Vincenzo Tagliavia (CKA, CKAD, CKS)
CKA, CKAD, CKS, LFCS
Last modified: 19 Nov 2024
Our Kubernetes Monitoring Best Practices help you run your clusters and applications smoothly and efficiently. We offer 7 essential steps to automate Monitoring deployments, reduce costs and eliminate common providers' lock-ins. This guide endorses Kubernetes Monitoring Best Practices and includes monitoring tools to deploy a full-stack in seconds.
Kubernetes Monitoring is one of the first strategies to consider if you endorse Kubernetes Security Best Practices. But security isn’t the only factor that comes into play. Like with any other well-designed system, Kubernetes Monitoring provides insights into your infrastructure. These insights improve performance, robustness and availability of your systems.
What makes Kubernetes Monitoring different from other platforms?
Kubernetes captures data “snapshots” across nodes, pods and containers. These snapshots aren’t aggregated nor persisted by default. This means we need to configure and deploy a centralized system to aggregate, store and query this data – the Kubernetes project recommends this centralized approach at the cluster level.
A Kubernetes Monitoring strategy goes hand in hand with Observability. These two concepts are intertwined but often confused. Kubernetes Monitoring provides insights into what is happening in the System. Observability in contrast helps explain why the system behaves in a particular way.
1. Data Volume
Kubernetes environments generate vast amounts of data. According to a 2023 report by CNCF, the average Kubernetes cluster generates over 1TB of logs per day. Managing this data volume requires scalable storage solutions and efficient data processing pipelines.
2. Dynamic Nature of Containers
Kubernetes is a platform to manage and dynamically scale containerized applications. But containers are ephemeral and can behave erratically. Kubernetes Monitoring allows you to identify and resolve resource bottlenecks, issues and failures. By enabling cluster-wide logging, the logging agent captures activities in dynamic environments at scale.
3. Tool Fragmentation
Many organizations use a mix of open-source and commercial observability tools, leading to fragmented data and insights. A 2022 survey by the Cloud Native Computing Foundation (CNCF) found that 68% of organizations use more than three observability tools. This fragmentation can hinder the ability to get a unified view of system health and performance.
1. Centralize Monitoring
Use a centralized monitoring solution that aggregates metrics and logs from all components of your Kubernetes cluster. This simplifies data analysis and troubleshooting.
2. Leverage Labels and Annotations
Utilize Kubernetes labels and annotations to tag your resources. This helps in organizing and filtering metrics and logs based on specific criteria, such as environment, application, or team.
3. Automate Alerts
Set up automated alerts to notify you of critical issues. Ensure that alerts are actionable and prioritized to avoid alert fatigue.
4. Visualize Metrics
Use dashboards to visualize key metrics and trends. This makes it easier to spot anomalies and understand the overall health of your cluster at a glance.
5. Regular Audits
Conduct regular audits of your monitoring setup to ensure that it remains effective as your Kubernetes environment evolves. Kubernetes Auditing captures events across your cluster but you need to configure it with a persistent volume backend for storage.
6. Use The Four Golden Metrics of Monitoring
The "Four Golden Metrics" is a monitoring framework that takes a “snapshot” of your system's health by using four metrics: Latency, Traffic, Saturation and Errors. The RED framework (Rate, Errors, Duration) in contrast, captures metrics at the application level. Use both for higher coverage and precision in your Kubernetes Monitoring.
7. Automate Your Kubernetes Monitoring Setup
Utilize Helm charts to streamline the deployment of Monitoring tools. This approach reduces manual configuration and ensures consistency. Helm Charts simplify the deployment process and are accessible even to those who aren’t Kubernetes experts. Helm Charts offer a straightforward lifecycle with just four commands: helm install, helm upgrade, helm rollback, and helm uninstall.
1. Prometheus
Prometheus is an open-source monitoring and alerting toolkit designed for reliability and scalability. It collects metrics from various sources and stores them in a time-series database. Prometheus's powerful query language (PromQL) allows you to analyze and alert on your metrics in real-time.
2. OpenMetrics
OpenMetrics is an open standard for exposing metrics. It aims to make metrics collection more consistent across different systems, making it easier to integrate various monitoring tools. OpenMetrics is designed to be compatible with Prometheus, ensuring seamless interoperability.
