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iperf3-monitor
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feat: Implement iperf3 exporter core logic and log level configuration (#13) 

* feat: Implement iperf3 exporter core logic and log level configuration

This commit completes the core functionality of the iperf3 exporter and adds flexible log level configuration.

Key changes:
- Added command-line (`--log-level`) and environment variable (`LOG_LEVEL`) options to configure the logging level.
- Implemented the main test orchestration loop (`main_loop`) which:
    - Discovers iperf3 server pods via the Kubernetes API.
    - Periodically runs iperf3 tests (TCP/UDP) between the exporter pod and discovered server pods.
    - Avoids self-testing.
    - Uses configurable test intervals, server ports, and protocols.
    - Requires `SOURCE_NODE_NAME` to be set.
- Refined the `parse_and_publish_metrics` function to:
    - Accurately parse iperf3 results for bandwidth, jitter, packets, and lost packets.
    - Set `IPERF_TEST_SUCCESS` metric (0 for failure, 1 for success).
    - Zero out all relevant metrics for a given path upon test failure to prevent stale data.
    - Handle UDP-specific metrics correctly, zeroing them for TCP tests.
    - Improved robustness in accessing iperf3 result attributes.
- Updated the main execution block to initialize logging, start the Prometheus HTTP server, and invoke the main loop.
- Added comprehensive docstrings and inline comments throughout `exporter/exporter.py` for improved readability and maintainability.

These changes align the exporter's implementation with the details specified in the design document (docs/DESIGN.MD).

* feat: Update Helm chart and CI for exporter enhancements

This commit introduces updates to the Helm chart to support log level
configuration for the iperf3 exporter, and modifies the CI workflow
to improve image tagging for pull requests.

Helm Chart Changes (`charts/iperf3-monitor`):
- Added `exporter.logLevel` to `values.yaml` (default: "INFO") to allow
  you to set the exporter's log level.
- Updated `templates/exporter-deployment.yaml` to use the
  `exporter.logLevel` value to set the `LOG_LEVEL` environment
  variable in the exporter container.

CI Workflow Changes (`.github/workflows/ci.yaml`):
- Modified the Docker image build process to tag images built from
  pull requests with `pr-<PR_NUMBER>`.
- Ensured that these PR-specific images are pushed to the container
  registry.
- Preserved existing tagging mechanisms (e.g., SHA-based tags).

* fix: Add Docker login and permissions to CI workflow

This commit fixes the Docker image push failure in the CI workflow
by adding the necessary Docker login step and ensuring the correct
permissions are set for the GITHUB_TOKEN.

- Added a Docker login step using `docker/login-action@v3` to the
  `Build Docker Image` job in `.github/workflows/ci.yaml`. This
  authenticates to GHCR before attempting to push images.
- Added a `permissions` block to the `Build Docker Image` job, granting
  `packages: write` scope to the `GITHUB_TOKEN`. This is required
  to allow pushing packages to the GitHub Container Registry.

---------

Co-authored-by: google-labs-jules[bot] <161369871+google-labs-jules[bot]@users.noreply.github.com>
fix_rbac v0.1.6
Malar Kannan 2025-06-21 01:02:45 +05:30 committed by GitHub
parent 81b771d1ee
commit 0c490e95d2
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4 changed files with 237 additions and 76 deletions
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21
.github/workflows/ci.yaml vendored
View File

@ -27,6 +27,9 @@ jobs:
build:
name: Build Docker Image
runs-on: ubuntu-latest
permissions:
contents: read # Needed to checkout the repository
packages: write # Needed to push Docker images to GHCR
steps:
- name: Check out code
uses: actions/checkout@v3
@ -42,12 +45,28 @@ jobs:
uses: docker/metadata-action@v4
with:
images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
tags: |
# Tag with the PR number if it's a pull request event
type=match,pattern=pull_request,value=pr-{{number}}
# Tag with the git SHA
type=sha,prefix=
# Tag with 'latest' if on the main branch (though this workflow only runs on PRs to main)
type=ref,event=branch,pattern=main,value=latest
- name: Log in to GitHub Container Registry
uses: docker/login-action@v3
with:
registry: ${{ env.REGISTRY }}
username: ${{ github.actor }}
password: ${{ secrets.GITHUB_TOKEN }}
- name: Build Docker image
uses: docker/build-push-action@v4
with:
context: ./exporter
push: false # Do not push on PRs
# Push the image if the event is a pull request.
# The workflow currently only triggers on pull_request events.
push: ${{ github.event_name == 'pull_request' }}
tags: ${{ steps.meta.outputs.tags }}
labels: ${{ steps.meta.outputs.labels }}
platforms: linux/amd64,linux/arm64

