Connecting with Akto's eBPF traffic collector is recommended for mTLS systems.
For a better understanding, here's an architecture diagram of the setup.
Adding Akto traffic collector
Apply the Daemonset configuration given below using kubectl apply -f auto-daemon set-config.yaml -n <NAMESPACE>. You will find AKTO_NLB_IP after setting up Akto data processor, as mentioned above.
You can add and configure the env variables below to control the daemonset. Here's a diagram of how the module processes traffic:
# This helps in filtering traffic sent to akto, based on certain headers. Here is an example for sending traffic only for 'bookinfo' namespace in an istio setup.
- name: AKTO_MODULE_DISCOVERY_CONFIG
value: '[{"key":{"eq":"x-forwarded-client-cert","ifAbsent":"reject"},"value":{"regex":".*bookinfo.*"}}]'
# Time limit ( in seconds ) after which, a traffic stream is processed and marked inactive. The same stream, is not processed again.
- name: TRAFFIC_INACTIVITY_THRESHOLD
value: "30"
# Max traffic connections kept in memory
- name: TRAFFIC_MAX_ACTIVE_CONN
value: "4096"
# Make this flag true to disable egress traffic. It is recommended to keep this false.
- name: TRAFFIC_DISABLE_EGRESS
value: "false"
# Max mem usage after which the pod restarts ( in MB )
- name: AKTO_MEM_THRESH_RESTART
value: "800"
# Max limit of traffic buffer kept in memory ( in MB )
- name: TRAFFIC_BUFFER_THRESHOLD
value: "600"
# Ignore traffic coming from unresolved IPs, i.e. requests with host header of the format <a.b.c.d>
- name: AKTO_IGNORE_IP_TRAFFIC
value: "false"
# Ignore traffic coming from AWS cloud metadata IP
- name: AKTO_IGNORE_CLOUD_METADATA_CALLS
value: "false"
# The interval poll ( in seconds ) in which data is sent to Akto data processor.
- name: KAFKA_POLL_INTERVAL
value: "0.5"
# If you only want to trace traffic for which SSL termination happens at proxy/service.
- name: CAPTURE_ALL
value: "false"
You can check your API inventory on Akto dashboard to see endpoints being discovered.
Kubernetes Pod Labels Tagging
Env Variables
# This will start capturing the pod labels from all namespaces except
# kube-system, kube-public and kube-node-lease
- name: AKTO_K8_METADATA_CAPTURE
value: "true"
# Use this if you want to capture pod labels from a specific namespace only.
- name: AKTO_K8_METADATA_CAPTURE_NAMESPACE
value: {NAMESPACE}
Frequently Asked Questions (FAQs)
The traffic will contain a lot of sensitive data - does it leave my VPC?
Data remains strictly within your VPC. Akto doesn't take data out of your VPC at all.
Does adding DaemonSet have any impact on performance or latency?
Zero impact on latency. The DaemonSet doesn't sit like a proxy. It works on eBPF technology, which works on traces function calls at kernel level. It is very lightweight. We have benchmarked it against traffic as high as 20M API requests/min. It consumes very low resources (CPU & RAM).
How can I control logs generated by akto's eBPF traffic collector ?
You can utilize the AKTO_LOG_LEVEL environment variable, which accepts DBEUG, INFO, WARN, ERROR, OFF as log levels.
Default level is set to WARN.
I don't see my error on this list here.
Please send us all details at support@akto.io or reach out via Intercom on your Akto dashboard. We will definitely help you out.
Get Support for your Akto setup
There are multiple ways to request support from Akto. We are 24X7 available on the following:
In-app intercom support. Message us with your query on intercom in Akto dashboard and someone will reply.
Contact help@akto.io for email support.
Setup Akto data processor using the guide
Akto traffic collector can be configured to capture Kubernetes Pod labels with each API request. It operates within the Akto eBPF DaemonSet and leverages the to maintain a local in-memory cache of pods running on each node. This cache is used to identify the labels of pod.