Docker and InfluxDB 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.
See Ways to Get Started
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.
The InfluxDB plugin writes metrics to the InfluxDB HTTP or UDP service. It provides options to configure how metrics are sent and stored in the database.
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.
InfluxDB
This plugin supports writing metrics to InfluxDB over HTTP or UDP. It also includes options for authentication using usernames and passwords, as well as various configurations for timeouts, database management, and writing metrics.
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
InfluxDB
[[outputs.influxdb]]
## The full HTTP or UDP URL for your InfluxDB instance.
##
## Multiple URLs can be specified for a single cluster, only ONE of the
## urls will be written to each interval.
# urls = ["unix:///var/run/influxdb.sock"]
# urls = ["udp://127.0.0.1:8089"]
# urls = ["http://127.0.0.1:8086"]
## Local address to bind when connecting to the server
## If empty or not set, the local address is automatically chosen.
# local_address = ""
## The target database for metrics; will be created as needed.
## For UDP url endpoint database needs to be configured on server side.
# database = "telegraf"
## The value of this tag will be used to determine the database. If this
## tag is not set the 'database' option is used as the default.
# database_tag = ""
## If true, the 'database_tag' will not be included in the written metric.
# exclude_database_tag = false
## If true, no CREATE DATABASE queries will be sent. Set to true when using
## Telegraf with a user without permissions to create databases or when the
## database already exists.
# skip_database_creation = false
## Name of existing retention policy to write to. Empty string writes to
## the default retention policy. Only takes effect when using HTTP.
# retention_policy = ""
## The value of this tag will be used to determine the retention policy. If this
## tag is not set the 'retention_policy' option is used as the default.
# retention_policy_tag = ""
## If true, the 'retention_policy_tag' will not be included in the written metric.
# exclude_retention_policy_tag = false
## Write consistency (clusters only), can be: "any", "one", "quorum", "all".
## Only takes effect when using HTTP.
# write_consistency = "any"
## Timeout for HTTP messages.
# timeout = "5s"
## HTTP Basic Auth
# username = "telegraf"
# password = "metricsmetricsmetricsmetrics"
## HTTP User-Agent
# user_agent = "telegraf"
## UDP payload size is the maximum packet size to send.
# udp_payload = "512B"
## Optional TLS Config for use on HTTP connections.
# 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
## HTTP Proxy override, if unset values the standard proxy environment
## variables are consulted to determine which proxy, if any, should be used.
# http_proxy = "http://corporate.proxy:3128"
## Additional HTTP headers
# http_headers = {"X-Special-Header" = "Special-Value"}
## HTTP Content-Encoding for write request body, can be set to "gzip" to
## compress body or "identity" to apply no encoding.
# content_encoding = "gzip"
## When true, Telegraf will output unsigned integers as unsigned values,
## i.e.: "42u". You will need a version of InfluxDB supporting unsigned
## integer values. Enabling this option will result in field type errors if
## existing data has been written.
# influx_uint_support = false
## When true, Telegraf will omit the timestamp on data to allow InfluxDB
## to set the timestamp of the data during ingestion. This is generally NOT
## what you want as it can lead to data points captured at different times
## getting omitted due to similar data.
# influx_omit_timestamp = false
Input and output integration examples
Docker
-
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.
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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.
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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.
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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.
InfluxDB
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Metric Aggregation: Use the InfluxDB output plugin to aggregate metrics from various sources, such as system performance data, and send it to InfluxDB for centralized monitoring and analysis.
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Real-Time Data Ingestion: Set up the plugin to send real-time data from your application to InfluxDB, enabling your development team to dynamically monitor performance and user analytics.
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Multi-Tenancy Support: You can configure multiple [[outputs.influxdb]] sections to send data from different applications to separate InfluxDB instances, effectively supporting multi-tenancy in your monitoring architecture.
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
Related Integrations
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