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[WEB-7447] feat: migrate CE telemetry from OTLP traces to OTLP metrics (#9156)

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* [WEB-7447] feat: migrate CE telemetry from OTLP traces to OTLP metrics

Replace span-based tracing (tracer.py) with OTLP observable gauges,
mirroring the approach already used in plane-ee. Key changes:

- Add otlp_endpoints.py — shared gRPC/HTTP endpoint helpers
- Add telemetry_metrics.py — push_instance_metrics task using
  MeterProvider + observable gauges (service name: plane-ce-api)
- User count excludes bots (is_bot=False)
- Page count excludes bot-owned private pages only
- Domain derived from WEB_URL env var
- Celery beat entry replaced with timedelta schedule +
  configurable METRICS_PUSH_INTERVAL_MINUTES (default 360 min)
- Add explicit opentelemetry-exporter-otlp-proto-grpc dep
- Delete tracer.py and telemetry.py (no longer needed)

Co-authored-by: Plane AI <noreply@plane.so>

* fix: address review comments on CE telemetry metrics

- harden grpc_endpoint_from_url for scheme-less OTLP_ENDPOINT values
  (e.g. "telemetry.plane.so:4317") by prepending "//" before urlparse
- fix WEB_URL domain extraction for scheme-less values with same approach
- replace N+1 workspace count queries (6×N) with 6 batched annotate(Count)
  aggregation queries — reduces DB load significantly at WORKSPACE_METRICS_LIMIT
- add deterministic ordering (order_by created_at) to workspace slice
- harden METRICS_PUSH_INTERVAL_MINUTES env parsing with try/except guard
  and positive-value validation to avoid crash on malformed input

Co-authored-by: Plane AI <noreply@plane.so>

* fix: cap METRICS_PUSH_INTERVAL_MINUTES to prevent timedelta overflow

Add upper-bound check (10_000_000 minutes) and catch OverflowError alongside
ValueError so an arbitrarily large env value cannot crash worker startup via
timedelta(minutes=...) OverflowError.

Co-authored-by: Plane AI <noreply@plane.so>

---------

Co-authored-by: Plane AI <noreply@plane.so>
This commit is contained in:
Manish Gupta
2026-05-28 18:34:27 +05:30
committed by GitHub
parent 0acb32e65e
commit 095b1aa360
8 changed files with 464 additions and 175 deletions
Download Patch File Download Diff File Expand all files Collapse all files
apps/api/plane/celery.py
+19 -4
View File
@@ -5,12 +5,13 @@
# Python imports
import os
import logging
from datetime import timedelta
# Third party imports
from celery import Celery
from pythonjsonlogger.json import JsonFormatter
from celery.signals import after_setup_logger, after_setup_task_logger
from celery.schedules import crontab
from celery.schedules import crontab, schedule
# Module imports
from plane.settings.redis import redis_instance
@@ -20,6 +21,20 @@ os.environ.setdefault("DJANGO_SETTINGS_MODULE", "plane.settings.production")
ri = redis_instance()
# Configurable metrics push interval (in minutes)
# Default: 360 (6 hours), set to 5 for development/testing
def _get_metrics_push_interval_minutes() -> int:
raw = os.environ.get("METRICS_PUSH_INTERVAL_MINUTES", "360")
try:
value = int(raw)
