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How to Secure Your Kubernetes Cluster

  • By Gcore
  • May 10, 2024
  • 8 min read
How to Secure Your Kubernetes Cluster

As Kubernetes continues to dominate as the go-to for producing containerized applications, securing these clusters becomes vital. This article discusses the complexities of Kubernetes security, highlighting common vulnerabilities and strategic defenses. We explore strategies to protect your Kubernetes environment, from understanding the four C’s of security—Cloud, Clusters, Containers, and Code—to learning the management of Kubernetes secrets. Learn how to strengthen your cluster and why these measures are crucial for resilient infrastructure.

What Is the Security Strategy of Kubernetes

To secure the integrity and confidentiality of data within the cluster, Kubernetes security takes a structured approach that focuses on Authentication, Authorization, and Admission Control. Below, we will look at these basic components of Kubernetes security and demonstrate the appropriate configurations and instructions to improve security measures.

#1 Authentication

Authentication is the initial stage in the security chain, guaranteeing that only legitimate users may access the Kubernetes API. Kubernetes supports a variety of authentication mechanisms:

  • Static Passwords and Tokens. This method relies on passwords and tokens that are predefined in the Kubernetes API server’s initial configuration. These credentials are often configured when the cluster is created, providing a basic level of access control. This strategy is commonly used for first installs or in contexts with reduced complexity and security requirements.
  • Service Account Tokens. Kubernetes manages customized tokens that are automatically assigned to pods. They are generally used to provide programmatic access to the Kubernetes API from within the pod. Service account tokens enable secure service-to-service communication within the cluster, ensuring that applications have the necessary permissions to run properly even without human interaction.
  • Client Certificates. For a more secure method of authentication, Kubernetes supports the use of X509 certificates. This approach uses public key infrastructure (PKI) to verify the identity of users and systems. Client certificates must be signed by a trusted certificate authority (CA) that the Kubernetes API server recognizes. This method is highly secure and commonly used in production environments to ensure secure connections and data integrity.
  • Static Files. Kubernetes can authenticate users based on credentials stored in static files. This method is similar to using static passwords and tokens, but it allows for the storage of multiple user credentials in a file, which the API server reads at startup. It provides a simple and direct way to manage access for a fixed list of users and is often used in smaller or less dynamic environments.
  • External Authentication Providers. To enhance flexibility and integrate with existing enterprise systems, Kubernetes can delegate authentication to external authentication providers. This includes systems such as LDAP (Lightweight Directory Access Protocol), SAML (Security Assertion Markup Language), and OAuth2. Integration with these external systems allows Kubernetes to leverage robust, enterprise-grade user management and authentication infrastructures, providing centralized control over access and enabling features like multi-factor authentication and single sign-on (SSO).

Authentication Flowchart

Example commands for managing authentication include:

# Create a CSR for a new user with client certificate authenticationopenssl req -new -key user-key.pem -out user.csr -subj "/CN=user/O=group"
# View authorized tokenskubectl get secrets

#2 Authorization

Once authenticated, Kubernetes uses authorization to determine which actions an authenticated user can take. Kubernetes offers multiple types of authorization:

  • Role-Based Access Control (RBAC). This approach of access management grants permissions depending on roles within the Kubernetes environment. RBAC is highly flexible, allowing administrators to build finely granular access control settings. Roles, or sets of permissions, are allocated to users, groups, and service accounts. These permissions specify the roles’ actions, such as viewing, editing, or deleting resources. This strategy benefits large businesses with complicated processes and diverse user responsibilities, as it ensures that users can only access the information they need to execute their duties.
  • Attribute-Based Access Control (ABAC). ABAC enables or refuses actions depending on various criteria, including user traits, environmental attributes, resource categories, and actions. This approach offers great flexibility and granularity, allowing for the implementation of sophisticated security rules that match an organization’s specific security requirements. For example, a policy may restrict access to a resource to specified times of day or network locations, thus increasing security and control.
  • Webhook Mode. In webhook mode, Kubernetes calls an external service to determine access rights. This adaptable option allows Kubernetes to connect with external authorization systems that enforce their access requirements. The webhook delivers information about the request to the external service, which subsequently responds by allowing or denying the request based on its policies. This solution is especially beneficial for enterprises with an external access control system and wish to easily integrate it with Kubernetes, providing consistent enforcement of security policies across several platforms.

