Docker and SigNoz Integration

Input and output integration overview

The Docker input plugin allows you to collect metrics from your Docker containers using the Docker Engine API, facilitating enhanced visibility and monitoring of containerized applications.

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

Docker

The Docker input plugin for Telegraf gathers valuable metrics from the Docker Engine API, providing insights into running containers. This plugin utilizes the Official Docker Client to interface with the Engine API, allowing users to monitor various container states, resource allocations, and performance metrics. With options for filtering containers by names and states, along with customizable tags and labels, this plugin supports flexibility in monitoring containerized applications in diverse environments, whether on local systems or within orchestration platforms like Kubernetes. Additionally, it addresses security considerations by requiring permissions for accessing Docker’s daemon and emphasizes proper configuration when deploying within containerized environments.

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

Docker

[[inputs.docker]]
  ## Docker Endpoint
  ##   To use TCP, set endpoint = "tcp://[ip]:[port]"
  ##   To use environment variables (ie, docker-machine), set endpoint = "ENV"
  endpoint = "unix:///var/run/docker.sock"

  ## Set to true to collect Swarm metrics(desired_replicas, running_replicas)
  ## Note: configure this in one of the manager nodes in a Swarm cluster.
  ## configuring in multiple Swarm managers results in duplication of metrics.
  gather_services = false

  ## Only collect metrics for these containers. Values will be appended to
  ## container_name_include.
  ## Deprecated (1.4.0), use container_name_include
  container_names = []

  ## Set the source tag for the metrics to the container ID hostname, eg first 12 chars
  source_tag = false

  ## Containers to include and exclude. Collect all if empty. Globs accepted.
  container_name_include = []
  container_name_exclude = []

  ## Container states to include and exclude. Globs accepted.
  ## When empty only containers in the "running" state will be captured.
  # container_state_include = []
  # container_state_exclude = []

  ## Objects to include for disk usage query
  ## Allowed values are "container", "image", "volume" 
  ## When empty disk usage is excluded
  storage_objects = []

  ## Timeout for docker list, info, and stats commands
  timeout = "5s"

  ## Whether to report for each container per-device blkio (8:0, 8:1...),
  ## network (eth0, eth1, ...) and cpu (cpu0, cpu1, ...) stats or not.
  ## Usage of this setting is discouraged since it will be deprecated in favor of 'perdevice_include'.
  ## Default value is 'true' for backwards compatibility, please set it to 'false' so that 'perdevice_include' setting
  ## is honored.
  perdevice = true

  ## Specifies for which classes a per-device metric should be issued
  ## Possible values are 'cpu' (cpu0, cpu1, ...), 'blkio' (8:0, 8:1, ...) and 'network' (eth0, eth1, ...)
  ## Please note that this setting has no effect if 'perdevice' is set to 'true'
  # perdevice_include = ["cpu"]

  ## Whether to report for each container total blkio and network stats or not.
  ## Usage of this setting is discouraged since it will be deprecated in favor of 'total_include'.
  ## Default value is 'false' for backwards compatibility, please set it to 'true' so that 'total_include' setting
  ## is honored.
  total = false

  ## Specifies for which classes a total metric should be issued. Total is an aggregated of the 'perdevice' values.
  ## Possible values are 'cpu', 'blkio' and 'network'
  ## Total 'cpu' is reported directly by Docker daemon, and 'network' and 'blkio' totals are aggregated by this plugin.
  ## Please note that this setting has no effect if 'total' is set to 'false'
  # total_include = ["cpu", "blkio", "network"]

  ## docker labels to include and exclude as tags.  Globs accepted.
  ## Note that an empty array for both will include all labels as tags
  docker_label_include = []
  docker_label_exclude = []

  ## Which environment variables should we use as a tag
  tag_env = ["JAVA_HOME", "HEAP_SIZE"]

  ## 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

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

Docker

1. Monitoring the Performance of Containerized Applications: Use the Docker input plugin in order to track the CPU, memory, disk I/O, and network activity of applications running in Docker containers. By collecting these metrics, DevOps teams can proactively manage resource allocation, troubleshoot performance bottlenecks, and ensure optimal application performance across different environments.

2. Integrating with Kubernetes: Leverage this plugin to gather metrics from Docker containers orchestrated by Kubernetes. By filtering out unnecessary Kubernetes labels and focusing on key metrics, teams can streamline their monitoring solutions and create dashboards that provide insights into the overall health of microservices running within the Kubernetes cluster.

3. Capacity Planning and Resource Optimization: Use the metrics collected by the Docker input plugin to perform capacity planning for Docker deployments. Analyzing usage patterns helps identify underutilized resources and over-provisioned containers, guiding decisions on scaling up or down based on actual usage trends.

4. Automated Alerting for Container Anomalies: Set up alerting rules based on the metrics collected through the Docker plugin to notify teams of unusual spikes in resource usage or service disruptions. This proactive monitoring approach helps maintain service reliability and optimize the performance of containerized applications.

SigNoz

1. 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.

2. 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.

3. 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.

4. 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

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