# Cap at 10,000,000 minutes to prevent timedelta(minutes=...) OverflowError
# on arbitrarily large inputs while still allowing multi-year intervals.
return value if 0 < value <= 10_000_000 else 360
except (ValueError, OverflowError):
return 360
METRICS_PUSH_INTERVAL_MINUTES = _get_metrics_push_interval_minutes()
app = Celery("plane")
# Using a string here means the worker will not have to
@@ -32,9 +47,9 @@ app.conf.beat_schedule = {
"task": "plane.bgtasks.email_notification_task.stack_email_notification",
"schedule": crontab(minute="*/5"), # Every 5 minutes
},
"run-every-6-hours-for-instance-trace": {
"task": "plane.license.bgtasks.tracer.instance_traces",
"schedule": crontab(hour="*/6", minute=0), # Every 6 hours
"push-instance-metrics": {
"task": "plane.license.bgtasks.telemetry_metrics.push_instance_metrics",
"schedule": schedule(run_every=timedelta(minutes=METRICS_PUSH_INTERVAL_MINUTES)),
},
# Occurs once every day
"check-every-day-to-delete-hard-delete": {
apps/api/plane/license/bgtasks/telemetry_metrics.py
+381
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@@ -0,0 +1,381 @@
# Copyright (c) 2023-present Plane Software, Inc. and contributors
# SPDX-License-Identifier: AGPL-3.0-only
# See the LICENSE file for details.
# Python imports
import os
import logging
from urllib.parse import urlparse
# Third party imports
from celery import shared_task
from django.db.models import Count
from opentelemetry import metrics
from opentelemetry.sdk.metrics import MeterProvider
from opentelemetry.sdk.metrics.export import PeriodicExportingMetricReader
from opentelemetry.sdk.resources import Resource
# Module imports
from plane.utils.otlp_endpoints import get_otlp_grpc_endpoint, get_otlp_http_metrics_url
from plane.license.models import Instance
from plane.db.models import (
User,
Workspace,
Project,
Issue,
Module,
Cycle,
CycleIssue,
ModuleIssue,
Page,
WorkspaceMember,
)
logger = logging.getLogger(__name__)
WORKSPACE_METRICS_LIMIT = 1000
FLUSH_TIMEOUT_MILLIS = 30000
EXPORT_INTERVAL_MILLIS = 20000
def _create_otlp_metric_exporter():
"""
Create OTLP metric exporter based on OTLP_METRICS_PROTOCOL (http or grpc).
Uses shared endpoint helpers so metrics and traces target the same collector.
Default is grpc; override with OTLP_METRICS_PROTOCOL=http if needed.
"""
protocol = (os.environ.get("OTLP_METRICS_PROTOCOL") or "grpc").strip().lower()
if protocol == "grpc":
from opentelemetry.exporter.otlp.proto.grpc.metric_exporter import (
OTLPMetricExporter as GrpcOTLPMetricExporter,
)
grpc_endpoint = get_otlp_grpc_endpoint()
insecure = os.environ.get("OTEL_EXPORTER_OTLP_METRICS_INSECURE", "").lower() == "true"
return GrpcOTLPMetricExporter(endpoint=grpc_endpoint, insecure=insecure)
# HTTP fallback
from opentelemetry.exporter.otlp.proto.http.metric_exporter import (
OTLPMetricExporter as HttpOTLPMetricExporter,
)
return HttpOTLPMetricExporter(endpoint=get_otlp_http_metrics_url())
def _collect_and_push_metrics() -> None:
"""
Collect instance metrics and push them to OTEL collector.
Uses OTEL metrics SDK to push gauge metrics directly to the collector,
replacing the previous span-based tracing approach.
"""
# Check if the instance is registered
instance = Instance.objects.first()
if instance is None:
logger.debug("No instance registered, skipping metrics push")
return
if not instance.is_telemetry_enabled:
logger.debug("Telemetry disabled, skipping metrics push")
return
# Configure OTEL metrics (gRPC default, or HTTP if OTLP_METRICS_PROTOCOL=http)
protocol = (os.environ.get("OTLP_METRICS_PROTOCOL") or "grpc").strip().lower()
export_endpoint = get_otlp_grpc_endpoint() if protocol == "grpc" else get_otlp_http_metrics_url()
service_name = os.environ.get("SERVICE_NAME", "plane-ce-api")
# Create resource with instance identification for the collector
resource = Resource.create({
"service.name": service_name,
"instance_id": str(instance.instance_id or ""),
"plane.instance.type": "self-hosted",
})
# Configure the OTLP metric exporter (HTTP or gRPC)
logger.info(f"Configuring OTLP exporter: protocol={protocol}, endpoint={export_endpoint}")
exporter = _create_otlp_metric_exporter()
reader = PeriodicExportingMetricReader(
exporter,
export_interval_millis=EXPORT_INTERVAL_MILLIS,
)