RBAC Configuration Diagram

Commands to manage RBAC include:

# Create a role with specified permissionskubectl create role developer --verb=create --verb=get --resource=pods
# Bind a role to a user within a namespacekubectl create rolebinding developer-binding --role=developer --user=user1 --namespace=dev

#3 Admission Control

Admission controllers are software modules that operate as gatekeepers, intercepting API requests for the Kubernetes server after authentication and authorization. They can change or reject requests to enforce policies. Standard admission controls are:

  • PodSecurityPolicy (PSP). PodSecurityPolicy is a Kubernetes feature that controls security-sensitive parts of pod setups. This policy governs permissions for pod creation and operations throughout the cluster, allowing administrators to enforce rules that limit the use of dangerous features such as privileged containers, prevent the use of host networking and file systems, restrict the injection of additional capabilities, and control access to volume types and filesystems. PSP reduces the risk of security vulnerabilities caused by misconfigured pods by specifying a set of constraints a pod must meet before deployment. This is especially important in contexts where security is critical, as it prevents potential escalation and exploits at the application level.
  • NodeRestriction. This Kubernetes admission controller restricts the kubelet from executing operations only on resources relevant to its node. This prohibits the kubelet from reading or altering resources assigned to other nodes, which is critical for the security and integrity of node operation. The NodeRestriction admittance plugin guarantees that kubelets follow the concept of least privilege, lowering the likelihood of an intranode security breach in which a compromised kubelet affects the rest of the cluster.
  • NamespaceLifecycle. This admission controller oversees the lifecycle of namespaces in the Kubernetes cluster. It inhibits the deletion of system-critical namespaces that are required for the cluster’s functioning and the creation of new objects in a namespace that is about to be deleted. This controller contributes to the cluster’s organizational order an9089d operational efficiency by controlling namespace lifecycles. It is critical for resource cleanup, namespace allocation, and preventing resource leaks, which can result in denial-of-service assaults or resource depletion.

Admission Control Workflow

Example command to enforce a security policy:

# Apply a PodSecurityPolicykubectl apply -f podsecuritypolicy.yaml

Now that we’ve covered the basics of Kubernetes Security Strategy, let’s dig further into our following topic: how to successfully secure your Kubernetes cluster. In this section, we’ll go over a variety of security methods and recommended practices for protecting your cluster from potential attacks and vulnerabilities.

How Do I Secure My Kubernetes Cluster?

Securing a Kubernetes cluster is a multifaceted strategy that necessitates the implementation of appropriate controls across many system components and layers to protect against unauthorized access and other security risks. This procedure includes creating network policies to limit traffic flow, implementing role-based access control (RBAC) to manage user permissions, and deploying security tools to monitor and respond to suspicious activity. To protect against vulnerabilities, the Kubernetes environment should also be updated and patched regularly. Ensuring data encryption in transit and at rest is critical to ensuring the confidentiality and integrity of the cluster’s data. Each of these stages is crucial for developing a solid security framework that protects your Kubernetes infrastructure from both internal and external. We will discuss these aspects in more detail in the following section.

#1 Control Access to the Kubernetes API

The Kubernetes API is the central interface for cluster administration hence security is crucial. It is critical to regulate and limit who can access the cluster and what activities they can take.

  • Use TLS for All API Traffic. The Kubernetes API is the central interface for cluster administration; hence, security is crucial. It is critical to regulate and limit who can access the cluster and what activities they can take.
# Check TLS settings in the Kubernetes API server configurationps aux | grep kube-apiserver | grep -- --tls-cert-file
  • Authentication Mechanisms. Depending on the cluster size and usage, choose an appropriate authentication mechanism, such as X.509 client certificates, static bearer tokens, or integrating with external identity providers like OIDC or LDAP.
# Example: List the current authenticated sessionskubectl get serviceaccounts

#2 Implement Role-Based Access Control (RBAC)

Role-Based Access Control (RBAC) is a method for regulating access to computer or network resources based on the roles of individual users within your enterprise.