2
charts/iperf3-monitor/templates/exporter-deployment.yaml
View File

@ -34,6 +34,8 @@ spec:
value: "{{ .Values.exporter.testInterval }}"
- name: IPERF_TEST_PROTOCOL
value: "{{ .Values.exporter.testProtocol }}"
- name: LOG_LEVEL
value: "{{ .Values.exporter.logLevel }}"
- name: IPERF_SERVER_PORT
value: "5201" # Hardcoded as per server DaemonSet
- name: IPERF_SERVER_NAMESPACE

3
charts/iperf3-monitor/values.yaml
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@ -24,6 +24,9 @@ exporter:
# -- Interval in seconds between complete test cycles (i.e., testing all server nodes).
testInterval: 300
# -- Log level for the iperf3 exporter (e.g., DEBUG, INFO, WARNING, ERROR, CRITICAL).
logLevel: INFO
# -- Timeout in seconds for a single iperf3 test run.
testTimeout: 10

287
exporter/exporter.py
View File

@ -1,28 +1,60 @@
"""
Prometheus exporter for iperf3 network performance monitoring.
This script runs iperf3 tests between the node it's running on (source) and
other iperf3 server pods discovered in a Kubernetes cluster. It then exposes
these metrics for Prometheus consumption.
Configuration is primarily through environment variables and command-line arguments
for log level.
"""
import os
import time
import logging
import argparse
import sys
from kubernetes import client, config
from prometheus_client import start_http_server, Gauge
import iperf3
# --- Configuration ---
# Configure logging
logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
# --- Global Configuration & Setup ---
# Argument parsing for log level configuration
# The command-line --log-level argument takes precedence over the LOG_LEVEL env var.
# Defaults to INFO if neither is set.
parser = argparse.ArgumentParser(description="iperf3 Prometheus exporter.")
parser.add_argument(
'--log-level',
default=os.environ.get('LOG_LEVEL', 'INFO').upper(),
choices=['DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL'],
help='Set the logging level. Overrides LOG_LEVEL environment variable. (Default: INFO)'
)
args = parser.parse_args()
log_level_str = args.log_level
# Convert log level string (e.g., 'INFO') to its numeric representation (e.g., logging.INFO)
numeric_level = getattr(logging, log_level_str.upper(), None)
if not isinstance(numeric_level, int):
# This case should ideally not be reached if choices in argparse are respected.
logging.error(f"Invalid log level: {log_level_str}. Defaulting to INFO.")
numeric_level = logging.INFO
logging.basicConfig(level=numeric_level, format='%(asctime)s - %(levelname)s - %(message)s')
# --- Prometheus Metrics Definition ---
# These gauges will be used to expose iperf3 test results.
IPERF_BANDWIDTH_MBPS = Gauge(
'iperf_network_bandwidth_mbps',
'Network bandwidth measured by iperf3 in Megabits per second',
'Network bandwidth measured by iperf3 in Megabits per second (Mbps)',
['source_node', 'destination_node', 'protocol']
)
IPERF_JITTER_MS = Gauge(
'iperf_network_jitter_ms',
'Network jitter measured by iperf3 in milliseconds',
'Network jitter measured by iperf3 in milliseconds (ms) for UDP tests',
['source_node', 'destination_node', 'protocol']
)
IPERF_PACKETS_TOTAL = Gauge(
'iperf_network_packets_total',
'Total packets transmitted or received during the iperf3 test',
'Total packets transmitted/received during the iperf3 UDP test',
['source_node', 'destination_node', 'protocol']
)
IPERF_LOST_PACKETS = Gauge(
@ -38,12 +70,21 @@ IPERF_TEST_SUCCESS = Gauge(
def discover_iperf_servers():
"""
Discover iperf3 server pods in the cluster using the Kubernetes API.
Discovers iperf3 server pods within a Kubernetes cluster.
It uses the in-cluster Kubernetes configuration to connect to the API.
The target namespace and label selector for iperf3 server pods are configured
via environment variables:
- IPERF_SERVER_NAMESPACE (default: 'default')
- IPERF_SERVER_LABEL_SELECTOR (default: 'app=iperf3-server')
Returns:
list: A list of dictionaries, where each dictionary contains the 'ip'
and 'node_name' of a discovered iperf3 server pod. Returns an
empty list if discovery fails or no servers are found.
"""
try:
# Load in-cluster configuration
# Assumes the exporter runs in a pod with a service account having permissions
config.load_incluster_config()
