plone.observability

Kubernetes-style health probes and pluggable metrics for Plone.

Features

• Liveness, readiness, and startup probes on a separate HTTP port
• Pluggable metrics endpoint (@@metrics) with Prometheus and JSON output
• Extensible via ZCA: custom health checks, metric providers, and formatters

Installation

Add plone.observability to your package dependencies:

[project]
dependencies = [
    "plone.observability",
]

Then include it in your ZCML:

<include package="plone.observability" />

The package registers itself and starts the health server automatically when Zope starts via a IProcessStarting subscriber.

Configuration

All configuration is done via environment variables.

Variable	Default	Description
PLONE_OBSERVABILITY_HEALTH_HOST	0.0.0.0	Bind address for the health probe server
PLONE_OBSERVABILITY_HEALTH_PORT	8081	Port for the health probe server. Set to 0 to disable.
PLONE_OBSERVABILITY_METRICS_ALLOWLIST	(empty, open)	Comma-separated CIDRs allowed to access @@metrics. Empty means all IPs are allowed.
PLONE_OBSERVABILITY_TRUSTED_PROXIES	127.0.0.1,::1	Comma-separated CIDRs of trusted reverse proxies for X-Forwarded-For resolution.
PLONE_OBSERVABILITY_METRICS_CACHE_TTL	60	Seconds to cache content catalog metrics (expensive to collect).

Health Probes

The health server runs on a dedicated port (default 8081) in a background daemon thread, separate from the Zope WSGI server. This means it answers even when all Zope threads are busy.

Endpoints

Path	Purpose
/live	Liveness check — is the process alive?
/ready	Readiness check — can the process serve requests?
/startup	Startup check — has the process finished initializing?

All endpoints return JSON with a 200 on success or 503 on failure:

{
  "status": "ok",
  "checks": {
    "zodb": {"ok": true, "message": "ZODB connection ok"}
  }
}

Kubernetes Integration

livenessProbe:
  httpGet:
    path: /live
    port: 8081
  initialDelaySeconds: 10
  periodSeconds: 30
  failureThreshold: 3

readinessProbe:
  httpGet:
    path: /ready
    port: 8081
  initialDelaySeconds: 5
  periodSeconds: 10
  failureThreshold: 3

startupProbe:
  httpGet:
    path: /startup
    port: 8081
  failureThreshold: 30
  periodSeconds: 10

Expose the probe port alongside the main Zope port:

ports:
  - name: http
    containerPort: 8080
  - name: health
    containerPort: 8081

Metrics

The @@metrics endpoint is a browser view registered on the application root (OFS.interfaces.IApplication). It collects metrics from all registered IMetricProvider adapters and serialises them using an IMetricFormatter utility.

Accessing the endpoint

http://your-plone-host/@@metrics
http://your-plone-host/@@metrics?format=json

The default format is Prometheus text. Pass ?format=json or an Accept: application/json header to get JSON.

Built-in metrics

Metric	Type	Scope	Description
plone_uptime_seconds	gauge	instance	Process uptime
plone_info	info	instance	Python, Zope, and Plone version labels
plone_threads_active	gauge	instance	Active Python threads
plone_process_rss_bytes	gauge	instance	Resident set size
plone_process_cpu_seconds	counter	instance	Total CPU time (user + system)
plone_requests_total	counter	instance	Total HTTP requests served
plone_request_duration_seconds_sum	counter	instance	Cumulative request duration
plone_request_duration_seconds_bucket	counter	instance	Request duration histogram buckets
plone_request_errors	counter	instance	HTTP errors by status code
plone_zodb_object_count	gauge	global	Total objects in ZODB
plone_zodb_db_size_bytes	gauge	global	ZODB file size
plone_zodb_connections	gauge	instance	Open ZODB connections
plone_zodb_cache_size	gauge	instance	Objects in the ZODB object cache
plone_zodb_cache_size_bytes	gauge	instance	ZODB object cache size in bytes
plone_content_total	gauge	global	Content objects by portal type and site
plone_content_by_state	gauge	global	Content objects by workflow state and site

Metric scope

Metrics carry a scope label with value "global" or "instance".

