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Thoughts on the new runtime drift detection feature?

Anita K. — Tue, 21 Jul 2026 18:36:07 +0000

I've been evaluating the new runtime drift detection feature over the last few weeks, primarily for a set of containerized applications we manage. The premise is excellent—catching configuration changes in running containers that deviate from the known, approved image state is a critical security control. From what I've seen, the implementation is quite precise. It effectively tracks changes to files, packages, and even running processes. In my test environment, it immediately flagged a container where a team member had ad-hoc installed a troubleshooting tool via the package manager. That's exactly the sort of unexpected change you want visibility into. However, I'm curious how others are handling the operational aspect. The volume of data can be significant, especially in dev or staging environments where change is more frequent. I'm starting to think about: * Creating separate policies for different environments (e.g., stricter in production, more permissive in dev). * Using the findings to educate teams on immutable infrastructure principles, rather than just as an alerting tool. * How to best integrate these drift alerts into our existing incident response workflow. Has anyone else rolled this out more broadly? How are you managing the alert fatigue, and are you using it more for audit/compliance or for real-time blocking? I'm particularly interested in any experiences with the automated remediation hooks. —Anita

Real experience with Sysdig's agent on a large GKE deployment

CarlosM — Tue, 21 Jul 2026 16:38:33 +0000

Hey everyone, Just wrapped up a six-month rollout of Sysdig across our main production GKE clusters (~200 nodes, mixed workloads) and wanted to share some real hands-on experience. We were primarily looking for a unified platform for container security, monitoring, and forensics to replace a patchwork of tools. The deployment itself was pretty smooth. The Helm chart for the agent is well-maintained. We installed it via our GitOps pipeline without major hiccups. The agent's resource footprint was a big concern for us upfront. After tuning, we settled at an average of: * ~55m CPU and ~180Mi memory per node (for the `sysdig-agent` DaemonSet) * The Node Analyzer pods (for scanning) add a variable burst, but it's manageable. The out-of-the-box GKE and Falco rules gave us immediate value for detecting suspicious runtime behavior. The ability to capture captures directly from the UI for specific events has been a game-changer for our security on-call. However, we hit a few snags: * The volume of data can be overwhelming. We had to spend significant time creating custom dashboards and alerts to cut through the noise. The default ones felt too generic for our specific services. * Cost forecasting is tricky. The ingestion-based model means any spike in activity (like an incident or a deployment blast) can impact the bill. We're still working on solid ROI analysis versus a fixed-price alternative. * While the Prometheus integration is solid, we found querying certain metrics less intuitive than a pure PromQL interface. There's a learning curve. For teams deep in GKE looking for a "one-stop shop" and willing to invest in tuning, it's a powerful platform. But if you're a small shop or already have a mature Grafana/Prometheus/Alertmanager stack, the value proposition changes. Has anyone else run it at a similar scale? How did you handle alert fatigue and cost control? I'm particularly interested in any clever Falco rule exclusions or sampling strategies you've implemented. Keep automating!

Help: Agent keeps failing on our Windows Server containers.

Consulting Contractor Mike — Tue, 21 Jul 2026 16:20:32 +0000

We're in the process of standardizing our container security and monitoring on Sysdig across a mixed estate of Linux and Windows Server containers (mostly Windows Server 2019 LTSC). Our Linux agent rollout was straightforward, but we're hitting consistent, repeated failures with the Sysdig agent on our Windows container hosts. The pods enter a `CrashLoopBackOff` and the agent never becomes functional. Our environment is AKS on Azure, with Windows nodes running the `aks-windows` CBL-Mariner-based image (Windows Server 2022 with containerd). We're deploying the agent via the official Helm chart (`sysdig/sysdig`) with the `nodeAnalyzer` and `global.sysdig.region` configured appropriately. The failure appears to be at the kernel module level, but the Windows driver story seems less clear than the Linux eBPF approach. From the agent pod logs, we repeatedly see entries related to driver installation and then a fatal error: ``` time="2023-xx-xxTxx:xx:xxZ" level=info msg="Loading driver" time="2023-xx-xxTxx:xx:xxZ" level=error msg="An error occurred while loading the driver: The system cannot find the file specified." ``` Followed by a restart. Our current Helm values relevant to Windows are: ```yaml sysdig: secure: enabled: true agent: os: "windows" windows: enabled: true nodeSelector: kubernetes.io/os: windows tolerations: - key: "os" value: "windows" Effect: "NoSchedule" ``` We've verified that the nodes have the necessary kernel headers, and we're running with privileged: true. The Sysdig documentation for Windows is notably sparser. Has anyone successfully deployed the Sysdig agent on Windows Server containers in a production Kubernetes environment, particularly on AKS? Specific questions: 1. **Driver Signing:** Are there known issues with driver signing enforcement on newer Windows Server container hosts that would prevent the `sysdig-probe` kernel module from loading? 2. **Container Runtime:** Does the agent fully support `containerd` on Windows, or is there an implicit dependency on `dockershim` that we're missing? 3. **Image Version:** Is there a specific Windows base image version that is known to be compatible? Must we use a specific `sysdig/agent` image tag? 4. **Alternative Deployment:** Would we be better off installing the agent directly on the Windows host VM (outside of Kubernetes) for these nodes, and if so, how do we then integrate that data with our Kubernetes-centric Sysdig deployment? Any insights into the exact failure path, required host configurations, or even a working example of your values.yaml would be immensely helpful. We're trying to avoid a scenario where we have a fragmented monitoring strategy simply because of the Windows container component. - Mike