  • Configure RBAC Policies. Set up roles and role bindings that define what operations are allowed for each user or group within the cluster. RBAC ensures that users have the minimum necessary access that their roles require.
# Create a role that includes permission to list pods and serviceskubectl create role example-role --verb=list --resource=pods,services --namespace=default
# Bind this role to a userkubectl create rolebinding example-binding --role=example-role --user=john.doe --namespace=default

#3 Secure Node and Pod Access

Kubelets, which run on each node, should have restricted access to ensure they can only perform actions required for their operation.

  • Enable Kubelet Authentication and Authorization. Make sure kubelets are authenticated and authorized before they can interact with the Kubernetes API.
# Example command to set kubelet authentication and authorizationkubelet --authentication-token-webhook=true --authorization-mode=Webhook

#4 Use Network Policies

Network policies define how groups of pods are allowed to communicate with each other and other network endpoints.

  • Define and Implement Network Policies. Create specific rules that govern the traffic between pods within your cluster to isolate and secure network traffic.
# Example network policy to deny all traffic except from the same namespaceapiVersion: networking.k8s.io/v1kind: NetworkPolicymetadata:  name: deny-cross-namespace  namespace: defaultspec:  podSelector: {}  policyTypes:  - Ingress  ingress: []
# Apply the network policykubectl apply -f deny-cross-namespace.yaml

#5 Audit and Monitor Cluster Activities

Keeping a close watch on the activities within your cluster is crucial for early detection of potential security incidents.

  • Enable Audit Logs. Set up audit logs to record actions taken on the API for analysis in the event of an incident.
# Example of enabling audit logs in Kuberneteskube-apiserver --audit-log-path=/var/log/kubernetes/audit.log --audit-log-maxage=30 --audit-log-maxbackup=10 --audit-log-maxsize=100

What Are the Four C’s of Kubernetes Security

The four C’s of Kubernetes security take an extensive strategy to protect cloud-native applications and their environments, from infrastructure to application. These levels of protection are crucial because they form an in-depth defense, ensuring that if one layer is compromised, the remaining layers contribute to total security. There are four C’s:

#1 Cloud (or Cluster)

This layer refers to the security of the underlying infrastructure on which the Kubernetes cluster operates. Whether your cluster is hosted on a public cloud provider like Gcore, or on-premises in your own data centers, securing this layer involves:

  • Verify that the infrastructure is configured correctly, such as with firewalls, private networks, and secure access restrictions.
  • Installing security patches and updates on your operating systems and physical servers.
  • The infrastructure is being monitored for threats and weaknesses.

#2 Clusters

Securing the Kubernetes cluster itself is crucial since it directly manages the containers and orchestrates their deployment and operation. This includes:

  • Configuring Kubernetes components securely, including the API server, etcd, kubelet, and network policies.
  • Using Role-Based Access govern (RBAC) to govern who has access to the Kubernetes API and what actions they can take.
  • Allowing audit logs to track what activities are occurring within the cluster.
  • To prevent vulnerabilities, Kubernetes should be updated and patched on a regular basis.

#3 Containers

Securing containers that run applications and their dependencies is essential to maintaining strong Kubernetes security. This procedure entails using trustworthy base images and running extensive vulnerability assessments to ensure the containers are as secure as feasible from the outset. Furthermore, setting security contexts for containers helps limit their privileges and access to host resources, reducing the risk of a compromise. It is also critical to ensure that containers only use the network and disk resources they require, reducing the attack surface. Finally, runtime security monitoring is needed to detect and prevent malicious activity within the containerized system, ensuring continuous protection against threats.

#4 Code

At the application layer, code security is crucial to ensuring the overall safety of applications running within containers. This security strategy entails using safe coding techniques to protect against vulnerabilities like SQL injection and cross-site scripting. Additionally, static and dynamic analysis techniques are critical in discovering potential security problems in code prior to deployment. Efficient secret management is also required to protect sensitive information from unauthorized users. Furthermore, encrypting data transported to and from the application protects sensitive information from interception and unwanted access.

By carefully addressing each of these layers, enterprises may improve the security of their Kubernetes systems and defend them from a variety of security risks. This approach emphasizes the importance of comprehensive security measures that consider all areas of system architecture and deployment.