• global — the value is the same across all Plone instances sharing the same ZODB (e.g. object count, content totals). When aggregating in Prometheus, avoid double-counting by filtering to a single instance.
• instance — the value is specific to this process (e.g. request counts, RSS). Sum across instances when aggregating.

Prometheus scrape configuration

scrape_configs:
  - job_name: plone
    static_configs:
      - targets: ["plone-host:8080"]
    metrics_path: /@@metrics

PromQL examples

Total requests across all instances:

sum(plone_requests_total{job="plone"})

Request rate per instance (5-minute window):

rate(plone_requests_total{job="plone"}[5m])

ZODB object count (global metric — pick one instance to avoid double-counting):

plone_zodb_object_count{scope="global"} * on(instance) group_left()
  (plone_info{instance=~"plone-0.*"})

Or simply query a single instance:

plone_zodb_object_count{instance="plone-0:8080", scope="global"}

Average request duration (p50 approximation from histogram):

histogram_quantile(0.5,
  sum(rate(plone_request_duration_seconds_bucket[5m])) by (le, instance)
)

Memory usage per instance (MB):

plone_process_rss_bytes{job="plone"} / 1024 / 1024

WSGI Middleware for Request Metrics

The plone_requests_total and plone_request_duration_seconds_* metrics are populated by the ObservabilityMiddleware WSGI middleware. You must add it to your WSGI pipeline to get request metrics.

Using PasteDeploy (pipeline.ini)

[pipeline:main]
pipeline =
    egg:plone.observability#observability
    ...
    Zope

[filter:observability]
use = egg:plone.observability#observability

Manual WSGI wrapping

from plone.observability.metrics.providers.request import ObservabilityMiddleware

application = ObservabilityMiddleware(application)

Extensibility

All components are registered via ZCA and can be extended or replaced by third-party packages.

Custom liveness check

Implement ILivenessCheck and register it as a named utility. Liveness checks MUST NOT access ZODB or block.

from zope.interface import implementer
from plone.observability.interfaces import ILivenessCheck

@implementer(ILivenessCheck)
class MyLivenessCheck:
    name = "myapp"

    def __call__(self):
        # Return (ok: bool, message: str)
        return True, "all good"

<utility
    factory=".checks.MyLivenessCheck"
    provides="plone.observability.interfaces.ILivenessCheck"
    name="myapp"
    />

Custom readiness check

Implement IReadinessCheck. Readiness checks may access ZODB.

from zope.interface import implementer
from plone.observability.interfaces import IReadinessCheck

@implementer(IReadinessCheck)
class MyReadinessCheck:
    name = "myapp"

    def __call__(self):
        # Check a dependency
        ok = _check_external_service()
        return ok, "service ok" if ok else "service unavailable"

<utility
    factory=".checks.MyReadinessCheck"
    provides="plone.observability.interfaces.IReadinessCheck"
    name="myapp"
    />

Custom metric provider

Implement IMetricProvider as an adapter on OFS.interfaces.IApplication.

from zope.interface import implementer
from plone.observability.interfaces import IMetricProvider
from plone.observability.metric import Metric

@implementer(IMetricProvider)
class MyMetricProvider:
    name = "myapp"
    scope = "instance"

    def __init__(self, context):
        self.context = context

    def collect(self):
        yield Metric(
            name="myapp_queue_length",
            value=get_queue_length(),
            type="gauge",
            scope="instance",
            help="Number of items in the processing queue",
        )

<adapter
    factory=".metrics.MyMetricProvider"
    provides="plone.observability.interfaces.IMetricProvider"
    for="OFS.interfaces.IApplication"
    name="myapp"
    />

Custom metric formatter

Implement IMetricFormatter as a named utility to support additional wire formats.

from zope.interface import implementer
from plone.observability.interfaces import IMetricFormatter

@implementer(IMetricFormatter)
class CSVFormatter:
    content_type = "text/csv"

    def format(self, metrics):
        lines = ["name,value,type,scope,help"]
        for m in metrics:
            lines.append(f"{m.name},{m.value},{m.type},{m.scope},{m.help}")
        return "\n".join(lines)

<utility
    factory=".formatters.CSVFormatter"
    provides="plone.observability.interfaces.IMetricFormatter"
    name="csv"
    />

Access it via @@metrics?format=csv.