eBPF and Cilium: Modern Networking and Observability for Kubernetes

TL;DR

eBPF and Cilium: Modern Networking and Observability for Kubernetes without the fluff: focus on outcomes, measure them, and stop pretending slides are progress.

“If you still treat your dataplane as a black box, you are troubleshooting blindfolded; eBPF removes the blindfold.”

Why eBPF + Cilium?

eBPF lets the kernel run safe, programmable code in critical paths. Cilium uses eBPF to deliver high‑performance networking, network policy enforcement, and rich flow visibility—often reducing complexity vs. iptables‑based CNIs.

Core Capabilities

• CNI dataplane: High‑performance routing and load balancing
• Network policies: L3/L4/L7 enforcement with identities and DNS awareness
• Observability: Hubble provides rich flow logs, service maps, and alerts
• Encryption: WireGuard or IPsec for node‑to‑node encryption

Migration Strategy

• Start in a non‑prod cluster; validate CNI compatibility and kernel versions
• Plan IPAM and service CIDR migrations carefully; snapshot network policies
• Enable Hubble for visibility; baseline traffic and errors before/after

Example: L7 Policy with Cilium

apiVersion: cilium.io/v2
kind: CiliumNetworkPolicy
metadata:
  name: allow-api-only
  namespace: payments
spec:
  endpointSelector:
    matchLabels:
      app: api
  ingress:
    - toPorts:
        - ports:
            - port: "80"
              protocol: TCP
          rules:
            http:
              - method: GET
                path: "/v1/health"

Operations

• Monitor dataplane metrics (drops, retransmits), Hubble flows, and policy hits
• Establish runbooks for policy blocks, DNS issues, and IPAM exhaustion
• Keep Cilium versions aligned with cluster/K8s versions; rehearse upgrades

Pitfalls

• Kernel version gaps; ensure managed Kubernetes supports eBPF features
• Policy sprawl; adopt naming/labeling conventions and test matrices
• Blind spots without Hubble; enable early and use dashboards

Conclusion

Cilium with eBPF upgrades Kubernetes networking and security while improving visibility. Roll out gradually, observe thoroughly, and standardize policies to keep complexity in check.

Long‑Form Addendum: A Practical Operating Model for eBPF and Cilium: Modern Networking and Observability for Kubernetes

“Resilience is a behavior, not a topology.”

1) Define Your Non‑Negotiables

Start with the constraints you cannot violate: customer impact, regulated data boundaries, and acceptable recovery windows. Write them down as measurable targets:

• RTO and RPO per system of record
• An SLO for the top user journeys (login, checkout, API success)
• A definition of “tier-1”: what pages the on-call, what can wait

2) Runbook (Repeatable)

1. Preflight: verify capacity headroom, DNS and ingress health, controller errors, and that tier‑1 workloads have sane replicas and a PDB.
2. Execute: make one change at a time (control plane, then node pools, then add-ons). Publish timed checkpoints to a shared channel.
3. Validate: run synthetics per region/cluster, confirm burn-rate alerts are stable, and ensure the control plane (API, scheduler) latency has not regressed.
4. Rollback: revert the last change (node pool, add-on, or traffic steering) before you start debugging. Debugging is easier when the blast radius is shrinking.
5. Document: update the runbook with the 2–3 pivots that actually worked.

3) Concrete Guardrails

• No manual drift: changes go through Git; break-glass is time-bound and then codified.
• Standardized components: one ingress pattern, one policy stack, one logging/tracing convention per fleet.
• Controlled disruption: test drain behavior in staging; ensure you can drain a node without violating PDBs or taking SLO hits.
• Ownership clarity: every platform component has an on-call and an escalation path.

4) Metrics That Prove This Works

• Change failure rate during maintenance windows
• Median time to complete a safe node pool rotation
• % tier‑1 services with rehearsed runbooks in the last 90 days
• Alert quality: pages that include dashboard links, owners, and a next action

5) A Small Checklist

• One “go/no‑go” dashboard exists (SLO burn + synthetics + platform signals).
• Every tier‑1 service has a tested rollback and a failover decision tree.
• Policies and configs are versioned and enforced (GitOps + RBAC).
• Quarterly drills produce measurable improvements and updated runbooks.

Appendix 1: Checklists, Gates, and a 30/60/90 Plan

A Minimal “Go/No‑Go” Gate

Before you execute a risky operation, confirm:

• You have a clear stop signal (SLO burn + a synthetic journey).
• You can roll back within minutes (node pool revert, traffic revert, or Git revert).
• You have capacity headroom to absorb churn (surge nodes, autoscaler limits, and realistic disruption budgets).

30/60/90 (Operating Improvements)

• 30 days: standardize dashboards and alerts; prove you can drain a node without violating a PDB; document one runbook with owner + links.
• 60 days: automate preflight checks; rehearse a controlled failure (node pool rotation or traffic failover) and publish a short retro.
• 90 days: make the drill routine; track outcomes (maintenance change failure rate, duration, and customer impact).

Common Investigations (What On‑Call Actually Does)

• “Are we failing because of DNS?” Check CoreDNS latency, NXDOMAIN spikes, and node-local cache health.
• “Are we failing because of scheduling?” Check pending pods, webhook timeouts, and priority class preemption.
• “Are we failing because of data?” Confirm which writes are region/cluster pinned and whether replication lag is within RPO.

Checklist

• One owner per platform component and an escalation path.
• One canonical runbook per operation (upgrade, failover, restore).
• One “break-glass” procedure with time-bound access and codification afterward (RBAC + audit logs).

Appendix 2: Checklists, Gates, and a 30/60/90 Plan

A Minimal “Go/No‑Go” Gate

Before you execute a risky operation, confirm:

• You have a clear stop signal (SLO burn + a synthetic journey).
• You can roll back within minutes (node pool revert, traffic revert, or Git revert).
• You have capacity headroom to absorb churn (surge nodes, autoscaler limits, and realistic disruption budgets).

30/60/90 (Operating Improvements)

• 30 days: standardize dashboards and alerts; prove you can drain a node without violating a PDB; document one runbook with owner + links.
• 60 days: automate preflight checks; rehearse a controlled failure (node pool rotation or traffic failover) and publish a short retro.
• 90 days: make the drill routine; track outcomes (maintenance change failure rate, duration, and customer impact).

Common Investigations (What On‑Call Actually Does)

• “Are we failing because of DNS?” Check CoreDNS latency, NXDOMAIN spikes, and node-local cache health.
• “Are we failing because of scheduling?” Check pending pods, webhook timeouts, and priority class preemption.
• “Are we failing because of data?” Confirm which writes are region/cluster pinned and whether replication lag is within RPO.

Checklist

• One owner per platform component and an escalation path.
• One canonical runbook per operation (upgrade, failover, restore).
• One “break-glass” procedure with time-bound access and codification afterward (RBAC + audit logs).