over time, leading to inefficiencies and wasted compute power.

In Kubernetes, orphaned resources often include:

• Unused Persistent Volumes (PVs) or Claims (PVCs): These volumes may not be linked to any pods or applications, but they still consume storage resources.
• Orphaned Pods: Pods that are no longer associated with any deployments or services but remain running in the cluster.
• Service Endpoints: Services that no longer have active connections but continue to occupy network resources.

By identifying and addressing orphaned resources, organizations can reclaim valuable resources and reduce the potential for performance issues.

Unused vs Orphaned Resources in Kubernetes

The difference between unused and orphaned resources in Kubernetes lies primarily in their relationship to active applications or services:

• Unused Resources: These are resources that are no longer actively needed but haven’t been deleted. They could be volumes, services, or other resources that once served a function but are no longer required.
• Orphaned Resources: Orphaned resources, as discussed, are resources that have lost their parent associations, meaning they are isolated from their original controllers and applications. While unused resources might still be connected to some aspect of the cluster, orphaned resources are completely disconnected.

Both types of resources can lead to inefficiencies, but orphaned resources tend to be more problematic since they have lost their context and might require manual intervention to clean up.

Examples of Unused Resources in Kubernetes

In Kubernetes, some of the most common examples of unused resources include:

• Unused Persistent Volumes (PVs): These are volumes that were once mounted to pods but no longer serve any active purpose in the cluster.
• Dangling Services: These are services that are no longer connected to any active pods or workloads but still exist in the cluster.
• Stale ConfigMaps or Secrets: Configuration data or secrets that are no longer referenced by any pods or applications.
• Old Deployments or ReplicaSets: Deployments that are no longer relevant but haven't been deleted, leaving behind unneeded replicas or configurations.

By identifying unused resources, organizations can avoid unnecessary resource consumption and reduce their operational costs. Sedai’s autonomous cloud platform can track and highlight unused resources, providing alerts for timely action.

Sedai's platform helps automate the identification, cleanup, and management of unused and orphaned resources, making it easier for organizations to maintain efficient Kubernetes environments. By leveraging Sedai's AI-driven insights, teams can significantly reduce manual intervention and ensure that their clusters are always optimized for performance and cost efficiency.

Impact of Unused and Orphaned Resources

As Kubernetes clusters scale, unused and orphaned resources can accumulate, causing several issues that impact performance, security, and costs. Understanding the impact of these resources is crucial for maintaining efficient and secure Kubernetes environments. Sedai plays a key role in helping organizations proactively identify, optimize, and manage these resources to achieve better operational outcomes.

Orphaned resources in Kubernetes, such as unassigned pods, persistent volume claims, or network interfaces, can have a significant negative impact on the performance of your cluster. These resources continue to consume computational power, memory, and network bandwidth, leading to congestion and slowdowns in the cluster’s performance. As orphaned resources grow in number, they can result in slower pod scheduling, resource contention, and inefficient workload balancing.

Sedai offers a comprehensive set of tools that can automatically identify unused and orphaned resources, providing detailed recommendations for improvements in cost, performance, and security. Through intelligent monitoring and automated optimization, Sedai ensures that Kubernetes clusters are always operating at peak efficiency.

Cost of Unused Kubernetes Resources

Unused resources in Kubernetes, such as persistent volumes, services, and config maps, continue to consume cloud infrastructure costs even when they do not serve any functional purpose. Persistent volumes that are no longer linked to any pods, for example, can incur storage charges without providing any value. Similarly, unused services, networks, and other resources that are left running unnecessarily add to operational costs.

The impact on costs can be particularly significant in cloud environments like AWS, where resources are billed based on usage. Sedai’s optimization tools help you identify and eliminate unused resources, reduce unnecessary expenditures, and ensure that your cloud infrastructure is being used effectively. 

Kubernetes Performance Issues with Orphaned Resources

Source: Kubernetes performance issues and how to handle them 

Orphaned Kubernetes ConfigMaps and Secrets Create Security Risks

Source: Kubernetes 101: Secret and ConfigMap 

ConfigMaps and Secrets are crucial for storing configuration data and sensitive information in Kubernetes. However, orphaned or unused ConfigMaps and Secrets can introduce security risks. These resources, if left unmanaged, may contain outdated or sensitive information that is no longer in use but could still be accessed by unauthorized users or processes. Additionally, orphaned resources that are not cleaned up may result in security vulnerabilities, such as exposed secrets or inconsistent configuration states that could lead to misconfigurations.

