Kubernetes observability shows why access control must follow telemetry

At a glance

What this is: This is a Kubernetes observability primer that argues metrics, logs, and traces only create value when teams can securely control access to the monitoring stack.

Why it matters: It matters because IAM teams must treat observability systems as sensitive infrastructure, with the same privilege, audit, and lifecycle controls used for other high-value operational data.

👉 Read StrongDM's guide to Kubernetes observability, tools, and best practices

Context

Kubernetes observability is the practice of using metrics, logs, and traces to understand what a cluster is doing and why. The governance gap is not the lack of telemetry, but the fact that telemetry platforms themselves become high-value access targets once they aggregate operational and security data across environments.

For identity teams, that means observability cannot be treated as a separate DevOps concern. Access to dashboards, log stores, trace backends, and metric pipelines should be governed like any other privileged pathway, because those systems expose both infrastructure state and sensitive troubleshooting context.

Key questions

Q: How should security teams govern access to Kubernetes observability tools?

A: Security teams should treat observability tools as privileged systems and assign access by operational role, not broad team membership. Separate read, query, and export permissions, require audit logging for every request, and recertify access when people change roles or leave. That keeps telemetry useful for operations without turning it into a lateral intelligence source.

Q: Why do Kubernetes observability platforms increase identity risk?

A: They increase identity risk because they centralize highly sensitive context about infrastructure, service relationships, and incident history. If access is too broad, those platforms reveal how environments are built and where they are weak. That makes them attractive targets for abuse and a natural place to enforce least privilege and strong auditing.

Q: What breaks when observability access is overprovisioned?

A: Overprovisioned access breaks confidentiality and accountability at the same time. Users can see logs, traces, and dashboards they do not need, which can expose credentials, internal endpoints, and incident details. It also makes it harder to prove who accessed what during an investigation because too many identities share the same visibility.

Q: When should observability permissions be recertified?

A: Observability permissions should be recertified whenever a role changes, a team restructures, or the platform expands into new clusters and environments. They should also be reviewed on a fixed schedule for privileged readers and operators. The control should follow current need, not assume that temporary troubleshooting access remains valid indefinitely.

Technical breakdown

Metrics, logs, and traces in Kubernetes observability

Kubernetes observability rests on three data types. Metrics provide numerical signals such as CPU, memory, and latency trends. Logs preserve discrete event records for troubleshooting and audit reconstruction. Traces follow a request across services and show where delays or failures emerge. Together they create a layered view of cluster behaviour, but they also concentrate operational knowledge in one stack. That makes access control, retention, and correlation rules part of the observability design, not an afterthought.

Practical implication: treat observability data as sensitive and scope access separately for metrics, logs, and traces.

Prometheus, Grafana, and ELK as access-controlled telemetry systems

Open source observability tools do more than collect data. Prometheus stores time-series metrics, Grafana turns them into dashboards, and the ELK stack centralizes log analysis. In practice, these tools often connect to credentials, endpoints, and internal service data that attackers or insiders can use to map an environment. Their security profile is therefore closer to a privileged platform than to a passive reporting layer. If the monitoring plane is overexposed, observability becomes a source of lateral insight instead of controlled visibility.

Practical implication: govern observability platforms with least privilege, audit trails, and explicit separation between operators and viewers.

Service mesh observability and request-path visibility

Service meshes add proxy sidecars that intercept service-to-service traffic, giving teams deeper visibility into east-west communication. That improves troubleshooting, but it also means the observability layer can see authentication flows, internal endpoints, and request timing across the cluster. The architecture is useful precisely because it centralizes visibility, yet that centralization raises the sensitivity of the identities that can query it. In identity terms, the mesh is not just telemetry infrastructure, it is privileged access to runtime behaviour.

Practical implication: restrict who can query mesh telemetry and align those entitlements with operational role boundaries.

Breaches seen in the wild

• Schneider Electric credentials breach — exposed credentials gave attackers access to Schneider Electric Jira, exfiltrating 40GB.
• LiteLLM PyPI package breach — LiteLLM PyPI supply chain attack, credentials stolen from users.

Read our 52 NHI Breaches Analysis report for a comprehensive view of breaches impacting Non-Human Identities including AI Agents.

NHI Mgmt Group analysis

Observability platforms are privileged data systems, not neutral monitoring utilities. Once metrics, logs, and traces are centralized, they expose topology, workload behaviour, and often credentials-adjacent context. That makes them part of the identity and access problem, because every dashboard, query path, and export function is a potential privilege boundary. Practitioners should treat the monitoring plane as a sensitive tier of infrastructure, not a convenience layer.

Overshared telemetry creates an identity blast radius that most teams underestimate. The same access that helps engineers diagnose incidents can also reveal how clusters are segmented, which services talk to each other, and where secrets may be surfaced in logs. The named concept here is identity blast radius: the amount of sensitive operational knowledge exposed when observability access is too broad. Teams should therefore align observability entitlements with role and purpose, not with general engineering membership.

