How Tetragon Tracks Kubernetes Security Events in Real-Time

In the evolving world of cloud-native infrastructure, where scalability, security, and observability are paramount, Tetragon, an open-source project under the Cilium umbrella, emerges as a transformative solution. Tetragon leverages the power of eBPF (extended Berkeley Packet Filter) to observe, enforce, and react to real-time runtime events directly within the Linux kernel, with precise integration into Kubernetes environments.

At its core, Tetragon is an eBPF-based security observability and runtime enforcement tool designed for modern Kubernetes clusters. Unlike traditional agents that depend on logs or external audit data, Tetragon provides low-overhead, real-time insight into kernel-level events such as process execution, network activity, and file system access, all while maintaining deep Kubernetes context.

Let’s explore in rich detail how Tetragon tracks Kubernetes security events in real time, what makes it unique for developers and SREs, and why it’s a game-changer for observability and runtime security.

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Kernel-Level Instrumentation: Tapping into eBPF for Deep Visibility

Why Kernel-Level Insights Matter

To understand how Tetragon operates, one must appreciate the power of eBPF for kernel observability. eBPF allows developers to safely and dynamically insert programs into the Linux kernel at runtime. These programs can be attached to kernel tracepoints, kprobes, and other hooks to gather contextual data about system activity.

Tetragon uses this mechanism to observe kernel-level events directly, including:

• Process lifecycle events such as execve, fork, exit
  
  
• Network-related syscalls like connect, accept, bind
  
  
• File access operations like open, read, write
  
  
• Privilege elevation activities like setuid, capset
  
  

By operating directly in the kernel, Tetragon eliminates the latency and visibility gaps that traditional logging or agents may introduce. There’s no polling, no delay, and no dependency on application instrumentation.

This kernel-based approach also makes Tetragon language-agnostic, and able to operate across all workloads within Kubernetes, whether written in Go, Python, Java, Rust, or any other language.

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Kubernetes Metadata Enrichment: Making Kernel Events Kubernetes-Aware

Bridging Linux Kernel Events with K8s Context

One of Tetragon’s most powerful features is its Kubernetes-native enrichment layer. While eBPF captures raw syscalls or tracepoints, Tetragon correlates these events with:

• Pod name
  
  
• Namespace
  
  
• Container image and ID
  
  
• Deployment or workload label
  
  
• Node name
  
  

This correlation is done in real-time using Cilium’s K8s-aware infrastructure and custom kernel maps. As a result, each syscall or event logged by Tetragon can be traced back to a specific pod, workload, or namespace, allowing teams to understand not just what is happening at the system level, but where and why.

This level of enrichment enables powerful use cases such as:

• Monitoring suspicious activity from a specific pod
  
  
• Auditing all file access by a specific namespace
  
  
• Alerting on privilege escalation inside specific deployments
  
  

This kind of deep context is what transforms raw data into actionable intelligence for both security and development teams.

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Real-Time Streaming of Events: From Kernel to User Space

Ensuring Low-Latency Observability and Actionability

Tetragon is designed for real-time workloads, and its event pipeline is built for speed and scalability. Events are first filtered and processed in-kernel by eBPF programs and only relevant, enriched data is sent to user space.

In user space, the Tetragon daemon (typically deployed as a Kubernetes DaemonSet) collects and processes the event streams. The events can be:

• Printed in structured JSON for logging systems
  
  
• Streamed via gRPC to external consumers
  
  
• Ingested by SIEM, observability stacks, or custom dashboards
  
  

This architecture ensures minimal CPU and memory overhead, while maintaining instant visibility into security events. There’s no compromise between performance and observability.

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Declarative Tracing Policies (CRDs): The Developer’s Toolkit

Write, Deploy, and Enforce Security Rules as Code

Tetragon introduces a powerful concept called TracingPolicies, a Kubernetes Custom Resource Definition (CRD) that allows users to define what events they care about and what actions to take.

These policies are:

• Declarative and version-controlled
  
  
• Highly expressive, with support for filtering on args, UID, labels, process path
  
  
• Capable of triggering actions (e.g., logging, killing a process, denying execution)
  
  

Example use cases for TracingPolicy include:

• Blocking execution of binaries in /tmp folder inside pods
  
  
• Alerting on connect() syscalls from high-privilege containers
  
  
• Auditing file access to /etc/shadow
  
  

Because the policies are implemented using eBPF, enforcement is instantaneous and preemptive, no delay between detection and action. This makes Tetragon not only an observability tool but also a real-time runtime enforcement engine.