Mismanagement of ConfigMaps and Secrets could lead to a potential breach of sensitive data or make your Kubernetes environment vulnerable to attacks. It is vital to regularly audit and remove unused or orphaned ConfigMaps and Secrets to prevent these risks.

Sedai’s autonomous platform provides continuous monitoring of Kubernetes clusters, identifying unused or orphaned ConfigMaps and Secrets that may pose a security threat. By detecting and alerting you to potential security issues, Sedai helps organizations maintain the security and integrity of their Kubernetes environments. Additionally, Sedai’s optimization tools can identify resources that are misconfigured or unnecessarily exposed, reducing the likelihood of security breaches and ensuring that sensitive data remains protected.

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Through Sedai's innovative platform, you can effectively mitigate the impact of unused and orphaned resources on cost, performance, and security. By automatically identifying these resources and offering actionable insights, Sedai empowers organizations to streamline operations, optimize cloud infrastructure, and maintain secure Kubernetes environments.

Techniques for Detecting Orphaned Resources

Effective detection of orphaned resources in Kubernetes clusters is crucial for maintaining an optimized, cost-efficient, and secure environment. There are several techniques to identify orphaned resources, including utilizing Kubernetes CLI commands, kubectl, and more advanced methods tailored to specific resource types such as ConfigMaps and Secrets. Sedai further enhances these efforts by automating resource detection and providing AI-driven optimization opportunities for better efficiency.

Kubernetes CLI Commands for Resource Detection

Kubernetes provides a variety of CLI commands that allow you to detect orphaned resources within your clusters. These commands offer a direct and hands-on approach to searching for unused or unassigned resources. Some useful commands include:

Identify all resources in a namespace: To list all the resources within a specific namespace, you can use the kubectl get command:

• This will show you all pods, services, deployments, replica sets, etc., within the given namespace. You can then manually inspect whether any of these resources are orphaned (not connected to any workloads or serving any functional purpose).

Check for orphaned persistent volumes: Orphaned persistent volumes (PVs) that are not bound to any persistent volume claims (PVCs) are a common problem. To find unbound PVs, you can run:

• This lists PVs that are not bound to any pods, which are often orphaned resources that need to be cleaned up.

Identifying orphaned services: To detect services that are no longer associated with any active workloads (like pods or deployments), you can use:

• From the output, look for services that are not linked to any active endpoints, indicating they might be orphaned.

By using these Kubernetes CLI commands, you can manually track down orphaned resources and remove them, reducing clutter and minimizing the cost of unused resources.

However, manual detection can be time-consuming and error-prone, especially in large clusters. This is where Sedai can provide added value, autonomously detecting unused and orphaned resources, generating insights, and offering recommendations for optimization at both the workload and container levels.

How to Identify Orphaned Resources with kubectl

Using kubectl, you can directly identify orphaned resources through a combination of specific commands and labels. Here are some steps you can take to identify orphaned resources effectively:

Finding orphaned Persistent Volume Claims (PVCs): To detect orphaned PVCs, which are not bound to any active pods, use the following:

1. If a PVC does not have a corresponding pod, it is likely orphaned. Orphaned PVCs may still incur storage costs, so it's crucial to clean them up.

Checking orphaned Deployments and ReplicaSets: To find deployments or ReplicaSets that no longer have associated pods, you can list all deployments and check for the status of their pods:

2. If any deployment or ReplicaSet has no active pods, it's an indicator of an orphaned resource.

Analyzing Services and Endpoints: Services that don’t have any endpoints associated with them might be orphaned:

Cross-check the services with the endpoints:

3. If a service has no corresponding endpoints, it could be considered orphaned.

Unused Network Resources: For resources like unused network interfaces, security groups, or route tables, you can use commands to list network resources across the cluster:

Identifying orphaned resources using kubectl is an effective way to manually audit and clean up Kubernetes clusters, but it can be labor-intensive when scaling across large or multiple clusters. Sedai simplifies this process by automating resource detection and identifying optimization opportunities for cost, performance, and security.

