3 Commits

Author SHA1 Message Date
google-labs-jules[bot]
2e019b16ff fix: Correct Dockerfile lib path and add Helm dependency toggle
This commit includes two main changes:

1.  **Fix Dockerfile library path for amd64:**
    - I updated the `exporter/Dockerfile` to correctly determine the source path for `libiperf.so.0` when building for different architectures.
    - Specifically, for `TARGETARCH=amd64`, the path `/usr/lib/x86_64-linux-gnu/libiperf.so.0` is now used.
    - For `TARGETARCH=arm64`, the path `/usr/lib/aarch64-linux-gnu/libiperf.so.0` is used.
    - I achieved this by copying the library to a canonical temporary location in the builder stage based on `TARGETARCH`, and then copying it from this location into the final image. This resolves an issue where builds for `amd64` would fail to find the library.

2.  **Add Helm chart option to disable dependencies:**
    - I added a new option `dependencies.install` (default: `true`) to `charts/iperf3-monitor/values.yaml`.
    - This allows you to disable the installation of managed dependencies (i.e., Prometheus Operator via `kube-prometheus-stack` or `prometheus-operator` from TrueCharts) even if `serviceMonitor.enabled` is true.
    - I updated the `condition` for these dependencies in `charts/iperf3-monitor/Chart.yaml` to `dependencies.install, serviceMonitor.enabled, ...`.
    - This is useful for you if you manage your Prometheus Operator installation separately.
2025-06-20 13:25:34 +00:00
google-labs-jules[bot]
a00629af7a fix: Ensure multi-platform builds with Docker Buildx
This commit updates the GitHub Actions workflows to correctly set up
Docker Buildx for multi-platform (amd64, arm64) image builds.

Previously, the workflows were missing the `docker/setup-buildx-action`
step, which led to errors when attempting multi-platform builds as the
default Docker driver does not support this.

The following changes were made:
1.  **Added `docker/setup-buildx-action@v3`:**
    - This step is now included in both the CI (`.github/workflows/ci.yaml`) and Release (`.github/workflows/release.yml`) workflows before the QEMU setup and build/push actions.

2.  **Dockerfile (`exporter/Dockerfile`):**
    - Remains as per the previous commit, using `TARGETARCH` to correctly copy architecture-specific libraries. This part was already correct for multi-arch builds.

3.  **Helm Chart:**
    - No changes were required for the Helm chart.

This ensures that the CI/CD pipeline can successfully build and push
Docker images for both `linux/amd64` and `linux/arm64` architectures.
2025-06-20 13:13:46 +00:00
google-labs-jules[bot]
e1164a597e feat: Add support for arm64 architecture
This commit introduces support for the arm64 architecture by:

1.  **Updating the Dockerfile:**
    *   The `exporter/Dockerfile` now uses the `TARGETARCH` build argument to dynamically determine the correct path for `libiperf.so.0`. This allows the same Dockerfile to be used for building both `amd64` and `arm64` images.

2.  **Modifying GitHub Workflows:**
    *   The CI workflow (`.github/workflows/ci.yaml`) and the Release workflow (`.github/workflows/release.yml`) have been updated to build and push multi-architecture Docker images (`linux/amd64` and `linux/arm64`).
    *   This involves adding the `docker/setup-qemu-action` for cross-compilation and specifying the target platforms in the `docker/build-push-action`.

3.  **Helm Chart:**
    *   No changes were required for the Helm chart as the image tag will now point to a multi-arch manifest, and the default iperf3 server image (`networkstatic/iperf3:latest`) is assumed to be multi-arch. Node selectors in the chart are not architecture-specific.