config.load_incluster_config() # Assumes running inside a Kubernetes pod
v1 = client.CoreV1Api()
namespace = os.getenv('IPERF_SERVER_NAMESPACE', 'default')
@ -51,110 +92,206 @@ def discover_iperf_servers():
logging.info(f"Discovering iperf3 servers with label '{label_selector}' in namespace '{namespace}'")
# List pods across all namespaces with the specified label selector
# Note: list_pod_for_all_namespaces requires cluster-wide permissions
ret = v1.list_pod_for_all_namespaces(label_selector=label_selector, watch=False)
servers = []
for i in ret.items:
# Ensure pod has an IP and is running
if i.status.pod_ip and i.status.phase == 'Running':
for item in ret.items:
if item.status.pod_ip and item.status.phase == 'Running':
servers.append({
'ip': i.status.pod_ip,
'node_name': i.spec.node_name
'ip': item.status.pod_ip,
'node_name': item.spec.node_name # Node where the iperf server pod is running
})
logging.info(f"Discovered {len(servers)} iperf3 server pods.")
return servers
except config.ConfigException as e:
logging.error(f"Kubernetes config error: {e}. Is the exporter running in a cluster with RBAC permissions?")
return []
except Exception as e:
logging.error(f"Error discovering iperf servers: {e}")
return [] # Return empty list on error to avoid crashing the loop
return [] # Return empty list on error to avoid crashing the main loop
def run_iperf_test(server_ip, server_port, protocol, source_node, dest_node):
def run_iperf_test(server_ip, server_port, protocol, source_node_name, dest_node_name):
"""
Runs a single iperf3 test and updates Prometheus metrics.
Runs a single iperf3 test against a specified server and publishes metrics.
Args:
server_ip (str): The IP address of the iperf3 server.
server_port (int): The port number of the iperf3 server.
protocol (str): The protocol to use ('tcp' or 'udp').
source_node_name (str): The name of the source node (where this exporter is running).
dest_node_name (str): The name of the destination node (where the server is running).
The test duration is controlled by the IPERF_TEST_DURATION environment variable
(default: 5 seconds).
"""
logging.info(f"Running iperf3 test from {source_node} to {dest_node} ({server_ip}:{server_port}) using {protocol.upper()}")
logging.info(f"Running iperf3 {protocol.upper()} test from {source_node_name} to {dest_node_name} ({server_ip}:{server_port})")
client = iperf3.Client()
client.server_hostname = server_ip
client.port = server_port
client.protocol = protocol
# Duration of the test (seconds)
client.duration = int(os.getenv('IPERF_TEST_DURATION', 5))
# Output results as JSON for easy parsing
client.json_output = True
iperf_client = iperf3.Client()
iperf_client.server_hostname = server_ip
iperf_client.port = server_port
iperf_client.protocol = protocol
iperf_client.duration = int(os.getenv('IPERF_TEST_DURATION', 5)) # Test duration in seconds
iperf_client.json_output = True # Enables easy parsing of results
result = client.run()
# Parse results and update metrics
parse_and_publish_metrics(result, source_node, dest_node, protocol)
def parse_and_publish_metrics(result, source_node, dest_node, protocol):
"""
Parses the iperf3 result and updates Prometheus gauges.
Handles both successful and failed tests.
"""
labels = {'source_node': source_node, 'destination_node': dest_node, 'protocol': protocol}
if result and result.error:
logging.error(f"Test from {source_node} to {dest_node} failed: {result.error}")
try:
result = iperf_client.run()
parse_and_publish_metrics(result, source_node_name, dest_node_name, protocol)
except Exception as e:
# Catch unexpected errors during client.run() or parsing
logging.error(f"Exception during iperf3 test or metric parsing for {dest_node_name}: {e}")
labels = {'source_node': source_node_name, 'destination_node': dest_node_name, 'protocol': protocol}
IPERF_TEST_SUCCESS.labels(**labels).set(0)
# Set metrics to 0 on failure
try:
IPERF_BANDWIDTH_MBPS.labels(**labels).set(0)
IPERF_JITTER_MS.labels(**labels).set(0)
IPERF_PACKETS_TOTAL.labels(**labels).set(0)
IPERF_LOST_PACKETS.labels(**labels).set(0)
except KeyError:
# Labels might not be registered yet if this is the first failure
pass