Detecting Unused ConfigMaps and Secrets in Kubernetes

ConfigMaps and Secrets are used to store configuration data and sensitive information within Kubernetes clusters. However, if these resources are orphaned or no longer in use, they can pose security risks or cause unnecessary storage costs. Detecting unused ConfigMaps and Secrets is essential for maintaining security and reducing cluster clutter.

Here’s how you can detect unused ConfigMaps and Secrets manually:

Listing ConfigMaps and Secrets: To list all ConfigMaps and Secrets in a specific namespace, use the following commands:

1. This gives you an overview of all ConfigMaps and Secrets across your clusters. You can then cross-check whether these resources are still being used by active pods or workloads.
2. Inspecting Resource Usage: After listing the ConfigMaps and Secrets, you can inspect whether they are still being referenced by pods or deployments. For instance, if a ConfigMap is no longer being mounted as a volume or referenced by a deployment, it may be an orphaned resource.

Cleaning Up Unused ConfigMaps and Secrets: Once you identify unused or orphaned ConfigMaps and Secrets, you can delete them to reduce the security risk of exposing sensitive data or consuming unnecessary storage:

Sedai further streamlines the process by continuously monitoring ConfigMaps and Secrets, detecting unused resources, and providing automatic recommendations for their removal. This helps reduce security risks and ensures that only necessary configuration data and secrets remain in your clusters.

By integrating Sedai’s resource detection and optimization capabilities, you can ensure that your Kubernetes clusters are not only cost-efficient but also secure, freeing up resources for more critical workloads. Sedai also provides recommendations for improving resource usage at both the container and workload levels, ensuring that your Kubernetes environment is always performing at its best.

Tools and Best Practices for Cleanup

Cleaning up unused and orphaned resources are crucial for maintaining the health, security, and cost-effectiveness of Kubernetes clusters. Various tools and best practices can assist in identifying and cleaning up unnecessary resources while improving resource utilization and ensuring a streamlined environment. Sedai can also automate many of these processes, ensuring that Kubernetes clusters are optimized for both performance and cost.

Kubernetes Resource Cleanup Tools

There are several Kubernetes resource cleanup tools available to help administrators easily manage and remove orphaned or unused resources. These tools can automate the cleanup process and make it easier to maintain cluster efficiency. Some of the most widely used cleanup tools include:

kubectl delete: Kubernetes’ native CLI tool, kubectl, provides basic resource cleanup capabilities. You can use kubectl delete to remove unwanted resources manually:

For example, to delete an unused deployment or a pod, simply use:

1. Kube-bench: Kube-bench is a tool used for auditing and verifying the security of your Kubernetes clusters based on best practices. While it's not strictly a cleanup tool, it helps identify configuration issues that could lead to unnecessary or unused resources, which can then be cleaned up manually.
2. K8s Garbage Collection: Kubernetes has an internal garbage collection system that automatically cleans up certain orphaned resources, such as terminated pods, unused volumes, and stale containers. However, this garbage collection is not always comprehensive, especially for resources like ConfigMaps, Secrets, and network configurations. It's essential to monitor and manually intervene when necessary.
3. Helm Cleanup: For Kubernetes users who rely on Helm for managing applications, Helm provides a helm uninstall command to cleanly remove charts and the resources associated with them. This helps prevent orphaned resources left behind by failed or outdated Helm releases.

Sedai integrates these manual cleanup tools by automating the identification and removal of unused resources, ensuring continuous optimization. The platform can offer detailed insights and recommendations, helping administrators keep Kubernetes clusters clean without manual intervention.

Prometheus for Monitoring Kubernetes Resources

Source: A Hands-On Guide to Kubernetes Monitoring Using Prometheus & Grafana 

Prometheus is one of the most popular open-source monitoring tools for Kubernetes. It collects and stores time-series data, providing real-time insights into the health and performance of clusters and their components. By using Prometheus to monitor Kubernetes resources, you can easily identify unused or underutilized resources and take proactive steps to clean them up.

1. Collect Metrics: Prometheus collects metrics about your Kubernetes cluster's components, such as pods, deployments, nodes, and services. By setting up the right metrics and alerts, you can track resource usage over time and identify orphaned or underutilized resources that need cleanup.
2. Set Alerts: Prometheus allows you to set custom alerts based on resource usage thresholds. For example, you can set an alert for when a persistent volume is not bound to a pod or when a pod is using significantly more CPU or memory than expected. These alerts can help you identify orphaned or unused resources early on, allowing for timely cleanup.
3. Query with PromQL: Prometheus uses PromQL (Prometheus Query Language) to query and filter metrics. Using PromQL, you can write complex queries to identify specific resource usage patterns, such as unused services, pods, or persistent volumes. By using Prometheus effectively, you can automate monitoring and resource management, reducing the risk of orphaned resources.