3. Grafana
Grafana is an open-source visualization and monitoring platform that integrates with various data sources, including Prometheus. It provides powerful and customizable dashboards, allowing you to visualize your metrics, logs, and traces in a unified interface. Grafana also supports alerting, enabling you to set up and manage alerts directly from the dashboards.
4. Loki
Loki is a log aggregation system designed to work seamlessly with Grafana. Unlike traditional log management systems, Loki indexes only the metadata, making it highly efficient in terms of resource consumption. With Loki, you can correlate logs with metrics, providing a comprehensive view of your Kubernetes environment's health and performance.
Effective monitoring is crucial for maintaining the health and performance of your Kubernetes clusters. By understanding the importance of monitoring, addressing common challenges, following best practices, and leveraging powerful tools like Prometheus, OpenMetrics, Grafana, and Loki, you can ensure that your Kubernetes environment runs smoothly and efficiently. This proactive approach to monitoring not only helps you detect and resolve issues early but also enhances the overall reliability and security of your applications.
layout: post meta_title: “Kubernetes Security Best Practices: Simplified Guide” title: “KUBERNETES SECURITY BEST PRACTICES” description: “Simplified guide with 9 Kubernetes security best practices divided into 3 Infrastructure Layers: 1. System, 2. Orchestrator and 3. Application.” date: 2025-01-15 last_modified_at: 2025-01-15 permalink: /blog/kubernetes-security-best-practices author: Vincenzo Tagliavia (CKA, CKAD, CKS) —
Security is top priority in Kubernetes environments, but it is hard. Why is it hard? Because Kubernetes interacts with a lot of components and sub-systems that together make environments complex to understand. This guide helps you implement Kubernetes security best practices in an easy, digestable way.
1. Misconfiguration
Lack of specialized knowledge and human errors are the most common causes of Kubernetes security breaches. The Kubernetes architecture is designed to orchestrate containers. More advanced features require deep know-how of the platform. Take for example Admission Controllers. As for Kubernetes v1.31, there are more than 30 native Admission Controllers that support several use cases to validate or modify requests access. Depending on the Kubernetes distribution you use, only a few Admission Controllers are enabled during cluster initialization. This means that your Kubernetes Administrators must enable them based on business and technical requirements.
2. Encryption & Secrets Management
Kubernetes secrets aren't encrypted by default. Secret objects instead use base64 encoding. This means that the default configuration for secret objects leaves the Kubernetes cluster open to a vast array of exploitations. We recommend 4 immediate resolutions to mediate this issue. First, enforce strict RBAC's to restrict access for human users and system components. GET, WATCH, LIST permissions must be whitelisted. Second, enforce encryption at rest for ETCD, which is disabled by default. Also, enforce TLS/SSL traffic so that secrets don't travel to ETCD in text format. Third, use a third-party secret provider (recommended) to decouple secret storage and management outside the cluster. Not an exhaustive list of recommendations, but they'll get you started.
3. Weak Role Base Access Control
Kubernetes Role Base Access Control (RBAC) is a security control that provides the minimum permissions for individual users or service accounts to operate on specific namespaces and workloads. Without RBAC management, users and service accounts can run cluster operations across resources they shouldn't have access to. Therefore, RBAC allows cluster administrators to implement the Principle of Least Privilege (POLP) and in doing so, think proactively about Kubernetes security best practices.
We outline the baseline recommendations and Kubernetes RBAC best practices as follows:
4. Supply Chain Vulnerabilities
Supply chain vulnerabilities crawl into your development lifecycle from different sources. As a result, supply chain vulnerabilities constitute challenges upstream that your DevSecOps team import in your artifacts. You tackle supply chain risks by taking control of the application development lifecycle. Build, distribution, and deployment phases are all different but interrelated processes of the application lifecycle.
Each phase in the application development lifecycle requires its own tools and strategies. For example, the build phase should only use minimal base images that contain the minimum amount of dependencies required to run (e.g. Linux Alpine based images). Distroless images are another possible solution. The distribution and deployment phases, as another example, should only pull and push images to whitelisted registries you can trust. Static analysis of file systems, binaries, images and configuration files, substantially improve your security posture internally, upstream and downstream. In short, if we can't manage what happens on the outside, we harden the inside.
Kubernetes security best practices is a curated list of "best-of-breed" recommendations from security specialists in the Kubernetes space. For simplicity, we break Kubernetes security into 3 main parts reflecting each Kubernetes architecture layer: system, cluster and application layers. Each layer has its own peculiarities and challenges.
