K8s-native ยท EKS, AKS, GKE

Kubernetes Observability

Production observability built the Kubernetes-native way. Prometheus Operator with ServiceMonitor and PodMonitor CRDs, OpenTelemetry in-cluster, Loki for logs, Tempo for traces, and eBPF tools for kernel-level visibility. Self-hosted or managed, multi-cluster ready.

4.9โ˜… Clutch ISO 27001
In 6 LAYERS
You'll Have

Prometheus Operator + ServiceMonitor and PodMonitor CRDs

OpenTelemetry in-cluster: metrics, logs, traces unified

eBPF observability: Cilium Hubble and Pixie

Multi-cluster federation with Thanos, Mimir, or Cortex

K8s
native, not bolt-on
6
observability layers
EKS/AKS/GKE
all three supported

Why Kubernetes observability is different

Generic APM tools were designed for static infrastructure. Kubernetes is dynamic: pods come and go, replicas scale up and down, deployments roll over, and namespaces multiply. The observability stack that worked for your VMs falls over the moment you have 200 ephemeral pods producing high-cardinality metrics.

Kubernetes-native observability solves this with declarative configuration (Prometheus Operator), service discovery built on K8s labels and annotations (ServiceMonitor and PodMonitor CRDs), and kernel-level data collection that does not require code changes (eBPF). It is purpose-built for the shape of Kubernetes workloads.

If you are running EKS, AKS, or GKE in production, your general observability strategy needs a K8s-native layer underneath it. That is what this service builds.

What we build

Six layers of Kubernetes observability. Implemented K8s-native, not retrofitted.

Prometheus Operator + CRDs

ServiceMonitor, PodMonitor, and PrometheusRule custom resources. Declarative monitoring that scales with your cluster, not against it.

OpenTelemetry in Kubernetes

OTel Operator with auto-instrumentation for Java, Python, Node.js, .NET, and Go. Sidecar-less collectors and DaemonSet patterns done right.

Logs that scale with pods

Loki and Promtail (or OTel logs) configured for high-cardinality Kubernetes workloads. Log labels that do not blow up your storage bill.

Distributed tracing

Tempo or Jaeger deployed K8s-native, integrated with your service mesh and ingress for end-to-end request flow visibility.

eBPF-level visibility

Cilium Hubble for network observability and Pixie for kernel-level workload metrics without sidecars. Production-grade kernel observability.

Multi-cluster aggregation

Thanos, Mimir, or Cortex for long-term retention and cross-cluster querying. One Grafana, many clusters, one source of truth.

The Kubernetes observability stack

Five domains, each with the K8s-native tools we deploy and operate in production.

Metrics

  • ·Prometheus with Operator
  • ·ServiceMonitor, PodMonitor CRDs
  • ·kube-state-metrics
  • ·node_exporter, cAdvisor
  • ·Custom workload exporters
  • ·Recording rules + PrometheusRule CRDs

Logs

  • ·Loki + Promtail (or Grafana Alloy)
  • ·OpenTelemetry log pipeline
  • ·FluentBit / Vector for shipping
  • ·Label cardinality controls
  • ·Per-namespace retention
  • ·S3 or GCS-backed long-term storage

Traces

  • ·Tempo or Jaeger
  • ·OpenTelemetry Operator
  • ·Auto-instrumentation: Java, Python, Node, .NET, Go
  • ·Tail-based sampling strategies
  • ·Service mesh integration (Istio, Linkerd)
  • ·Ingress trace propagation

Events & Audit

  • ·Kubernetes event aggregation
  • ·kubernetes-event-exporter
  • ·API server audit logs
  • ·Falco for runtime security events
  • ·Alert correlation to events

Network & eBPF

  • ·Cilium Hubble (network)
  • ·Pixie (kernel + HTTP)
  • ·eBPF without sidecars
  • ·Service mesh telemetry
  • ·L7 flow visualization

Visualization & Alerting

  • ·Grafana dashboards
  • ·Alertmanager routing
  • ·SLO and error budget dashboards
  • ·PagerDuty / OpsGenie integration
  • ·Thanos, Mimir, Cortex for scale

How we deliver

Four phases. Tailored to your cluster size and existing observability state.

