Brought to you by
Using eBPF to Measure the
k8s Cluster Health
Henrik Rexed
Cloud Native Advocate at

Who is this speaker?
■ Henrik Rexed
■ 15 years of Performance engineering
■ Cloud Native Advocate @Dynatrace
■ Lego Fan
■ Focus on SRE and Observability

Abstract (Hidden)
As a k8s cluster-admin your app teams have a certain expectation of your cluster to be available to deploy services at any
time without problems.
While there is no shortage on metrics in k8s its important to have the right metrics to alert on issues and giving you
enough data to react to potential availability issues.
Prometheus has become a standard and sheds light on the inner behaviour of Kubernetes clusters and workloads.
Lots of KPIs (CPU, IO, network. Etc) in our On-Premise environment are less precise when we start to work in a Cloud
environment.
Ebpf is the perfect technology that fulfills that requirement as it gives us information down to the kernel level.
In 2018 Cloudflare shared an opensource project to expose custom ebpf metrics in
Prometheus.
Join this session and learn about:
• What is ebpf?
• What type of metrics we can collect?
• How to expose those metrics in a K8s environment.
This session will try to deliver a step-by-step guide on how to take advantage of the
ebpf exporter.

■ What is Ebpf?
■ What is Prometheus?
■ How to expose Ebpf metrics in
Prometheus ?
If you stay with me you will learn...

Detect node running out of resource in our
kubernetes cluster
Evicted

There are technics minimize the impact on
critical components
■ Define Resource
● Limit
● Request
■ Define PodClassPrority on you Pods
■ Define Quotas on your Nodes and Namespaces

« CPU Utilization is wrong » Brendon Gregg
■ We are all using CPU utilization to monitor the health of our cluster/servers… but :
Could mean :
■ What are we waiting for ?
● IO
● Memory
● Network?
■ So, CPU utilization is wrong ? It’s a time to collect data that we help us understand
what is really happening on our systems.
Busy idle
Busy Waiting"stalled" Waiting"Idle"

What is eBPF?
Liz Rice,
IsoValent
Brendon
Gregg,
Netflix
Thomas Graf
IsoValent, Cilium

Let’s remind the linux kernel architecture
User
Space
Linux
Kernel
hardware
Process Process
Storage Network
Block device Network device
File
Syscall
Write( ) Read( )
Socket
Syscall
Sendmsg( ) recvmsg( )

BPF program are attached to a syscall event
User
Space
Process
Linux
Kernel
Block Device
Syscall
Write()
Vfs_rea
d

How to report back metrics collected by the BPF program?
■ BPF MAP
● HashMap, Array
● Stack Trace
● …etc
■ With BPF MAP you can store:
● Program state
● Metrics,
● Statistics
● Traces
● BPF Map can be shared with user space
program
User
Space
Process
Linux
Kernel Block Device
Syscall
Write( )
Vfs_read
BPF
map

How do you create a BPF Program with bcc ?
User
Space
Process
Linux
Kernel
Block Device
Write( )
BPF
map
BCC
BPF
program
Verifier
JIT Compiler
Syscall
Syscall

What is Prometheus?
TechWorld with Nana

Prometheus Architecture
Kube State metrics
Node exporter
Cadvisor
App
Third party
Alertmanager
Etc.
Scrap
Prometheus Server
PromQl

Prometheus is becoming a standard
•CouchDb
•Mysql
•Oracle
•PostgreSQL
•MongoDB
•…
Database
•Netgear
•Windows
•IBM Z
•Nvidia
•….etc
Hardware
•MQ
•Kafka
•MQTT
•RabbitMQ
•…etc
Messagin
g
•Tivoli
•Hadoop
•NetApp
•ScaleIO
Storage
•Jira
•Jenkins
•Github
•Fluentd
•Nagios
•…etc
Others

Let’s bring automation
■ Prometheus & Grafana could be configured directly from configuration files:
Prometheus yaml Alertmanager.yaml Dashboard.json

ServiceMonitor map all the services that
expose Prometheus metrics.
The serviceMonitor has a label selector to
select services and the information required
to scrap the metrics :
■ Port
■ interval
Scraping configuration in K8s

Let’s use the Existing project exposing metrics

The CloudFlare Ebpf Exporter
■ The purpose is to run to run bcc tools to collect metrics and
expose them in prometheus
■ This exporter could be used :
● Physical server
● VM
● Containers
● Kubernetes
■ The github repository has several examples to collect :
● Bio latency
● Cachestat
● Cpu instructions
● …etc
cloudflare/ebpf_exporter: Prometheus exporter for custom eBPF metrics (github.com)

What does the deployment looks like in k8s?
ConfigMap
Daemonset
Service
Scraping
annotation
BPF
program
ServiceMonitor

Your BPF program will be defined in the
config map
Data ( config.yaml)
Program
List of
metrics
Kprobe Knetprobe
Raw
tracepoints
perfevents
Code ( c
language)
config.yaml: |
programs:
- name: timers
metrics:
counters:
- name: timer_start_total
help: Timers fired in the kernel
table: counts
labels:
- name: function
size: 8
decoders:
- name: ksym
raw_tracepoints:
timer_start: raw_tracepoint-_timer_start
code: |
#include <linux/timer.h>
BPF_HASH(counts, u64);
RAW_TRACEPOINT_PROBE(timer_start) {
-/ TP_PROTO(struct timer_list *timer,
-/ unsigned long expires,
-/ unsigned int flags),
struct timer_list *timer = (struct timer_list
*)ctx->args[0];
void * function = timer->function;
counts.increment((u64) function);
return 0;
}

The Cgnet project
■ The purpose is to run to run metrics related to the
cgroups of the various pods running in our cluster
■ The github repository has all the examples to deploy the
cgnet in your cluster :
kinvolk-archives/cgnet (github.com)

How does the deployment looks like in k8s?
Daemonset
Service
ServiceMonitor

Step by step approach
Let’s create a
ServiceMonitor to collect
the ebpf-exporter
1
apiVersion: monitoring.coreos.com/v1
kind: ServiceMonitor
metadata:
name: tracer-servicemon
labels:
release: prometheus
spec:
endpoints:
- interval: 10s
port: metrics
selector:
matchLabels:
app: bpf-exporter
Prometheus
2
Create a
Dashboard
3

Brought to you by
Henrik Rexed
Henrik.rexed@dynatrace.com
@hrexed