Sedai integrates with Prometheus and other monitoring tools, providing even deeper insights into cluster performance and resource usage. Sedai's detection and optimization features can proactively recommend actions based on Prometheus metrics, streamlining the cleanup process.

K8s-cleaner and Kor Tool for Kubernetes

Source: Kor - Kubernetes Orphaned Resources Finder 

In addition to native cleanup tools, there are several third-party solutions designed specifically for managing and cleaning up unused Kubernetes resources.

1. K8s-cleaner: K8s-cleaner is an open-source tool designed to help Kubernetes administrators clean up orphaned resources in their clusters. It automatically scans the cluster for unused resources, such as old deployments, replica sets, services, and more, and offers suggestions for deletion. It can be run as a scheduled job or manually, and it supports integrations with other tools like Helm and Prometheus.
   Key features of K8s-cleaner:
   
   • Identifies orphaned resources across multiple namespaces
   • Provides detailed reports of unused resources
   • Allows for selective cleanup based on resource type
   • Can be run periodically to ensure continuous cleanup
2. Kor Tool: Kor is another open-source tool that focuses on cleaning up Kubernetes resources. It provides an automated cleanup process for resources that are no longer needed. Kor supports multiple resource types and can clean up orphaned pods, deployments, persistent volumes, and other resources that are not actively used in the cluster.
   Key features of Kor:
   
   • Automates the cleanup of orphaned resources
   • Compatible with various cloud providers and Kubernetes configurations
   • Reduces operational overhead by automating resource management
   • Helps maintain a lean, efficient Kubernetes cluster

Both K8s-cleaner and Kor are effective for managing and cleaning up unused Kubernetes resources. However, manual intervention may still be required for some complex cleanup tasks. Sedai elevates these tools by providing an all-in-one solution that autonomously optimizes resources, recommends targeted cleanup actions, and tracks resource usage across the entire cluster.

By integrating Sedai with tools like K8s-cleaner and Kor, Kubernetes administrators can ensure that their clusters remain optimized and free from orphaned or unused resources. Sedai's automation capabilities enable continuous optimization and resource cleanup, allowing you to focus on more important aspects of cluster management and workload performance.

Using Automation and Notifications

Automating the detection and cleanup of unused and orphaned resources in Kubernetes is essential to maintaining cluster efficiency and reducing manual oversight. By implementing automated alerts and notifications, you can proactively manage resources and ensure that unused components do not accumulate. 

Kubernetes Alerting and Notifications for Unused Resources

Source: Best practices for alerting on Kubernetes 

One of the best ways to prevent unused resources from accumulating in Kubernetes is by setting up alerting mechanisms that notify you when resources are underutilized or orphaned. These alerts can be triggered based on specific thresholds or patterns, such as resource usage, workload status, or a lack of activity for a defined period.

1. Set Resource Usage Thresholds: Create alerts that notify you when resources such as CPU, memory, or storage reach a certain usage threshold. For example, if a pod or container is not using the CPU or memory it has been allocated, it might be a sign that resources are underutilized and could be optimized or removed.
2. Monitor Resource Lifecycle Events: Set up alerts that notify you when Kubernetes resources, such as pods, services, or volumes, are deleted or no longer in use. Monitoring lifecycle events ensures that orphaned resources can be identified quickly and cleaned up before they lead to operational inefficiencies.
3. Track Resource Idle Time: Resources that are idle for extended periods can become orphaned and unnecessary. You can automate alerts to trigger when a resource has not been accessed or used within a specified timeframe, allowing you to identify potential orphaned resources that may require cleanup.
4. Integrate with Kubernetes Metrics Server: The Kubernetes Metrics Server can help track resource utilization, and setting alerts for low usage levels will help identify unused resources. Combining this with Sedai can give you deeper insights into resource inefficiencies and suggest optimizations that could further reduce costs and improve performance.