  1. 1

    Discovery

    Audit your existing K8s observability posture across metrics, logs, traces, events, and network. Identify gaps against the 47-point production readiness checklist.

  2. 2

    Design

    Architect the observability stack: Prometheus Operator topology, log pipeline, trace sampling strategy, retention policies, and cost ceiling per cluster.

  3. 3

    Implement

    Deploy via Helm or GitOps. Provision ServiceMonitor and PodMonitor resources, configure alerts with Alertmanager, ship logs to Loki, and roll out OpenTelemetry instrumentation.

  4. 4

    Operate

    SLO definitions, error budget tracking, on-call alert routing, dashboard standards, and runbooks for the first ten production alert scenarios.

Frequently asked questions

About Kubernetes-native observability and how we deliver it.

How is this different from your /observability-consulting service?

Observability consulting covers your full stack including applications, infrastructure, and cost-optimization angles like replacing Datadog. Kubernetes observability is specifically the K8s-native layer: Prometheus Operator and its CRDs, OpenTelemetry in Kubernetes, eBPF tools that only make sense in K8s, multi-cluster Prometheus federation, and integration with service mesh and ingress. If your environment is Kubernetes-centric, start here.

Do you only work with self-hosted observability stacks?

We deploy and operate self-hosted Prometheus, Loki, Tempo, and OpenTelemetry stacks - that is most of our work because customers want to own their telemetry data. We also work with managed offerings (Grafana Cloud, Amazon Managed Prometheus, Azure Monitor managed Prometheus, Google Managed Service for Prometheus) when that fits the team's operational model better.

Which clusters do you support?

Amazon EKS, Azure AKS, and Google GKE. We work across all three regularly and can advise on cloud-specific observability integrations (CloudWatch Container Insights, Azure Monitor for Containers, Google Cloud Operations for GKE).

What does the Prometheus Operator give me that vanilla Prometheus does not?

Declarative monitoring. Instead of manually editing prometheus.yaml every time a service is added, you create a ServiceMonitor or PodMonitor custom resource and the Operator updates configuration automatically. Combined with PrometheusRule for alerts, your entire monitoring posture lives in Git alongside your application code.

Why eBPF tools like Pixie or Cilium Hubble?

Traditional metrics require code instrumentation; eBPF runs in the Linux kernel and observes pod traffic, syscalls, and network flows with zero application changes. Pixie gives you golden signals and HTTP request data automatically. Cilium Hubble gives you full network observability when you run Cilium as your CNI. These complement Prometheus and OpenTelemetry, not replace them.

Can you help with multi-cluster observability?

Yes. We deploy Thanos, Mimir, or Cortex for long-term metric storage and cross-cluster querying. One Grafana hits the long-term store, individual cluster Prometheus instances handle short-term local scraping. This is the standard pattern for organizations running 3 or more production clusters.

Do you do SLOs and error budgets?

Yes. SLO definitions for your top user-facing services, recording rules in Prometheus to compute error budgets, dashboards in Grafana to visualize burn rate, and Alertmanager routing for SLO violations. SLOs are not theoretical for us; they are operational artifacts your team will use weekly.

What if my cluster is already running Prometheus but it is a mess?

Common scenario. Start with our $495 Kubernetes Production Readiness Audit - the Observability category surfaces what is wrong (high-cardinality metrics, missing SLOs, noisy alerts, retention gaps) and produces a prioritized remediation roadmap. From there we can do the remediation work, or your team can run it from the roadmap.

Productized Service

Kubernetes Production Readiness Audit

47-point assessment of your production EKS, AKS, or GKE cluster. Senior CKA or CKS engineer review. Board-ready report and 90-day remediation roadmap. Delivered in 2 weeks.

$495fixed price ยท 2 weeks ยท no procurement runaround

Ready to make your Kubernetes observable?

20-minute call to scope your environment. We will tell you what is missing before you commit to anything.

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