Apache Zookeeper and SigNoz Integration
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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
The Zookeeper Telegraf plugin collects and reports metrics from Zookeeper servers, facilitating monitoring and performance analysis. It utilizes the ‘mntr’ command output to gather essential statistics critical for maintaining Zookeeper’s operational health.
This configuration turns any Telegraf agent into a Remote Write publisher for SigNoz, streaming rich metrics straight into the SigNoz backend with a single URL change.
Integration details
Apache Zookeeper
The Zookeeper plugin for Telegraf is designed to collect vital statistics from Zookeeper servers by executing the ‘mntr’ command. This plugin serves as a monitoring tool that captures important metrics related to Zookeeper’s performance, including connection details, latency, and various operational statistics, facilitating the assessment of the health and efficiency of Zookeeper deployments. In contrast to the Prometheus input plugin, which is recommended when the Prometheus metrics provider is enabled, the Zookeeper plugin accesses raw output from the ‘mntr’ command, rendering it tailored for configurations that do not adopt Prometheus for metrics reporting. This unique approach allows administrators to gather Java Properties formatted metrics directly from Zookeeper, ensuring comprehensive visibility into Zookeeper’s operational state and enabling timely responses to performance anomalies. It specifically excels in environments where Zookeeper operates as a centralized service for maintaining configuration information and names for distributed systems, thus providing immeasurable insights essential for troubleshooting and capacity planning.
SigNoz
SigNoz is an open source observability platform that stores metrics, traces, and logs. When you deploy SigNoz, its signoz-otel-collector-metrics service exposes a Prometheus Remote Write receiver (default :13133/api/v1/write). By configuring Telegraf’s Prometheus plugin to point at this endpoint, you can push any Telegraf collected metrics, SNMP counters, cloud services, or business KPIs—directly into SigNoz. The plugin natively serializes metrics in the Remote Write protobuf format, supports external labels, metadata export, retries, and TLS or bearer-token auth, so it fits zero-trust and multi-tenant SigNoz clusters. Inside SigNoz, the data lands in ClickHouse tables that back Metrics Explorer, alert rules, and unified dashboards. This approach lets organizations unify Prometheus and OTLP pipelines, enables long-term retention powered by ClickHouse compression, and avoids vendor lock-in while retaining PromQL-style queries.
Configuration
Apache Zookeeper
[[inputs.zookeeper]]
## An array of address to gather stats about. Specify an ip or hostname
## with port. ie localhost:2181, 10.0.0.1:2181, etc.
## If no servers are specified, then localhost is used as the host.
## If no port is specified, 2181 is used
servers = [":2181"]
## Timeout for metric collections from all servers. Minimum timeout is "1s".
# timeout = "5s"
## Float Parsing - the initial implementation forced any value unable to be
## parsed as an int to be a string. Setting this to "float" will attempt to
## parse float values as floats and not strings. This would break existing
## metrics and may cause issues if a value switches between a float and int.
# parse_floats = "string"
## Optional TLS Config
# enable_tls = false
# tls_ca = "/etc/telegraf/ca.pem"
# tls_cert = "/etc/telegraf/cert.pem"
# tls_key = "/etc/telegraf/key.pem"
## If false, skip chain & host verification
# insecure_skip_verify = true
SigNoz
[[outputs.prometheusremotewrite]]
## SigNoz OTEL-Collector metrics endpoint (Prometheus Remote Write receiver)
## Default port is 13133 when you install SigNoz with the Helm chart
url = "http://signoz-otel-collector-metrics.monitoring.svc.cluster.local:13133/api/v1/write"
## Add identifying labels so you can slice & dice the data later
external_labels = { host = "${HOSTNAME}", agent = "telegraf" }
## Forward host metadata for richer dashboards (SigNoz maps these to ClickHouse columns)
send_metadata = true
## ----- Authentication (comment out what you don’t need) -----
# bearer_token = "$SIGNOZ_TOKEN" # SaaS tenant token
# basic_username = "signoz" # Basic auth (self-hosted)
# basic_password = "secret"
## ----- TLS options (for SaaS or HTTPS self-hosted) -----
# tls_ca = "/etc/ssl/certs/ca.crt"
# tls_cert = "/etc/telegraf/certs/telegraf.crt"
# tls_key = "/etc/telegraf/certs/telegraf.key"
# insecure_skip_verify = false
## ----- Performance tuning -----
max_batch_size = 10000 # samples per POST
timeout = "10s"
retry_max = 3
Input and output integration examples
Apache Zookeeper
-
Cluster Health Monitoring: Integrate the Zookeeper plugin to monitor the health and performance of a distributed application relying on Zookeeper for configuration management and service discovery. By tracking metrics such as session count, latency, and data size, DevOps teams can identify potential issues before they escalate, ensuring high availability and reliability across applications.
-
Performance Benchmarks: Utilize the plugin to benchmark Zookeeper performance in varying workload scenarios. This not only helps in understanding how Zookeeper behaves under load but also assists in tuning configurations to optimize throughput and reduce latency during peak operations.
-
Alerting for Anomalies: Combine this plugin with alerting tools to create a proactive monitoring system that notifies engineers if specific Zookeeper metrics exceed threshold limits, such as open file descriptor counts or high latency values. This enables teams to respond promptly to issues that could impact service reliability.
-
Historical Data Analysis: Store the metrics collected by the Zookeeper plugin in a time-series database to analyze historical performance trends. This allows teams to evaluate the impact of changes over time, assess the effectiveness of scaling actions, and plan for future capacity needs.
SigNoz
-
Multi-Cluster Federated Monitoring: Drop a Telegraf DaemonSet into each Kubernetes cluster, tag metrics with
cluster=<name>
, and Remote Write them to a central SigNoz instance. Ops teams get a single PromQL window across prod, staging, and edge clusters without running Thanos sidecars. -
Factory-Floor Edge Gateway: A rugged Intel NUC on the shop floor runs Telegraf to scrape Modbus PLCs and environmental sensors. It batches readings every 5 seconds and pushes them over an intermittent 4G link to SigNoz SaaS. ClickHouse compression keeps costs low while AI-based outlier detection in SigNoz flags overheating motors before failure.
-
SaaS Usage Metering: Telegraf runs alongside each micro-service, exporting per-tenant counters (
api_calls
,gigabytes_processed
). Remote Write streams the data to SigNoz where a scheduled ClickHouse materialized view aggregates usage for monthly billing—no separate metering stack required. -
Autoscaling Feedback Loop: Combine Telegraf’s Kubernetes input with the Remote Write output to publish granular pod CPU and queue-length metrics into SigNoz. A custom SigNoz alert fires when P95 latency breaches 200 ms and a GitOps controller reads that alert to trigger a HorizontalPodAutoscaler tweak—closing the loop between observability and automation.
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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