# Create a new MeterProvider per execution. Gauges use callbacks that capture
# current DB counts, so we need fresh meters each run. provider.shutdown() in
# finally ensures clean teardown. For a 6-hour periodic task, this overhead is acceptable.
provider = MeterProvider(resource=resource, metric_readers=[reader])
try:
# Get a meter
meter = provider.get_meter(__name__)
# Collect instance-level counts
user_count = User.objects.filter(is_bot=False).count()
workspace_count = Workspace.objects.count()
project_count = Project.objects.count()
issue_count = Issue.objects.count()
module_count = Module.objects.count()
cycle_count = Cycle.objects.count()
cycle_issue_count = CycleIssue.objects.count()
module_issue_count = ModuleIssue.objects.count()
page_count = Page.objects.exclude(owned_by__is_bot=True, access=1).count()
# Derive domain from WEB_URL env var (e.g. https://plane.acmecorp.com -> plane.acmecorp.com).
# Prepend "//" for scheme-less values (e.g. "plane.acmecorp.com") so urlparse
# populates netloc correctly instead of treating the host as a path component.
web_url = os.environ.get("WEB_URL", "")
if web_url and "://" not in web_url:
web_url = "//" + web_url
domain = urlparse(web_url).netloc if web_url else ""
# Common attributes for all instance-level metrics
instance_attrs = {
"instance_id": str(instance.instance_id or ""),
"instance_name": str(instance.instance_name or ""),
"current_version": str(instance.current_version or ""),
"latest_version": str(instance.latest_version or ""),
"edition": str(instance.edition or ""),
"domain": domain,
"is_verified": str(instance.is_verified).lower(),
"is_setup_done": str(instance.is_setup_done).lower(),
}
# Create gauge callbacks for instance-level metrics
def users_callback(_options):
yield metrics.Observation(user_count, instance_attrs)
def workspaces_callback(_options):
yield metrics.Observation(workspace_count, instance_attrs)
def projects_callback(_options):
yield metrics.Observation(project_count, instance_attrs)
def issues_callback(_options):
yield metrics.Observation(issue_count, instance_attrs)
def modules_callback(_options):
yield metrics.Observation(module_count, instance_attrs)
def cycles_callback(_options):
yield metrics.Observation(cycle_count, instance_attrs)
def cycle_issues_callback(_options):
yield metrics.Observation(cycle_issue_count, instance_attrs)
def module_issues_callback(_options):
yield metrics.Observation(module_issue_count, instance_attrs)
def pages_callback(_options):
yield metrics.Observation(page_count, instance_attrs)
# Register observable gauges for instance metrics
meter.create_observable_gauge(
name="plane_instance_users_total",
description="Total number of users in the Plane instance",
callbacks=[users_callback],
)
meter.create_observable_gauge(
name="plane_instance_workspaces_total",
description="Total number of workspaces",
callbacks=[workspaces_callback],
)
meter.create_observable_gauge(
name="plane_instance_projects_total",
description="Total number of projects across all workspaces",
callbacks=[projects_callback],
)
meter.create_observable_gauge(
name="plane_instance_issues_total",
description="Total number of issues across all projects",
callbacks=[issues_callback],
)
meter.create_observable_gauge(
name="plane_instance_modules_total",
description="Total number of modules",
callbacks=[modules_callback],
)
meter.create_observable_gauge(
name="plane_instance_cycles_total",
description="Total number of cycles",
callbacks=[cycles_callback],
)
meter.create_observable_gauge(
name="plane_instance_cycle_issues_total",
description="Total number of issues in cycles",
callbacks=[cycle_issues_callback],
)
meter.create_observable_gauge(
name="plane_instance_module_issues_total",
description="Total number of issues in modules",
callbacks=[module_issues_callback],
)
meter.create_observable_gauge(
name="plane_instance_pages_total",
description="Total number of pages",
callbacks=[pages_callback],
)