Conclusion

Securing your Kubernetes cluster is crucial for protecting your infrastructure. Understanding and implementing Kubernetes security principles such as authentication, authorization, admission control, and network policies can help you build a strong defense against security threats. The four C’s of Kubernetes security (Cloud, Clusters, Containers, and Code) emphasize the layered security strategy required for complete protection. With these measures in place, you can protect your Kubernetes environment and prepare for future scalability and expansion. If you’re looking to leverage the benefits of Kubernetes without the complexities and cost escalations of managing it yourself, Gcore offers Managed Kubernetes, simplifying the process for companies and technical decision-makers.

Discover more with Gcore Managed Kubernetes

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Workloads that need high processing power, such as video encoding, machine learning, or simulations, will benefit from VMs with multiple CPU cores. However, be mindful of CPU architecture—look for VMs that offer the latest processors (e.g., Intel Xeon, AMD EPYC) for better performance per core.It’s also important that the VM has enough memory to avoid paging, which occurs when the system uses disk space as virtual memory, significantly slowing down performance. Consider a configuration with more RAM and support for faster memory types like DDR4 for memory-heavy applications.﹟4 Assess storage performance and capacityStorage performance and capacity can significantly impact the performance of your virtual machine, especially for applications requiring large data volumes. Key considerations include:Disk type: For faster read/write operations, opt for solid-state drives (SSDs) over traditional hard disk drives (HDDs). Some cloud providers also offer NVMe storage, which can provide even greater speed for highly demanding workloads.Disk size: Choose the right size based on the amount of data you need to store and process. Over-allocating storage space might seem like a safe bet, but it can also increase costs unnecessarily. You can always resize disks later, so avoid over-allocating them upfront.IOPS and throughput: Some workloads require high input/output operations per second (IOPS). If this is a priority for your workload (e.g., databases), make sure that your VM configuration includes high IOPS storage options.﹟5 Weigh up your network requirementsWhen working with cloud-based VMs, network performance is a critical consideration. High-speed and low-latency networking can make a difference for applications such as online gaming, video conferencing, and real-time analytics.Bandwidth: Check whether the VM configuration offers the necessary bandwidth for your workload. For applications that handle large data transfers, such as cloud backup or file servers, make sure that the network interface provides high throughput.Network latency: Low latency is crucial for applications where real-time performance is key (e.g., trading systems, gaming). Choose VMs with low-latency networking options to minimize delays and improve the user experience.Network isolation and security: Check if your VM configuration provides the necessary network isolation and security features, especially when handling sensitive data or operating in multi-tenant environments.﹟6 Factor in cost considerationsWhile it’s essential that your VM has the right configuration, cost is always an important factor to consider. Cloud providers typically charge based on the resources allocated, so optimizing for cost efficiency can significantly impact your budget.Consider whether a pay-as-you-go or reserved model (which offers discounted rates in exchange for a long-term commitment) fits your usage pattern. The reserved option can provide significant savings if your workload runs continuously. You can also use monitoring tools to track your VM’s performance and resource usage over time. This data will help you make informed decisions about scaling up or down so you’re not paying for unused resources.﹟7 Evaluate security featuresSecurity is a primary concern when selecting a VM configuration, especially for workloads handling sensitive data. Consider the following:Built-in security: Look for VMs that offer integrated security features such as DDoS protection, web application firewall (WAF), and encryption.Compliance: Check that the VM configuration meets industry standards and regulations, such as GDPR, ISO 27001, and PCI DSS.Network security: Evaluate the VM's network isolation capabilities and the availability of cloud firewalls to manage incoming and outgoing traffic.﹟8 Consider geographic locationThe geographic location of your VM can impact latency and compliance. Therefore, it’s a good idea to choose VM locations that are geographically close to your end users to minimize latency and improve performance. In addition, it’s essential to select VM locations that comply with local data sovereignty laws and regulations.﹟9 Assess backup and recovery optionsBackup and recovery are critical for maintaining data integrity and availability. Look for VMs that offer automated backup solutions so that data is regularly saved. You should also evaluate disaster recovery capabilities, including the ability to quickly restore data and applications in case of failure.﹟10 Test and iterateFinally, once you've chosen a VM configuration, testing its performance under real-world conditions is essential. Most cloud providers offer performance monitoring tools that allow you to assess how well your VM is meeting your workload requirements.If you notice any performance bottlenecks, be prepared to adjust the configuration. This could involve increasing CPU cores, adding more memory, or upgrading storage. Regular testing and fine-tuning means that your VM is always optimized.Choosing a virtual machine that suits your requirementsSelecting the best virtual machine configuration is a key step toward optimizing your workloads efficiently, cost-effectively, and without unnecessary performance bottlenecks. By understanding your workload’s needs, considering factors like CPU, memory, storage, and network performance, and continuously monitoring resource usage, you can make informed decisions that lead to better outcomes and savings.Whether you're running a small application or large-scale enterprise software, the right VM configuration can significantly improve performance and cost. Gcore offers a wide range of virtual machine options that can meet your unique requirements. Our virtual machines are designed to meet diverse workload requirements, providing dedicated vCPUs, high-speed storage, and low-latency networking across 30+ global regions. You can scale compute resources on demand, benefit from free egress traffic, and enjoy flexible pricing models by paying only for the resources in use, maximizing the value of your cloud investments.Contact us to discuss your VM needs

