Having run Lacework in production for 18 months on a ~300-node K8s cluster, here's my grounded take. We pushed it hard across CSPM, CWPP, and container registry scanning. The goal was to consolidate tools and reduce alert fatigue. Results were mixed.
**What it does well (and why we kept it):**
* **Unified Data Platform:** This is its core strength. Having compliance, host vulnerabilities, container vulnerabilities, and cloud resource misconfigs in a single queryable interface saves hours during investigations. The Polygraph data model is legit.
* **Baseline-based Alerting:** The behavioral learning for processes and network connections significantly reduced noise after the initial learning period. We're not chasing every single new process spawn.
* **K8s Runtime Visibility:** The depth of pod/container execution data during an incident is excellent. You can reconstruct the attack chain without manually cobbling together logs from three different systems.
**Where it falls short for DevOps/SRE teams:**
* **Cost:** The pricing model is opaque and can explode. We got hit with a massive bill increase after enabling container registry scanning on a large number of repos. The sales rep's initial "it's just a few dollars per container" line didn't scale to reality.
* **Agent Performance:** The agent is heavy. On some of our higher-throughput nodes, we consistently saw 5-8% CPU utilization attributed to the Lacework agent. We had to adjust resource requests and limits to account for it, which is not ideal.
* **Remediation Guidance:** Often vague. It will flag a critical CVE in a container image but not provide actionable, version-specific fix details. You're still heading to the vendor's advisory. For cloud misconfigurations, the Terraform snippets it *sometimes* generates are often for older provider versions.
* **CI/CD Integration Feels Bolted-On:** The container image scanning in the pipeline is slow enough to impact our build times. We had to move it to an async post-build step, which defeats the purpose of "fail fast." The policy-as-code (LaceQL) framework is powerful but lacks a robust local testing toolchain.
**Bottom line for DevOps:** If you need a single pane of glass for security observability and have the budget, it's a strong contender. However, be prepared to fight the agent resource battle and scrutinize the pricing breakdown. For teams that want deep integration into their GitOps flow and fast pipeline feedback, it's less impressive. We're currently evaluating whether a combo of open-source tools (Trivy, Checkov) and a more focused CSPM might be more cost-effective and performant for our specific workflows.
-shift
shift left or go home
That cost point hits home. We're evaluating it for a smaller setup but the pricing is a total black box. How long did the "initial learning period" for behavioral alerts take on your cluster? I'm worried we'd be drowning in noise for months.
It took about 4-6 weeks for the behavioral alerts to settle. But the key was aggressively tuning the baseline policy severity during that period. You can't just set and forget it.
The container registry scanning cost was a surprise for us too. The bill wasn't tied to actual scans, but to the total number of unique image tags it indexed across all our repos, including old dev branches.
Proof in production.