Apache and OpenObserve Integration
Powerful performance with an easy integration, powered by Telegraf, the open source data connector built by InfluxData.
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Table of Contents
Powerful Performance, Limitless Scale
Collect, organize, and act on massive volumes of high-velocity data. Any data is more valuable when you think of it as time series data. with InfluxDB, the #1 time series platform built to scale with Telegraf.
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Input and output integration overview
This plugin interfaces with the Apache HTTP Server’s mod_status to gather and report performance metrics from the server.
This configuration pairs Telegraf’s HTTP output with OpenObserve’s native JSON ingestion API, turning any Telegraf agent into a first-class OpenObserve collector.
Integration details
Apache
The Apache plugin collects server performance information using the mod_status module of the Apache HTTP Server. It relies on the mod_status feature, which must be explicitly enabled in the Apache configuration to access a machine-readable status page. This plugin allows users to fetch several metrics related to Apache’s operational performance, including worker status, connection statistics, and server load, thereby facilitating effective monitoring and troubleshooting of web server performance in real-time.
OpenObserve
OpenObserve is an open source observability platform written in Rust that stores data cost-effectively on object storage or local disk. It exposes REST endpoints such as /api/{org}/ingest/metrics/_json
that accept batched metric documents conforming to a concise JSON schema, making it an attractive drop-in replacement for Loki or Elasticsearch stacks. The Telegraf HTTP output plugin streams metrics to arbitrary HTTP targets; when the "data_format = "json"" serializer is selected, Telegraf batches its metric objects into a payload that matches OpenObserve’s ingestion contract. The plugin supports configurable batch size, custom headers, TLS, and compression, allowing operators to authenticate with Basic or Bearer tokens and to enforce back-pressure without additional collectors. By reusing existing Telegraf agents already collecting system, application, or SNMP data, organizations can funnel rich telemetry into OpenObserve dashboards and SQL-like analytics with minimal overhead, enabling unified observability, long-term retention, and real-time alerting without vendor lock-in.
Configuration
Apache
[[inputs.apache]]
## An array of URLs to gather from, must be directed at the machine
## readable version of the mod_status page including the auto query string.
## Default is "http://localhost/server-status?auto".
urls = ["http://localhost/server-status?auto"]
## Credentials for basic HTTP authentication.
# username = "myuser"
# password = "mypassword"
## Maximum time to receive response.
# response_timeout = "5s"
## Optional TLS Config
# tls_ca = "/etc/telegraf/ca.pem"
# tls_cert = "/etc/telegraf/cert.pem"
# tls_key = "/etc/telegraf/key.pem"
## Use TLS but skip chain & host verification
# insecure_skip_verify = false
OpenObserve
[[outputs.http]]
## OpenObserve JSON metrics ingestion endpoint
url = "https://api.openobserve.ai/api/default/ingest/metrics/_json"
## Use POST to push batches
method = "POST"
## Basic auth header (base64 encoded "username:password")
headers = { Authorization = "Basic dXNlcjpwYXNzd29yZA==" }
## Timeout for HTTP requests
timeout = "10s"
## Override Content-Type to match OpenObserve expectation
content_type = "application/json"
## Force Telegraf to batch and serialize metrics as JSON
data_format = "json"
## JSON serializer specific options
json_timestamp_units = "1ms"
## Uncomment to restrict batch size
# batch_size = 5000
Input and output integration examples
Apache
-
Real-Time Performance Monitoring: Use the Apache input plugin to set up a real-time dashboard displaying critical performance metrics of your Apache server. By visualizing metrics such as BusyWorkers, and Load averages, you can quickly identify performance bottlenecks and server health issues, aiding in proactive management of web traffic loads.
-
Automated Alerting for Server Issues: Implement alerts based on metrics collected by this plugin to notify administrators in case of performance degradation. For instance, if the
BusyWorkers
metric exceeds a certain threshold, automatic alerts can be triggered, ensuring prompt incident response to maintain uptime and service reliability. -
Historical Performance Analysis: Combine data collected by the Apache plugin with long-term storage solutions to track performance trends over time. This accumulated data helps in understanding usage patterns, forecasting resource needs, and making informed decisions regarding server scaling or optimization.
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Cross-System Monitoring: Integrate metrics gathered from Apache alongside metrics from other components of your web stack using Telegraf’s capabilities to send data to a centralized monitoring solution. This holistic view can simplify troubleshooting and coordination between different technologies, ensuring optimal system performance across the board.
OpenObserve
-
Edge Device Health Mirror: Deploy Telegraf on thousands of industrial IoT devices to capture temperature, vibration, and power metrics, then use this output to push JSON batches to OpenObserve. Plant operators gain a real-time overview of machine health and can trigger maintenance based on anomalies without relying on heavyweight collectors.
-
Blue-Green Deployment Canary: Attach a lightweight Telegraf sidecar to each Kubernetes release-candidate pod that scrapes /metrics and forwards container stats to a dedicated “canary” stream in OpenObserve. Continuous comparison of error rates between blue and green versions empowers the CI pipeline to auto-roll back poor performers within seconds.
-
Multi-Tenant SaaS Billing Pipeline: Emit per-customer usage counters via Telegraf and tag them with
tenant_id
; the HTTP plugin posts them to OpenObserve where SQL reports aggregate usage into invoices, eliminating separate metering services and simplifying compliance audits. -
Security Threat Scoring: Fuse Suricata events and host resource metrics in Telegraf, deliver them to OpenObserve’s analytics engine, and run stream-processing rules that correlate spikes in suspicious traffic with CPU saturation to produce an actionable threat score and automatically open tickets in a SOAR platform.
Feedback
Thank you for being part of our community! If you have any general feedback or found any bugs on these pages, we welcome and encourage your input. Please submit your feedback in the InfluxDB community Slack.
Powerful Performance, Limitless Scale
Collect, organize, and act on massive volumes of high-velocity data. Any data is more valuable when you think of it as time series data. with InfluxDB, the #1 time series platform built to scale with Telegraf.
See Ways to Get Started
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