How to get the size of a directory in Linux

Understanding how to check directory size in Linux is critical for managing storage space efficiently. Understanding this process is essential whether you’re assessing specific folder space or preventing storage issues.This comprehensive guide covers commands and tools so you can easily calculate and analyze directory sizes in a Linux environment. We will guide you step-by-step through three methods: du, ncdu, and ls -la. They’re all effective and each offers different benefits.What is a Linux directory?A Linux directory is a special type of file that functions as a container for storing files and subdirectories. It plays a key role in organizing the Linux file system by creating a hierarchical structure. This arrangement simplifies file management, making it easier to locate, access, and organize related files. Directories are fundamental components that help ensure smooth system operations by maintaining order and facilitating seamless file access in Linux environments.#1 Get Linux directory size using the du commandUsing the du command, you can easily determine a directory’s size by displaying the disk space used by files and directories. The output can be customized to be presented in human-readable formats like kilobytes (KB), megabytes (MB), or gigabytes (GB).Check the size of a specific directory in LinuxTo get the size of a specific directory, open your terminal and type the following command:du -sh /path/to/directoryIn this command, replace /path/to/directory with the actual path of the directory you want to assess. The -s flag stands for “summary” and will only display the total size of the specified directory. The -h flag makes the output human-readable, showing sizes in a more understandable format.Example: Here, we used the path /home/ubuntu/, where ubuntu is the name of our username directory. We used the du command to retrieve an output of 32K for this directory, indicating a size of 32 KB.Check the size of all directories in LinuxTo get the size of all files and directories within the current directory, use the following command:sudo du -h /path/to/directoryExample: In this instance, we again used the path /home/ubuntu/, with ubuntu representing our username directory. Using the command du -h, we obtained an output listing all files and directories within that particular path.#2 Get Linux directory size using ncduIf you’re looking for a more interactive and feature-rich approach to exploring directory sizes, consider using the ncdu (NCurses Disk Usage) tool. ncdu provides a visual representation of disk usage and allows you to navigate through directories, view size details, and identify large files with ease.For Debian or Ubuntu, use this command:sudo apt-get install ncduOnce installed, run ncdu followed by the path to the directory you want to analyze:ncdu /path/to/directoryThis will launch the ncdu interface, which shows a breakdown of file and subdirectory sizes. Use the arrow keys to navigate and explore various folders, and press q to exit the tool.Example: Here’s a sample output of using the ncdu command to analyze the home directory. Simply enter the ncdu command and press Enter. The displayed output will look something like this:#3 Get Linux directory size using 1s -1aYou can alternatively opt to use the ls command to list the files and directories within a directory. The options -l and -a modify the default behavior of ls as follows:-l (long listing format)Displays the detailed information for each file and directoryShows file permissions, the number of links, owner, group, file size, the timestamp of the last modification, and the file/directory name-a (all files)Instructs ls to include all files, including hidden files and directoriesIncludes hidden files on Linux that typically have names beginning with a . (dot)ls -la lists all files (including hidden ones) in long format, providing detailed information such as permissions, owner, group, size, and last modification time. This command is especially useful when you want to inspect file attributes or see hidden files and directories.Example: When you enter ls -la command and press Enter, you will see an output similar to this:Each line includes:File type and permissions (e.g., drwxr-xr-x):The first character indicates the file type- for a regular filed for a directoryl for a symbolic linkThe next nine characters are permissions in groups of three (rwx):r = readw = writex = executePermissions are shown for three classes of users: owner, group, and others.Number of links (e.g., 2):For regular files, this usually indicates the number of hard linksFor directories, it often reflects subdirectory links (e.g., the . and .. entries)Owner and group (e.g., user group)File size (e.g., 4096 or 1045 bytes)Modification date and time (e.g., Jan 7 09:34)File name (e.g., .bashrc, notes.txt, Documents):Files or directories that begin with a dot (.) are hidden (e.g., .bashrc)ConclusionThat’s it! You can now determine the size of a directory in Linux. Measuring directory sizes is a crucial skill for efficient storage management. Whether you choose the straightforward du command, use the visual advantages of the ncdu tool, or opt for the versatility of ls -la, this expertise enhances your ability to uphold an organized and efficient Linux environment.Looking to deploy Linux in the cloud? With Gcore Edge Cloud, you can choose from a wide range of pre-configured virtual machines suitable for Linux:Affordable shared compute resources starting from €3.2 per monthDeploy across 50+ cloud regions with dedicated servers for low-latency applicationsSecure apps and data with DDoS protection, WAF, and encryption at no additional costGet started today