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Process Ancestry & Tree Correlation: Unraveling Suspicious Behavior

Seeing the Bigger Picture of Process Behavior in Kubernetes

Another standout capability of Tetragon is process ancestry correlation. Every process execution captured by Tetragon includes its entire parent-child tree, enabling full context on who spawned what and when.

Why does this matter?

• Reverse shells don’t usually start with a bash. They start with an obscure binary that spawns another and then finally opens a socket.
  
  
• Malware often forks subprocesses to evade detection.
  
  
• Devs may want to track down what initiated an unexpected connection or file access.
  
  

By providing causal relationships across process trees, Tetragon enables advanced threat detection and forensic analysis with a timeline-based view of what happened inside a container or pod.

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Network and File I/O Correlation: Full Runtime Observability

Track Connections, Transfers, and Sensitive File Interactions

Tetragon doesn’t just stop at process monitoring, it also offers deep insight into network and file activity:

• Tracks connect(), bind(), and accept() syscalls
  
  
• Logs destination IP, port, protocol, and associates it with the calling process and pod
  
  
• Captures file opens, writes, and access to specific paths (like secret volumes or passwd files)
  
  

This allows:

• Detecting lateral movement from pod to pod
  
  
• Alerting when internal services make external unauthorized connections
  
  
• Identifying data exfiltration attempts through strange file reads
  
  

Every event includes both kernel context and Kubernetes identity, making it easy for teams to correlate these behaviors with the originating workload.

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Exporting and Filtering Events Efficiently

Avoiding Noise and Ensuring Focused Monitoring

One of the traditional challenges in observability tools is event sprawl, a flood of low-value data that’s difficult to process or act upon. Tetragon solves this by supporting kernel-level filtering of events before they leave the kernel.

Filters include:

• Event type
  
  
• Pod label
  
  
• Namespace
  
  
• Command path or arguments
  
  
• Capabilities required
  
  
• User or group ID
  
  

These filters are defined within the TracingPolicy and executed at the eBPF level, ensuring only high-value events are streamed to users or logging systems.

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Real-Time Detection, Alerts, and Enforcement

Automating Response Without Losing Insight

Tetragon’s unique architecture supports detection and enforcement in the same tool, all powered by eBPF.

Real-time response capabilities include:

• Killing a suspicious process the moment it tries to execute a disallowed binary
  
  
• Denying access to protected files or directories
  
  
• Alerting developers or SREs via logging or stream notifications
  
  

This means that teams can detect and neutralize threats without delay, all without needing to modify application code.

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Developer Advantages of Tetragon: Secure Code Meets Secure Runtime

Bridging Dev and Sec in DevSecOps

For developers, Tetragon provides an incredible amount of runtime insight without any code changes. It allows teams to:

• Enforce least privilege access in Kubernetes containers
  
  
• Monitor behavior of third-party or legacy containers
  
  
• Build custom security policies aligned with their application’s logic
  
  

Moreover, because Tetragon is:

• Lightweight (using eBPF, no sidecars)
  
  
• Zero-instrumentation (no code modification)
  
  
• Kubernetes-aware (fully integrated with pods and namespaces)
  
  

…it can be easily integrated into CI/CD pipelines, observability dashboards, and runtime enforcement layers, helping DevOps and security teams move faster without compromising on insight or control.

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Benefits Over Traditional Security Tools

Real-Time, Context-Rich, Zero-Delay Security

Compared to traditional runtime security tools, Tetragon offers:

• Real-time detection and response via eBPF
  
  
• Full Kubernetes context baked into every event
  
  
• Declarative, version-controlled policies
  
  
• Lightweight footprint with no sidecars or userland agents
  
  
• Frictionless integration with developer workflows and CI/CD
  
  

With Tetragon, runtime security becomes proactive, precise, and programmable, not just reactive.

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Final Thoughts: Transforming Observability with eBPF

Tetragon is more than a security tool, it’s a platform for real-time observability, enforcement, and introspection in modern Kubernetes environments. By combining eBPF-powered kernel tracing, policy-driven control, and Kubernetes-native context, it empowers teams to see, understand, and act on what’s happening inside their clusters, without blind spots or delay.

For developers, DevOps, and platform engineers looking to build secure-by-design applications, Tetragon offers the visibility and control needed to protect workloads, detect threats, and maintain peace of mind in production environments.