# Collect workspace-level metrics (limited to WORKSPACE_METRICS_LIMIT).
# Fetch workspaces in a deterministic order so the slice is stable across runs.
# Counts are batched into 6 aggregation queries instead of 6×N per-workspace
# queries (avoids N+1 at scale when WORKSPACE_METRICS_LIMIT is large).
instance_id_str = str(instance.instance_id or "")
workspaces = list(Workspace.objects.order_by("created_at")[:WORKSPACE_METRICS_LIMIT])
workspace_ids = [ws.id for ws in workspaces]
project_counts = dict(
Project.objects.filter(workspace_id__in=workspace_ids)
.values("workspace_id")
.annotate(count=Count("id"))
.values_list("workspace_id", "count")
)
issue_counts = dict(
Issue.objects.filter(workspace_id__in=workspace_ids)
.values("workspace_id")
.annotate(count=Count("id"))
.values_list("workspace_id", "count")
)
module_counts = dict(
Module.objects.filter(workspace_id__in=workspace_ids)
.values("workspace_id")
.annotate(count=Count("id"))
.values_list("workspace_id", "count")
)
cycle_counts = dict(
Cycle.objects.filter(workspace_id__in=workspace_ids)
.values("workspace_id")
.annotate(count=Count("id"))
.values_list("workspace_id", "count")
)
member_counts = dict(
WorkspaceMember.objects.filter(workspace_id__in=workspace_ids)
.values("workspace_id")
.annotate(count=Count("id"))
.values_list("workspace_id", "count")
)
page_counts = dict(
Page.objects.filter(workspace_id__in=workspace_ids)
.exclude(owned_by__is_bot=True, access=1)
.values("workspace_id")
.annotate(count=Count("id"))
.values_list("workspace_id", "count")
)
workspace_metrics = []
for workspace in workspaces:
ws_id = workspace.id
workspace_metrics.append({
"instance_id": instance_id_str,
"workspace_id": str(ws_id),
"workspace_slug": str(workspace.slug),
"project_count": project_counts.get(ws_id, 0),
"issue_count": issue_counts.get(ws_id, 0),
"module_count": module_counts.get(ws_id, 0),
"cycle_count": cycle_counts.get(ws_id, 0),
"member_count": member_counts.get(ws_id, 0),
"page_count": page_counts.get(ws_id, 0),
})
def _ws_attrs(ws: dict) -> dict:
return {
"workspace_id": ws["workspace_id"],
"workspace_slug": ws["workspace_slug"],
"instance_id": ws["instance_id"],
}
# Create callbacks for workspace-level metrics
def ws_projects_callback(_options):
for ws in workspace_metrics:
yield metrics.Observation(ws["project_count"], _ws_attrs(ws))
def ws_issues_callback(_options):
for ws in workspace_metrics:
yield metrics.Observation(ws["issue_count"], _ws_attrs(ws))
def ws_modules_callback(_options):
for ws in workspace_metrics:
yield metrics.Observation(ws["module_count"], _ws_attrs(ws))
def ws_cycles_callback(_options):
for ws in workspace_metrics:
yield metrics.Observation(ws["cycle_count"], _ws_attrs(ws))
def ws_members_callback(_options):
for ws in workspace_metrics:
yield metrics.Observation(ws["member_count"], _ws_attrs(ws))
def ws_pages_callback(_options):
for ws in workspace_metrics:
yield metrics.Observation(ws["page_count"], _ws_attrs(ws))
# Register observable gauges for workspace metrics
meter.create_observable_gauge(
name="plane_workspace_projects_total",
description="Number of projects per workspace",
callbacks=[ws_projects_callback],
)
meter.create_observable_gauge(
name="plane_workspace_issues_total",
description="Number of issues per workspace",
callbacks=[ws_issues_callback],
)
meter.create_observable_gauge(
name="plane_workspace_modules_total",
description="Number of modules per workspace",
callbacks=[ws_modules_callback],
)
meter.create_observable_gauge(
name="plane_workspace_cycles_total",
description="Number of cycles per workspace",