System security includes hardware components and the OS Host
1. Use hardened OS images
Hardened OS images are security-enhanced OS that reduce the attack surface. For example, such operating systems can restrict WRITE operations or only ship the necessary binaries to perform essential functionalities. Talos Linux and Bottlerocket from AWS are two examples of hardened OS(s).
2. Employ Kernel security-enhanced modules
Enable SELinux, AppArmor or Seccomp to restrict system calls to the kernel. These Kernel modules enforce Mandatory Access Control (MAC) in addition to the default OS’s Discretionary Access Control (DAC), which is more permissive. MAC modules are more difficult to operationalize at scale so specific expertise is key to implement them.
3. Incorporate hardware security modules
Hardware Security Module (HSM) and Trusted Platform Module (TPM) are examples of hardware modules. Thes modules are tough to compromise because they operate at the hardware level and provide cryptographic protection and isolation for your workloads. Hardware modules require cost/benefit analysis and specific knowledge to implement. Other factors to consider are potential compatibility issues with some OS.
Security at this layer involves control plane configuration and hardening. The main components that require interventions are the Kubernetes API Server, ETCD and the Kubelet. The following list is not exhaustive.
1. Implement Native Admission Controllers
You implement security policies (Admission Controllers) to validate or modify access to the cluster. These plugins allow more fine-grained authentication and authorization mechanisms. Kubernetes provides Admission Controllers natively but you can also use external policy frameworks (e.g. OPA).
2. Enable Kubernetes API Server Audit logging.
This requires configuration of the Kubernetes API Server and it is compatible with some open-source static and dynamic scanners. Audit Logging only needs a reference to a config file and a backend volume for storage. With knowledge of Linux OS Systems, logs management is vastly simplified.
3. Use a Kubernetes Administrator (CKA or CKS)
We recommend you to consult a Kubernetes specialist to configure and harden your clusters. Kubernetes on-premise or bare metal is a completely different beast than managing Kubernetes in a cloud environment.
You secure your applications by managing supply chain and application lifecycle stages: development, distribution, deployment and runtime. Multi-tenancy setups and distributed teams are common challenges.
1. Adopt the 12-Factor-App development framework
The 12-Factor-App development framework is a set of best practices and guidelines to ship high-quality code. If you have control over development (first phase of CNCF's Security Model), this framework supports portability, maintainability, testability.It can slow down developments and has a learning curve.
2. Adopt a “shift-left” security approach
Integrate security measures early in the development process. For example, use container scanning tools to detect vulnerabilities in images before they are deployed. Or enforce open-source dependencies checks to ensure only high-quality inputs enter your code.
3. Implement Network Policies
Think of Network Policies as native lightweight firewall rules. They allow you to control how traffic flows inside and outside the cluster. Network Policies operate at the OSI Layer 3 and 4. You can specify rules by namespace, pod labels and CIDR block ranges.
Use Service Meshes for more complex requirements. For example, if you require more control over TLS or if logging network security events is crucial to your organization, Services Meshes support either and much more.
Security implementations don’t act in a vacuum. If your strategy doesn’t prioritize and support security, for example with the right policies, processes and people, implementations will be affected.
The majority of security breaches are caused by misconfigurations. Therefore, if we invest in knowledge and talent we prevent these breaches.
DevSecOps supports cross-team collaboration and security integrations. If you support DevSecOps at each stage of your application lifecycle, you improve your security posture.
AI tools predict, analyze and identify patterns across millions of data points. This can be a source of competitive advantage for years to come.
AI/ML models can learn from extensive datasets of known vulnerabilities to predict and identify potential security issues in code or configuration files. If we feed these models with new knowledge and new security breaches as they happen, we could build the next-generation of security tools with more precision and power than ever before.
Kubernetes has security mechanisms baked into the platform but we have to configure and implement them. Lack of know-how – resulting in misconfigurations – and poor allocation of resources to security are common causes of security breaches.
Why are security concerns growing?
Because we lack high-quality specialists and meticulous design in infrastructure deployments. We suggest kubernetes security best practices with a simplified framework that helps secure your infrastructure. But business policies and processes must support implementations and stopping or slowing down projects will not make your cluster more secure. Quite the contrary.