logging.debug(f"KeyError setting failure metrics for {labels} after client.run() exception.")
def parse_and_publish_metrics(result, source_node, dest_node, protocol):
"""
Parses the iperf3 test result and updates Prometheus gauges.
Args:
result (iperf3.TestResult): The result object from the iperf3 client.
source_node (str): Name of the source node.
dest_node (str): Name of the destination node.
protocol (str): Protocol used for the test ('tcp' or 'udp').
"""
labels = {'source_node': source_node, 'destination_node': dest_node, 'protocol': protocol}
# Handle failed tests (e.g., server unreachable) or missing result object
if not result or result.error:
error_message = result.error if result and result.error else "No result object from iperf3 client"
logging.warning(f"Test from {source_node} to {dest_node} ({protocol.upper()}) failed: {error_message}")
IPERF_TEST_SUCCESS.labels(**labels).set(0)
# Set all relevant metrics to 0 on failure to clear stale values from previous successes
try:
IPERF_BANDWIDTH_MBPS.labels(**labels).set(0)
IPERF_JITTER_MS.labels(**labels).set(0) # Applicable for UDP, zeroed for TCP later
IPERF_PACKETS_TOTAL.labels(**labels).set(0) # Applicable for UDP, zeroed for TCP later
IPERF_LOST_PACKETS.labels(**labels).set(0) # Applicable for UDP, zeroed for TCP later
except KeyError:
# This can happen if labels were never registered due to continuous failures
logging.debug(f"KeyError when setting failure metrics for {labels}. Gauges might not be initialized.")
return
if not result:
logging.error(f"Test from {source_node} to {dest_node} failed to return a result object.")
IPERF_TEST_SUCCESS.labels(**labels).set(0)
try:
IPERF_BANDWIDTH_MBPS.labels(**labels).set(0)
IPERF_JITTER_MS.labels(**labels).set(0)
IPERF_PACKETS_TOTAL.labels(**labels).set(0)
IPERF_LOST_PACKETS.labels(**labels).set(0)
except KeyError:
pass
return
# If we reach here, the test itself was successful in execution
IPERF_TEST_SUCCESS.labels(**labels).set(1)
# The summary data is typically in result.json['end']['sum_sent'] or result.json['end']['sum_received']
# The iperf3-python client often exposes this directly as attributes like sent_Mbps or received_Mbps
# For TCP, we usually care about the received bandwidth on the client side (which is the exporter)
# For UDP, the client report contains jitter, lost packets, etc.
# Determine bandwidth:
# Order of preference: received_Mbps, sent_Mbps, Mbps, then JSON fallbacks.
# received_Mbps is often most relevant for TCP client perspective.
# sent_Mbps can be relevant for UDP or as a TCP fallback.
bandwidth_mbps = 0
if hasattr(result, 'received_Mbps') and result.received_Mbps is not None:
bandwidth_mbps = result.received_Mbps
elif hasattr(result, 'sent_Mbps') and result.sent_Mbps is not None:
# Fallback, though received_Mbps is usually more relevant for TCP client
bandwidth_mbps = result.sent_Mbps
# Add a check for the raw JSON output structure as a fallback
elif result.json and 'end' in result.json and 'sum_received' in result.json['end'] and result.json['end']['sum_received']['bits_per_second'] is not None:
bandwidth_mbps = result.json['end']['sum_received']['bits_per_second'] / 1000000
elif result.json and 'end' in result.json and 'sum_sent' in result.json['end'] and result.json['end']['sum_sent']['bits_per_second'] is not None:
bandwidth_mbps = result.json['end']['sum_sent']['bits_per_second'] / 1000000
elif hasattr(result, 'Mbps') and result.Mbps is not None: # General attribute from iperf3 library
bandwidth_mbps = result.Mbps
# Fallback to raw JSON if direct attributes are None or missing
elif result.json:
# Prefer received sum, then sent sum from the JSON output's 'end' summary
if 'end' in result.json and 'sum_received' in result.json['end'] and \
result.json['end']['sum_received'].get('bits_per_second') is not None:
bandwidth_mbps = result.json['end']['sum_received']['bits_per_second'] / 1000000.0
elif 'end' in result.json and 'sum_sent' in result.json['end'] and \
result.json['end']['sum_sent'].get('bits_per_second') is not None:
bandwidth_mbps = result.json['end']['sum_sent']['bits_per_second'] / 1000000.0
IPERF_BANDWIDTH_MBPS.labels(**labels).set(bandwidth_mbps)