callbacks=[ws_cycles_callback],
)
meter.create_observable_gauge(
name="plane_workspace_members_total",
description="Number of members per workspace",
callbacks=[ws_members_callback],
)
meter.create_observable_gauge(
name="plane_workspace_pages_total",
description="Number of pages per workspace",
callbacks=[ws_pages_callback],
)
# Force a synchronous flush to ensure all metrics are exported
# force_flush() blocks until all metrics are exported or timeout is reached
flush_success = provider.force_flush(timeout_millis=FLUSH_TIMEOUT_MILLIS)
if flush_success:
logger.info(
f"Successfully pushed metrics to OTEL collector at {export_endpoint} "
f"for instance {instance.instance_id}"
)
else:
logger.warning(
f"Metrics flush timed out for instance {instance.instance_id}, "
f"some metrics may not have been exported"
)
except Exception as e:
logger.exception(f"Error pushing metrics to OTEL collector: {e}")
# Don't re-raise: allow task to complete gracefully so it retries on next scheduled run
finally:
# Shutdown the provider to clean up resources
provider.shutdown()
@shared_task
def push_instance_metrics():
"""
Celery task to push instance metrics to OTEL collector.
Replaces the previous span-based tracing approach with OTLP metrics gauges.
Scheduled to run every 6 hours via Celery beat.
"""
logger.debug("Starting push_instance_metrics task")
try:
_collect_and_push_metrics()
logger.debug("Completed push_instance_metrics task")
except Exception as e:
logger.exception(f"Failed to push instance metrics: {e}")
apps/api/plane/license/bgtasks/tracer.py
-105
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@@ -1,105 +0,0 @@
# Copyright (c) 2023-present Plane Software, Inc. and contributors
# SPDX-License-Identifier: AGPL-3.0-only
# See the LICENSE file for details.
# Third party imports
from celery import shared_task
from opentelemetry import trace
# Module imports
from plane.license.models import Instance
from plane.db.models import (
User,
Workspace,
Project,
Issue,
Module,
Cycle,
CycleIssue,
ModuleIssue,
Page,
WorkspaceMember,
)
from plane.utils.telemetry import init_tracer, shutdown_tracer
@shared_task
def instance_traces():
try:
init_tracer()
# Check if the instance is registered
instance = Instance.objects.first()
# If instance is None then return
if instance is None:
return
if instance.is_telemetry_enabled:
# Get the tracer
tracer = trace.get_tracer(__name__)
# Instance details
with tracer.start_as_current_span("instance_details") as span:
# Count of all models
workspace_count = Workspace.objects.count()
user_count = User.objects.count()
project_count = Project.objects.count()
issue_count = Issue.objects.count()
module_count = Module.objects.count()
cycle_count = Cycle.objects.count()
cycle_issue_count = CycleIssue.objects.count()
module_issue_count = ModuleIssue.objects.count()
page_count = Page.objects.count()
# Set span attributes
span.set_attribute("instance_id", instance.instance_id)
span.set_attribute("instance_name", instance.instance_name)
span.set_attribute("current_version", instance.current_version)
span.set_attribute("latest_version", instance.latest_version)
span.set_attribute("is_telemetry_enabled", instance.is_telemetry_enabled)
span.set_attribute("is_support_required", instance.is_support_required)
span.set_attribute("is_setup_done", instance.is_setup_done)
span.set_attribute("is_signup_screen_visited", instance.is_signup_screen_visited)
span.set_attribute("is_verified", instance.is_verified)
span.set_attribute("edition", instance.edition)
span.set_attribute("domain", instance.domain)
span.set_attribute("is_test", instance.is_test)