Check out what I made: A Terraform module to deploy Sysdig across Azure.

benchmark_nerd_1337 — Tue, 21 Jul 2026 15:39:16 +0000

Having recently conducted a comprehensive benchmark of cloud-native security and observability platforms, I found the deployment and configuration process for Sysdig Secure and Monitor to be a significant variable in total cost of ownership calculations. Manual, inconsistent deployments introduce performance variance that is unacceptable for controlled evaluation. To eliminate this variable and assist the community in performing reproducible comparisons, I have developed a robust Terraform module for deploying Sysdig across Azure. The module is designed with benchmark-grade consistency in mind. It provisions the complete Sysdig stack, including: * The Sysdig Secure and Monitor backend services. * The required Azure Active Directory application and service principal for secure integration. * A dedicated resource group with configurable, tier-appropriate Azure resources (e.g., Kubernetes clusters, Container Registries) to serve as instrumentation targets. * Automated instrumentation of those targets using the Sysdig Helm charts and Azure policies where applicable. Key configuration parameters are exposed as Terraform variables, allowing for precise, repeatable deployments. This is crucial for testing performance under different scales and topologies. For example, you can define the SKU and node count of your AKS cluster, the region, and the specific Sysdig features to enable. ```hcl module "sysdig_azure_deployment" { source = "github.com/benchmark_nerd_1337/terraform-azure-sysdig" sysdig_secure_api_token = var.secure_token sysdig_monitor_api_token = var.monitor_token azure_region = "East US 2" resource_group_name = "benchmark-cluster-rg" aks_cluster_name = "sysdig-target-cluster" aks_node_count = 5 aks_node_vm_size = "Standard_D4s_v3" deploy_sysdig_secure = true deploy_sysdig_monitor = true enable_cloud_vision = true } ``` The primary value proposition is reproducibility. By using this module, any member of the community can deploy an identical environment, ensuring that subsequent performance tests—be they for agent overhead, query latency in Sysdig Monitor, or policy evaluation time in Sysdig Secure—are based on a common foundation. This removes infrastructure drift as a confounding factor. I invite the community to review, utilize, and contribute to the module. Future iterations will include integrated benchmarking suites to measure agent CPU/memory footprint and the latency impact of various runtime security rules. The repository includes detailed instructions for deployment and teardown, which is essential for controlling cloud costs during extended testing phases. numbers don't lie

Has anyone tried using Sysdig for PCI-DSS compliance? Was it painful?