# UDP specific metrics
if protocol == 'udp':
# iperf3-python exposes UDP results directly
IPERF_JITTER_MS.labels(**labels).set(result.jitter_ms if hasattr(result, 'jitter_ms') and result.jitter_ms is not None else 0)
IPERF_PACKETS_TOTAL.labels(**labels).set(result.packets if hasattr(result, 'packets') and result.packets is not None else 0)
IPERF_LOST_PACKETS.labels(**labels).set(result.lost_packets if hasattr(result, 'lost_packets') and result.lost_packets is not None else 0)
# These attributes are specific to UDP tests in iperf3
IPERF_JITTER_MS.labels(**labels).set(getattr(result, 'jitter_ms', 0) if result.jitter_ms is not None else 0)
IPERF_PACKETS_TOTAL.labels(**labels).set(getattr(result, 'packets', 0) if result.packets is not None else 0)
IPERF_LOST_PACKETS.labels(**labels).set(getattr(result, 'lost_packets', 0) if result.lost_packets is not None else 0)
else:
# Ensure UDP metrics are zeroed or absent for TCP tests
# For TCP tests, ensure UDP-specific metrics are set to 0
try:
IPERF_JITTER_MS.labels(**labels).set(0)
IPERF_PACKETS_TOTAL.labels(**labels).set(0)
IPERF_LOST_PACKETS.labels(**labels).set(0)
except KeyError:
# Can occur if labels not yet registered (e.g. first test is TCP)
logging.debug(f"KeyError for {labels} when zeroing UDP metrics for TCP test.")
pass
def main_loop():
"""
Main operational loop of the iperf3 exporter.
This loop periodically:
1. Fetches configuration from environment variables:
- IPERF_TEST_INTERVAL (default: 300s): Time between test cycles.
- IPERF_SERVER_PORT (default: 5201): Port for iperf3 servers.
- IPERF_TEST_PROTOCOL (default: 'tcp'): 'tcp' or 'udp'.
- SOURCE_NODE_NAME (critical): Name of the node this exporter runs on.
2. Discovers iperf3 server pods in the Kubernetes cluster.
3. Runs iperf3 tests against each discovered server (unless it's on the same node).
4. Sleeps for the configured test interval.
If SOURCE_NODE_NAME is not set, the script will log an error and exit.
"""
# Fetch operational configuration from environment variables
test_interval = int(os.getenv('IPERF_TEST_INTERVAL', 300))
server_port = int(os.getenv('IPERF_SERVER_PORT', 5201))
protocol = os.getenv('IPERF_TEST_PROTOCOL', 'tcp').lower() # Ensure lowercase
source_node_name = os.getenv('SOURCE_NODE_NAME')
# SOURCE_NODE_NAME is crucial for labeling metrics correctly.
if not source_node_name:
logging.error("CRITICAL: SOURCE_NODE_NAME environment variable not set. This is required. Exiting.")
sys.exit(1)
logging.info(
f"Exporter configured. Source Node: {source_node_name}, "
f"Test Interval: {test_interval}s, Server Port: {server_port}, Protocol: {protocol.upper()}"
)
while True:
logging.info("Starting new iperf test cycle...")
servers = discover_iperf_servers()
if not servers:
logging.warning("No iperf servers discovered in this cycle. Check K8s setup and RBAC permissions.")
else:
for server in servers:
dest_node_name = server.get('node_name', 'unknown_destination_node') # Default if key missing
server_ip = server.get('ip')
if not server_ip:
logging.warning(f"Discovered server entry missing an IP: {server}. Skipping.")
continue
# Avoid testing a node against itself
if dest_node_name == source_node_name:
logging.info(f"Skipping test to self: {source_node_name} to {server_ip} (on same node: {dest_node_name}).")
continue
run_iperf_test(server_ip, server_port, protocol, source_node_name, dest_node_name)
logging.info(f"Test cycle completed. Sleeping for {test_interval} seconds.")
time.sleep(test_interval)
if __name__ == '__main__':
# Initial logging (like log level) is configured globally at the start of the script.
# Fetch Prometheus exporter listen port from environment variable
listen_port = int(os.getenv('LISTEN_PORT', 9876))
try:
# Start the Prometheus HTTP server to expose metrics.
start_http_server(listen_port)
logging.info(f"Prometheus exporter listening on port {listen_port}")
except Exception as e:
logging.error(f"Failed to start Prometheus HTTP server on port {listen_port}: {e}")
sys.exit(1) # Exit if the metrics server cannot start
# Enter the main operational loop.
# main_loop() contains its own critical checks (e.g., SOURCE_NODE_NAME) and will exit if necessary.
main_loop()