Sedai’s autonomous platform makes this process easier by providing advanced resource optimization and alerts for Kubernetes workloads and containers. With Sedai, you can get more than just alerts—you receive actionable recommendations that optimize resource allocation, reduce costs, and improve overall cluster efficiency.

Alertmanager and Slack Integration for K8s

Source: Install Prometheus with Helm, Monitor Your Kubernetes Cluster, and Send Alerts to Slack 

Effective alerting and notification systems are key to keeping track of unused resources and ensuring timely actions are taken to resolve them. Alertmanager and its integration with tools like Slack can streamline this process by automatically notifying your team of resource issues or potential optimizations in real-time.

1. Setting Up Alertmanager for Kubernetes: Alertmanager is the tool that manages alerts sent by the Prometheus monitoring system, which is commonly used in Kubernetes clusters. It can handle alerts for a variety of issues, including unused resources, performance bottlenecks, and potential security risks. By setting up Alertmanager to trigger alerts when resources exceed defined thresholds or when orphaned resources are detected, you can ensure that your Kubernetes cluster is continuously monitored for inefficiencies.
2. Custom Alerts for Orphaned Resources: Configure custom alert rules within Alertmanager to specifically target unused resources, such as idle volumes, unused ConfigMaps, or unnecessary pods. For example, you can set up an alert that triggers when a persistent volume has not been attached to a pod for a certain amount of time, signaling that the volume is orphaned and can be safely deleted.
3. Real-Time Notifications via Slack: Integrating Alertmanager with Slack ensures that your team receives real-time notifications for critical alerts. By creating a dedicated Slack channel for Kubernetes monitoring, your team can receive instant notifications about unused resources or performance issues, allowing them to take immediate action. Slack integrations also support rich notifications, including links to relevant dashboards, logs, or detailed alert data, making it easier for teams to respond quickly.
4. Automation of Cleanup Actions via Slack: With advanced automation and proper configuration, Slack can be integrated with Kubernetes cleanup tools (like Sedai) to trigger resource optimization actions directly from the Slack interface. This allows your team to make decisions and apply optimizations without leaving the communication platform. For example, an alert triggered in Slack about an unused service can be followed by a direct command to Sedai, which will initiate cleanup processes, ensuring that resources are efficiently managed.
5. Alert Escalation and Collaboration: When alerts for unused resources are raised, it’s critical to have an escalation process to ensure that the right people are notified. Slack’s integration with Alertmanager allows for alert escalation workflows, ensuring that if a resource cleanup task isn't acted upon, a higher-priority notification is sent. This helps prevent issues from being ignored and promotes collaborative efforts to resolve them in a timely manner.

By combining Sedai with Kubernetes alerting and notification tools like Alertmanager and Slack, your team can proactively address unused resources, optimize costs, and enhance performance with minimal manual intervention. Automated alerts and Slack notifications keep everyone on the same page and ensure that actions are taken as soon as potential issues arise.

Example Scripts and Use Cases for Kubernetes Cleanup

Scripts to Identify Unbound Persistent Volumes in Kubernetes

In Kubernetes, unbound Persistent Volumes (PVs) refer to volumes that are not currently bound to any Persistent Volume Claim (PVC). These unbound volumes can accumulate over time if not properly managed, consuming storage resources. Below is a basic script to identify unbound PVs using kubectl.

This script checks the state of all Persistent Volumes and filters out those in the "Released" state (indicating they are unbound). Once identified, you can manually delete them or automate cleanup processes.

Custom Kubernetes Cleanup Scripts for Clusters

You can automate cleanup of unused resources, such as pods, services, and PVs, with a custom cleanup script. This script can be tailored to target specific resource types or namespaces:

This script deletes resources in the "default" namespace that are no longer in use, such as pods, services, and Persistent Volumes. Customize it to include other resources or namespaces based on your cluster needs.