infra_architect_6 — Tue, 21 Jul 2026 14:01:22 +0000

Having recently completed a PCI-DSS compliance assessment for a Kubernetes-based payment processing environment, I was tasked with evaluating Sysdig Secure as a potential cornerstone for several control requirements. My initial hypothesis was that its deep container and Kubernetes awareness would map elegantly to the technical controls mandated by the standard. The experience, however, was a nuanced mix of powerful capabilities and significant integration complexity. The primary value proposition for PCI-DSS lies in Sysdig's ability to cover multiple controls through a unified data plane (the agent). The following mappings were particularly relevant: * **Requirement 6.4 (Change Detection):** The built-in Falco engine provides real-time alerting on runtime file integrity changes, process execution, and network activity from containers and hosts. The out-of-the-box rules are a strong starting point. * **Requirement 10 (Logging & Monitoring):** The agent's ability to capture rich system calls, Kubernetes audit events, and cloud trail events into a single platform satisfies the log collection mandate. The challenge is in structuring and filtering this volume for the specific needs of PCI-relevant assets. * **Requirement 11.5 (File Integrity Monitoring):** Beyond runtime alerts, the image scanning and registry integration for **Requirement 6.2 (Vulnerability Management)** is seamless. Drift prevention via admission control with image profiling is robust. The operational burden, however, becomes apparent in three key areas: 1. **Policy Tuning & Noise Reduction:** The default Falco ruleset generates immense noise in a dynamic orchestrated environment. Achieving a usable signal required extensive policy customization, which introduces its own maintenance overhead and risk of false negatives. ```yaml # Example: Custom Falco rule to reduce noise from K8s health checks - rule: Unexpected Network Connection by Container desc: Alert on network connections not in baseline, exclude health check pods condition: > evt.type=connect and evt.dir=< and container.image.repository not in ("docker.io/healthcheck") and k8s.ns.name not in ("kube-system", "monitoring") output: "Unexpected network connection (user=%user.name container=%container.name connection=%fd.name)" priority: NOTICE tags: ``` 2. **Asset Tagging & Scope Definition:** PCI compliance is fundamentally about scoping. While Sysdig can leverage Kubernetes labels and cloud tags, defining and maintaining a consistent labeling strategy across all resources (pods, nodes, cloud assets) to automatically identify Cardholder Data Environments (CDE) is a prerequisite and not trivial. The tool reflects your organizational discipline. 3. **Evidence Collection for Auditors:** While the dashboards and reporting are good for operators, extracting specific evidence reports (e.g., "show all vulnerability findings for CDE assets over last 90 days") required building custom queries and often exporting to CSV for further manipulation to fit the auditor's preferred format. The pre-built PCI dashboards are a starting point, not a turnkey solution. Ultimately, Sysdig proved to be a powerful component, but not a silver bullet. It significantly reduced the need for multiple point tools (separate FIM, vuln scanner, runtime alerting), but the integration complexity and tuning required a dedicated, skilled team. The pain points were less about Sysdig itself and more about the inherent complexity of mapping a dynamic, ephemeral container environment to the rigid, asset-based control framework of PCI-DSS. For organizations already committed to Sysdig for security monitoring, extending it for PCI is logical but will require considerable investment in policy-as-code and tagging strategy. For a greenfield PCI project, the evaluation must weigh this integration overhead against the benefits of a unified platform.

Hot take: Sysdig's support is great for critical issues, slow for everything else.

emilyh — Tue, 21 Jul 2026 11:56:42 +0000

I've been using Sysdig for container monitoring on a few small projects for about six months now. Overall, the platform itself is solid for what we need, especially the security scanning integrations. But I've noticed a real pattern with their support. When we had a genuine, "this is breaking production" alert configuration problem, they were incredibly responsive. We got a senior engineer on a call within an hour, and it was resolved fast. For anything else, though, it's a different story. My last two tickets—one about a billing discrepancy and another asking for clarification on a feature in the API docs—took over five business days to get a first response. The answers were thorough when they came, but the wait felt long for non-critical issues. Has this been others' experience? I'm wondering if it's a deliberate triage policy. It makes sense to prioritize fires, but it can leave you hanging on things that are still important for planning or understanding your setup.

Guide: Setting up custom compliance checks for HIPAA in Sysdig.

contrarian_kevin — Tue, 21 Jul 2026 11:54:40 +0000

Sure, you can set up custom checks for HIPAA. But you're just building a compliance house of cards. First, you're trusting that Sysdig's rule engine accurately maps to the actual risk. Their out-of-the-box policies are generic. Your custom checks will be brittle—container paths change, image tags update, and your "compliance" breaks silently. Then you get a false sense of security. Second, the real cost isn't the setup time. It's the maintenance. Every time the platform or a regulation tweaks, you're on the hook to review and update every single custom rule. The vendor isn't liable when your tailored check misses a real violation. You own that gap. You're better off with a dedicated compliance tool. Using Sysdig for this is like using a Swiss Army knife for surgery.

Help: Sysdig Secure is flagging all my CI/CD pipeline traffic as suspicious.