These changes enable the deployment of the iperf3-monitor on Kubernetes clusters with arm64 nodes.
2025-06-20 13:00:09 +00:00
5 changed files with 77 additions and 1656 deletions

View File

@@ -27,9 +27,6 @@ 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
@@ -45,28 +42,12 @@ 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 the image if the event is a pull request.
# The workflow currently only triggers on pull_request events.
push: ${{ github.event_name == 'pull_request' }}
push: false # Do not push on PRs
tags: ${{ steps.meta.outputs.tags }}
labels: ${{ steps.meta.outputs.labels }}
platforms: linux/amd64,linux/arm64

View File

@@ -34,8 +34,6 @@ 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

View File

@@ -24,9 +24,6 @@ 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
@@ -88,7 +85,7 @@ rbac:
serviceAccount:
# -- The name of the ServiceAccount to use for the exporter pod.
# Only used if rbac.create is false. If not set, it defaults to the chart's fullname.
name: "iperf3-monitor"
name: ""
serviceMonitor:
# -- If true, create a ServiceMonitor resource for integration with Prometheus Operator.

File diff suppressed because it is too large Load Diff

View File

@@ -1,60 +1,28 @@
"""
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
# --- 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')
# --- Configuration ---
# Configure logging
logging.basicConfig(level=logging.INFO, 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 (Mbps)',
'Network bandwidth measured by iperf3 in Megabits per second',
['source_node', 'destination_node', 'protocol']
)
IPERF_JITTER_MS = Gauge(
'iperf_network_jitter_ms',
'Network jitter measured by iperf3 in milliseconds (ms) for UDP tests',
'Network jitter measured by iperf3 in milliseconds',
['source_node', 'destination_node', 'protocol']
)
IPERF_PACKETS_TOTAL = Gauge(
'iperf_network_packets_total',
'Total packets transmitted/received during the iperf3 UDP test',
'Total packets transmitted or received during the iperf3 test',
['source_node', 'destination_node', 'protocol']
)
IPERF_LOST_PACKETS = Gauge(
@@ -70,21 +38,12 @@ IPERF_TEST_SUCCESS = Gauge(
def discover_iperf_servers():
"""
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.
Discover iperf3 server pods in the cluster using the Kubernetes API.
"""
try:
config.load_incluster_config() # Assumes running inside a Kubernetes pod
# Load in-cluster configuration
# Assumes the exporter runs in a pod with a service account having permissions
config.load_incluster_config()
v1 = client.CoreV1Api()
namespace = os.getenv('IPERF_SERVER_NAMESPACE', 'default')
@@ -92,54 +51,67 @@ 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 item in ret.items:
if item.status.pod_ip and item.status.phase == 'Running':
for i in ret.items:
# Ensure pod has an IP and is running
if i.status.pod_ip and i.status.phase == 'Running':
servers.append({
'ip': item.status.pod_ip,
'node_name': item.spec.node_name # Node where the iperf server pod is running
'ip': i.status.pod_ip,
'node_name': i.spec.node_name
})
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 main loop
return [] # Return empty list on error to avoid crashing the loop
def run_iperf_test(server_ip, server_port, protocol, source_node_name, dest_node_name):
def run_iperf_test(server_ip, server_port, protocol, source_node, dest_node):
"""
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).
Runs a single iperf3 test and updates Prometheus metrics.
"""
logging.info(f"Running iperf3 {protocol.upper()} test from {source_node_name} to {dest_node_name} ({server_ip}:{server_port})")
logging.info(f"Running iperf3 test from {source_node} to {dest_node} ({server_ip}:{server_port}) using {protocol.upper()}")
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
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
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}")
IPERF_TEST_SUCCESS.labels(**labels).set(0)
# Set metrics to 0 on failure
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_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
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)
@@ -147,151 +119,42 @@ def run_iperf_test(server_ip, server_port, protocol, source_node_name, dest_node
IPERF_PACKETS_TOTAL.labels(**labels).set(0)
IPERF_LOST_PACKETS.labels(**labels).set(0)
except KeyError:
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.")
pass
return
# If we reach here, the test itself was successful in execution
IPERF_TEST_SUCCESS.labels(**labels).set(1)
# 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.
# 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.
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
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
# 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
IPERF_BANDWIDTH_MBPS.labels(**labels).set(bandwidth_mbps)
# UDP specific metrics
if protocol == 'udp':
# 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)
# 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)
else:
# For TCP tests, ensure UDP-specific metrics are set to 0
# Ensure UDP metrics are zeroed or absent for TCP tests
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()