Kubernetes observability and privileged access management now overlap in the same control surface. StrongDM frames observability as a secure access problem because the tools used to inspect Kubernetes also become targets for misuse. That is directionally correct for the field: the more telemetry centralization improves operations, the more carefully identity controls must govern who can inspect, export, and retain that data. The practitioner conclusion is simple: monitoring infrastructure must sit inside the access governance model, not beside it.

Lifecycle governance matters for observability access because the people who need telemetry today may not need it tomorrow. Access reviews, offboarding, and role change handling should cover dashboard readers, log investigators, and tracing operators just as they cover database or cluster admins. In Kubernetes environments, stale access to observability tools is especially risky because it exposes both live operational state and historical incident context. Practitioners should recertify observability access on the same cadence as other privileged tooling.

The article also reinforces a broader zero trust pattern for cloud-native operations. Telemetry systems should not be assumed safe simply because they are internal or operational. Under ZT-NIST-207, the relevant question is whether every access request is explicitly authorized, scoped, and auditable. The field should expect observability to become a more common control point for identity governance, especially where multiple clusters and teams share the same monitoring stack.

From our research:

• Only 5.7% of organisations have full visibility into their service accounts, according to Ultimate Guide to NHIs.
• 96% of organisations store secrets outside of secrets managers in vulnerable locations including code, config files, and CI/CD tools.
• The 52 NHI Breaches Analysis shows how weak visibility and unmanaged credentials turn ordinary operational access into breach pathways.

What this signals

Identity blast radius: observability programmes should now measure not just system health, but who can see enough telemetry to reconstruct the environment. As Kubernetes estates expand, the monitoring plane becomes a governance domain in its own right, and access reviews must cover it with the same seriousness as admin tooling.

The fact that only 5.7% of organisations have full visibility into their service accounts points to a broader pattern: most teams still struggle to inventory the identities that underpin operational tooling. That gap makes telemetry governance harder, because you cannot secure or recertify what you cannot reliably see.

For practitioners, the next step is to connect observability to Zero Trust and NHI governance rather than to treat it as a standalone DevOps capability. The more telemetry centralizes across clusters, the more important it becomes to control who can query, export, and retain it.

For practitioners

• Classify observability tooling as privileged infrastructure Map dashboards, log stores, tracing backends, and metrics services into your privileged access inventory so they receive the same approval, logging, and review treatment as admin consoles.
• Separate read, query, and export entitlements Do not give all engineers the same access to monitoring platforms. Split viewer, investigator, and export permissions so teams can inspect telemetry without also being able to bulk extract sensitive data.
• Apply lifecycle controls to observability access Include monitoring tools in joiner, mover, and leaver workflows. Revoke telemetry access when roles change, and recertify it periodically so stale access does not persist across incident response or platform ownership changes.
• Limit trace and log reach to operational need Use role-based scoping to constrain who can query high-fidelity logs, distributed traces, and cross-cluster views. The goal is to preserve troubleshooting value without exposing unnecessary environment detail to broad user groups.

Key takeaways

• Kubernetes observability improves diagnosis, but it also concentrates sensitive operational context inside the monitoring stack.
• The main governance risk is not the dashboard itself, but the breadth of identity access granted to logs, traces, and metrics.
• Teams should govern observability platforms as privileged infrastructure, with scoped access, auditability, and lifecycle reviews.

Key terms

• Kubernetes Observability: Kubernetes observability is the practice of using metrics, logs, and traces to understand cluster behaviour and diagnose problems. In security terms, it also defines a sensitive data layer because the same telemetry that helps operators can expose architecture, identities, and operational patterns.
• Telemetry Plane: The telemetry plane is the collection of tools and data flows used to gather, store, and analyse operational signals. It becomes a governance domain when access to dashboards, logs, and traces can reveal sensitive infrastructure details or incident context.
• Identity Blast Radius: Identity blast radius is the amount of sensitive access, context, or operational visibility exposed when an identity is overprivileged. In observability environments, it describes how much of the cluster and its history a user can reconstruct if telemetry permissions are too broad.
• Distributed Tracing: Distributed tracing is a method for following a request across multiple services so operators can see where latency or failure occurs. It is especially valuable in Kubernetes, but it also captures fine-grained runtime behaviour that should be restricted to those with a clear operational need.

Deepen your knowledge

Kubernetes observability access control and telemetry governance are relevant topics in our NHI Foundation Level course, the industry's only accredited NHI security programme. If you are building monitoring governance around privileged data flows, it is worth exploring.

This post draws on content published by StrongDM: What Is Kubernetes Observability? Best Practices, Tools & More. Read the original.