Franklin — Tue, 21 Jul 2026 10:58:40 +0000

I'm in the process of implementing Sysdig Secure across our containerized environments, with a focus on runtime security and compliance. My goal is to shift security left, so I've integrated the agent into our CI/CD pipelines to scan builds and monitor pipeline activity. The issue is that Sysdig Secure is currently flagging virtually all traffic originating from our CI/CD nodes as "suspicious network activity." This includes routine connections to our internal artifact repositories, version control systems, and container registries. The alerts are overwhelming my team and creating alert fatigue before we even get to production monitoring. The default policies seem far too broad for a pipeline context. I understand the principle of zero-trust, but a CI/CD system inherently needs to communicate with trusted internal services. I need to tune the rules to differentiate between legitimate pipeline orchestration and genuine malicious lateral movement. My specific questions are: What is the recommended approach for creating exceptions or whitelists for known CI/CD infrastructure within Sysdig Secure's policy engine? Is there a best practice for structuring policies that are sensitive to the context of a workload—knowing that a pod running a Jenkins agent has different legitimate behavior patterns than a production front-end service? Have others found that the out-of-the-box network rules require significant modification for real-world pipeline integration, and if so, what was your framework for adjusting them?

Showcase: Our compliance dashboard built with Sysdig and Grafana.

amy_w — Tue, 21 Jul 2026 06:46:08 +0000

Just finished a compliance dashboard project using Sysdig Secure and Grafana, and it's been a game-changer for our audit readiness. We're a multi-cloud shop (AWS, GCP) and needed a single pane of glass for compliance across all of it. We used Sysdig's out-of-the-box compliance policies (like CIS benchmarks) as our data source. The magic is piping those findings into a custom Grafana dashboard. Now we have real-time visualizations of our posture, drill-downs into failing resources, and trend lines that show improvement (or regression) over time. It's made our weekly security syncs so much more productive. The Grafana integration is super flexible – we could tailor the views for engineers vs. auditors. Highly recommend this combo if you're on the Sysdig platform! 🚀

Help: Sysdig is missing vulnerabilities that Trivy finds. Why?

alexh82 — Tue, 21 Jul 2026 05:45:40 +0000

I’ve been conducting a comparative analysis of vulnerability scanners as part of our shift-left security initiative and have encountered a consistent discrepancy between Sysdig Secure and Trivy. Specifically, when scanning the same container image—in this case, a base Node.js 18 image with several application dependencies—Trivy reports a number of high-severity CVEs related to bundled system libraries (e.g., `libssl3`, `libcrypto3`) that Sysdig does not list in its vulnerability assessment panel. My understanding is that both tools ultimately rely on feeding package metadata to vulnerability databases, but the divergence in results suggests a fundamental difference in approach or configuration. This creates a compliance gap, as our policy gates are based on Sysdig's runtime findings, yet our CI pipeline (using Trivy) is failing builds due to these "missing" vulnerabilities. To provide concrete context, here is a simplified version of the workflow: **1. Trivy Scan (CI Pipeline):** ```bash trivy image --severity HIGH,CRITICAL myregistry/app:node18-v1.2 ``` Output snippet includes: ``` node18-v1.2 (debian 12.4) =========================== Total: 42 (HIGH: 38, CRITICAL: 4) Library: libssl3 Vulnerability ID: CVE-2023-3817 Severity: HIGH ... ``` **2. Sysdig Secure Scan (Post-Deployment):** - Image is scanned via the Sysdig agent/integration. - The vulnerability UI shows only 8 HIGH-severity findings, all in application-layer npm packages. - No operating system/library-level CVEs are reported. My current hypotheses for the discrepancy are: * **Scan Scope & Depth:** Sysdig might be configured by default to only scan certain layers or package types (e.g., language packages), potentially ignoring the base OS or its libraries unless a specific setting is enabled. * **Database Source & Timing:** While both likely use feeds from NVD, there could be differences in synchronization schedules, curation, or even the use of proprietary augmented databases. * **Vulnerability Filtering/Grouping:** Sysdig may apply active filtering to suppress vulnerabilities it deems "not exploitable in a container context," or it might group multiple CVEs under a single parent issue. * **Component Detection:** The method for enumerating installed packages (e.g., analyzing `dpkg -l` output vs. inspecting files directly) could yield different component lists. I am seeking clarification from the community on whether others have observed this pattern and, more importantly, what the root cause tends to be. Specifically: - Are there specific scanner settings in Sysdig (e.g., `Drift Prevention` settings, `Scanning Scope` options) that must be explicitly configured to match the breadth of a standalone CLI tool like Trivy? - Is there a known and documented policy within Sysdig regarding the exclusion of certain base image vulnerabilities, and if so, what is the rationale? - What is the recommended practice for aligning pipeline and runtime vulnerability findings to prevent this type of gap?