Real-World Examples of Kubernetes Resource Management

Kubernetes has transformed how large-scale companies manage their infrastructure. Below are a few real-world use cases:

1. Tinder's Move to Kubernetes
   Tinder faced significant scalability challenges due to the high volume of traffic. By migrating 200 services to Kubernetes, they successfully scaled their infrastructure, managing a Kubernetes cluster with 1,000 nodes, 15,000 pods, and 48,000 containers. Kubernetes enabled Tinder to run services at scale while maintaining stability.
2. Reddit’s Kubernetes Story
   Reddit transitioned to Kubernetes to overcome the limitations of traditional provisioning and configuration methods. With Kubernetes, Reddit enhanced its infrastructure to support high-traffic operations and allowed for improved scalability and performance.
3. The New York Times’s Journey to Kubernetes
   The New York Times migrated most of its customer-facing applications to Kubernetes, which drastically reduced deployment times from 45 minutes to just a few. Developers gained more autonomy and productivity, leading to faster deployments and fewer bottlenecks.
4. Airbnb’s Kubernetes Story
   Airbnb transitioned to a microservices architecture supported by Kubernetes, enabling over 1,000 engineers to deploy more than 250 services at scale. Kubernetes facilitated continuous delivery for Airbnb, supporting over 500 deployments per day.
5. Pinterest’s Kubernetes Story
   Pinterest faced scalability challenges due to growing traffic, so they moved their services to Docker containers and then to Kubernetes. Kubernetes allowed Pinterest to scale its infrastructure effectively, reduce overhead costs, and improve deployment times from days to minutes.
6. Pokémon Go’s Kubernetes Story
   Pokémon Go, developed by Niantic, saw exponential growth in users. Kubernetes helped scale their infrastructure to handle millions of users by orchestrating their containerized services. This enabled Pokémon Go to focus on game features while Kubernetes took care of the scaling challenges.

These companies have leveraged Kubernetes to optimize resource management, achieve high availability, and scale their services. The use of Kubernetes helped them solve major operational challenges and maintain performance at scale.

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Final Thoughts: The Future of Kubernetes Resource Management

Efficiently managing unused and orphaned resources in Kubernetes is crucial for maintaining cost-effectiveness, performance, and security across your clusters. By identifying orphaned resources, implementing cleanup strategies, and following best practices, you can optimize your Kubernetes infrastructure and avoid unnecessary overhead. Utilizing the right tools and automation can significantly improve the scalability and reliability of your applications, just as seen in the success stories of companies like Tinder, Reddit, and Pinterest.

To ensure continuous optimization of your Kubernetes clusters, leveraging solutions like Sedai can provide you with advanced, autonomous optimization capabilities. Sedai not only helps detect unused resources but also provides ongoing insights to optimize workloads, configurations, and node pools for peak efficiency. With its ability to optimize at both the workload and container levels, Sedai ensures that your Kubernetes infrastructure is running cost-effectively while maintaining high performance and availability.

Book a demo now to see how Sedai can help you optimize your Kubernetes clusters and achieve your performance, cost, and availability goals.

 Frequently Asked Questions (FAQs)

1. What is Sedai's approach to optimizing Kubernetes clusters? 

Sedai autonomously analyzes Kubernetes clusters to identify optimization opportunities at both the workload and container levels. By examining resource utilization, traffic patterns, and node configurations, Sedai provides tailored recommendations to reduce costs, improve resource efficiency, and enhance performance, ensuring your clusters meet your optimization goals.

2. How does Sedai help in detecting orphaned resources in Kubernetes? 

Sedai offers a comprehensive cost optimization solution for detecting unused and orphaned resources in Kubernetes by analyzing metrics and identifying workloads or resources that are no longer needed. The system flags orphaned resources such as unbound Persistent Volumes, unused ConfigMaps, and Secrets, allowing you to optimize your infrastructure and eliminate waste.

3. Can Sedai optimize Kubernetes clusters in different cloud environments? 

Yes, Sedai supports Kubernetes clusters across multiple cloud platforms, including AWS (with ECS or Fargate), Google Cloud, and Azure. It adjusts optimization strategies according to the specific cloud environment, ensuring that you achieve the most cost-effective and performance-optimized configurations for your workloads.

4. How does Sedai help with resource management and workload optimization? 

Sedai builds an internal model of application behavior based on available metrics, allowing it to fine-tune resource configurations for each workload. By adjusting vertical and horizontal sizing, including CPU and memory requests and limits, Sedai ensures optimal performance while minimizing overprovisioning and underutilization.

5. How can I get started with Sedai for Kubernetes optimization? 

To get started with Sedai, simply book a consultation to explore how its autonomous optimization capabilities can benefit your Kubernetes clusters. Sedai's platform will analyze your infrastructure and provide actionable insights tailored to your specific needs, helping you save costs and improve scalability and reliability.