How to Run Hugging Face Spaces on Gcore Inference at the Edge

Running machine learning models, especially large-scale models like GPT 3 or BERT, requires a lot of computing power and comes with a lot of latency. This makes real-time applications resource-intensive and challenging to deliver. Running ML models at the edge is a lightweight approach offering significant advantages for latency, privacy, and resource optimization.  Gcore Inference at the Edge makes it simple to deploy and manage custom models efficiently, giving you the ability to deploy and scale your favorite Hugging Face models globally in just a few clicks. In this guide, we’ll walk you through how easy it is to harness the power of Gcore’s edge AI infrastructure to deploy a Hugging Face Space model. Whether you’re developing NLP solutions or cutting-edge computer vision applications, deploying at the edge has never been simpler—or more powerful. Step 1: Log In to the Gcore Customer PortalGo to gcore.com and log in to the Gcore Customer Portal. If you don’t yet have an account, go ahead and create one—it’s free. Step 2: Go to Inference at the EdgeIn the Gcore Customer Portal, click Inference at the Edge from the left navigation menu. Then click Deploy custom model. Step 3: Choose a Hugging Face ModelOpen huggingface.com and browse the available models. Select the model you want to deploy. Navigate to the corresponding Hugging Face Space for the model. Click on Files in the Space and locate the Docker option. Copy the Docker image link and startup command from Hugging Face Space. Step 4: Deploy the Model on GcoreReturn to the Gcore Customer Portal deployment page and enter the following details: Model image URL: registry.hf.space/ethux-mistral-pixtral-demo:latest Startup command: python app.py Container port: 7860 Configure the pod as follows: GPU-optimized: 1x L40S vCPUs: 16 RAM: 232GiB For optimal performance, choose any available region for routing placement. Name your deployment and click Deploy.Step 5: Interact with Your ModelOnce the model is up and running, you’ll be provided with an endpoint. You can now interact with the model via this endpoint to test and use your deployed model at the edge.Powerful, Simple AI Deployment with GcoreGcore Inference at the Edge is the future of AI deployment, combining the ease of Hugging Face integration with the robust infrastructure needed for real-time, scalable, and global solutions. By leveraging edge computing, you can optimize model performance and simultaneously futureproof your business in a world that increasingly demands fast, secure, and localized AI applications. Deploying models to the edge allows you to capitalize on real-time insights, improve customer experiences, and outpace your competitors. Whether you’re leading a team of developers or spearheading a new AI initiative, Gcore Inference at the Edge offers the tools you need to innovate at the speed of tomorrow. Explore Gcore Inference at the Edge

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