span.set_attribute("user_count", user_count)
span.set_attribute("workspace_count", workspace_count)
span.set_attribute("project_count", project_count)
span.set_attribute("issue_count", issue_count)
span.set_attribute("module_count", module_count)
span.set_attribute("cycle_count", cycle_count)
span.set_attribute("cycle_issue_count", cycle_issue_count)
span.set_attribute("module_issue_count", module_issue_count)
span.set_attribute("page_count", page_count)
# Workspace details
for workspace in Workspace.objects.all():
# Count of all models
project_count = Project.objects.filter(workspace=workspace).count()
issue_count = Issue.objects.filter(workspace=workspace).count()
module_count = Module.objects.filter(workspace=workspace).count()
cycle_count = Cycle.objects.filter(workspace=workspace).count()
cycle_issue_count = CycleIssue.objects.filter(workspace=workspace).count()
module_issue_count = ModuleIssue.objects.filter(workspace=workspace).count()
page_count = Page.objects.filter(workspace=workspace).count()
member_count = WorkspaceMember.objects.filter(workspace=workspace).count()
# Set span attributes
with tracer.start_as_current_span("workspace_details") as span:
span.set_attribute("instance_id", instance.instance_id)
span.set_attribute("workspace_id", str(workspace.id))
span.set_attribute("workspace_slug", workspace.slug)
span.set_attribute("project_count", project_count)
span.set_attribute("issue_count", issue_count)
span.set_attribute("module_count", module_count)
span.set_attribute("cycle_count", cycle_count)
span.set_attribute("cycle_issue_count", cycle_issue_count)
span.set_attribute("module_issue_count", module_issue_count)
span.set_attribute("page_count", page_count)
span.set_attribute("member_count", member_count)
return
finally:
# Shutdown the tracer
shutdown_tracer()
apps/api/plane/license/management/commands/register_instance.py
+3 -3
View File
@@ -15,7 +15,7 @@ from django.utils import timezone
# Module imports
from plane.license.models import Instance, InstanceEdition
from plane.license.bgtasks.tracer import instance_traces
from plane.license.bgtasks.telemetry_metrics import push_instance_metrics
class Command(BaseCommand):
@@ -86,7 +86,7 @@ class Command(BaseCommand):
instance.edition = InstanceEdition.PLANE_COMMUNITY.value
instance.save()
# Call the instance traces task
instance_traces.delay()
# Push instance metrics on registration
push_instance_metrics.delay()
return
apps/api/plane/settings/common.py
+1 -1
View File
@@ -321,7 +321,7 @@ CELERY_IMPORTS = (
"plane.bgtasks.file_asset_task",
"plane.bgtasks.email_notification_task",
"plane.bgtasks.cleanup_task",
"plane.license.bgtasks.tracer",
"plane.license.bgtasks.telemetry_metrics",
# management tasks
"plane.bgtasks.dummy_data_task",
# issue version tasks
apps/api/plane/utils/otlp_endpoints.py
+59
View File
@@ -0,0 +1,59 @@
# Copyright (c) 2023-present Plane Software, Inc. and contributors
# SPDX-License-Identifier: AGPL-3.0-only
# See the LICENSE file for details.
"""
Shared OTLP endpoint helpers so metrics and traces use the same collector
when both are enabled. One URL (OTLP_ENDPOINT) is enough: same as traces
(e.g. https://telemetry.plane.so or https://telemetry.plane.town behind
nginx ingress with gRPC backend).
"""
import os
from urllib.parse import urlparse
# When no port in URL: https -> 443 (ingress), http -> 4317 (OTLP gRPC default)
OTLP_GRPC_DEFAULT_PORT = "4317"
HTTPS_DEFAULT_PORT = "443"
_DEFAULT_OTLP_ENDPOINT = "https://telemetry.plane.so"
def grpc_endpoint_from_url(url: str) -> str:
"""
Derive gRPC host:port from OTLP_ENDPOINT URL.
