snapshot of https://github.com/makeplane/plane.git @ d868349a55de79979eb8b98701bf1702c67ad634 (2026-09-15)

apps/api/plane/license/bgtasks/telemetry_metrics.py

@@ -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}")