- https://telemetry.plane.so -> telemetry.plane.so:443 (nginx ingress)
- https://telemetry.plane.town -> telemetry.plane.town:443 (dev)
- telemetry.plane.so:4317 -> telemetry.plane.so:4317 (scheme-less with port)
- telemetry.plane.so -> telemetry.plane.so:4317 (scheme-less, default gRPC port)
- Explicit port in URL is always preserved.
"""
# urlparse needs a scheme to correctly populate hostname/netloc.
# Scheme-less values like "host:port" are misread as scheme="host", path="port".
if "://" not in url:
url = "//" + url
parsed = urlparse(url)
host = parsed.hostname or "telemetry.plane.so"
if parsed.port is not None:
port = str(parsed.port)
elif parsed.scheme == "https":
port = HTTPS_DEFAULT_PORT
else:
port = OTLP_GRPC_DEFAULT_PORT
return f"{host}:{port}"
def get_otlp_grpc_endpoint() -> str:
"""
Return the gRPC endpoint (host:port) for OTLP traces and metrics.
Derived from OTLP_ENDPOINT so the same URL works for both (e.g. collector
behind nginx ingress with gRPC backend on 443).
"""
base = os.environ.get("OTLP_ENDPOINT", _DEFAULT_OTLP_ENDPOINT)
return grpc_endpoint_from_url(base)
def get_otlp_http_metrics_url() -> str:
"""Return the HTTP URL for OTLP metrics (OTLP_ENDPOINT + /v1/metrics)."""
base = os.environ.get("OTLP_ENDPOINT", _DEFAULT_OTLP_ENDPOINT)
return f"{base.rstrip('/')}/v1/metrics"
apps/api/plane/utils/telemetry.py
-62
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@@ -1,62 +0,0 @@
# Copyright (c) 2023-present Plane Software, Inc. and contributors
# SPDX-License-Identifier: AGPL-3.0-only
# See the LICENSE file for details.
# Python imports
import os
import atexit
# Third party imports
from opentelemetry import trace
from opentelemetry.sdk.trace import TracerProvider
from opentelemetry.sdk.trace.export import BatchSpanProcessor
from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter
from opentelemetry.sdk.resources import Resource
from opentelemetry.instrumentation.django import DjangoInstrumentor
# Global variable to track initialization
_TRACER_PROVIDER = None
def init_tracer():
"""Initialize OpenTelemetry with proper shutdown handling"""
global _TRACER_PROVIDER
# If already initialized, return existing provider
if _TRACER_PROVIDER is not None:
return _TRACER_PROVIDER
# Configure the tracer provider
service_name = os.environ.get("SERVICE_NAME", "plane-ce-api")
resource = Resource.create({"service.name": service_name})
tracer_provider = TracerProvider(resource=resource)
# Set as global tracer provider
trace.set_tracer_provider(tracer_provider)
# Configure the OTLP exporter
otel_endpoint = os.environ.get("OTLP_ENDPOINT", "https://telemetry.plane.so")
otlp_exporter = OTLPSpanExporter(endpoint=otel_endpoint)
span_processor = BatchSpanProcessor(otlp_exporter)
tracer_provider.add_span_processor(span_processor)
# Initialize Django instrumentation
DjangoInstrumentor().instrument()
# Store provider globally
_TRACER_PROVIDER = tracer_provider
# Register shutdown handler
atexit.register(shutdown_tracer)
return tracer_provider
def shutdown_tracer():
"""Shutdown OpenTelemetry tracers and processors"""
global _TRACER_PROVIDER
if _TRACER_PROVIDER is not None:
if hasattr(_TRACER_PROVIDER, "shutdown"):
_TRACER_PROVIDER.shutdown()
_TRACER_PROVIDER = None
apps/api/requirements/base.txt
+1
View File
@@ -67,6 +67,7 @@ opentelemetry-api==1.28.1
opentelemetry-sdk==1.28.1
opentelemetry-instrumentation-django==0.49b1
opentelemetry-exporter-otlp==1.28.1
opentelemetry-exporter-otlp-proto-grpc==1.28.1
# OpenAPI Specification
drf-spectacular==0.28.0
# html sanitizer