telegraf.conf

telegraf.conf

# Telegraf Configuration
#
# Telegraf is entirely plugin driven. All metrics are gathered from the
# declared inputs, and sent to the declared outputs.
#
# Plugins must be declared in here to be active.
# To deactivate a plugin, comment out the name and any variables.
#
# Use 'telegraf -config telegraf.conf -test' to see what metrics a config
# file would generate.
#
# Environment variables can be used anywhere in this config file, simply prepend
# them with $. For strings the variable must be within quotes (ie, "$STR_VAR"),
# for numbers and booleans they should be plain (ie, $INT_VAR, $BOOL_VAR)


# Global tags can be specified here in key="value" format.
[global_tags]
  # dc = "us-east-1" # will tag all metrics with dc=us-east-1
  # rack = "1a"
  ## Environment variables can be used as tags, and throughout the config file
  # user = "$USER"


# Configuration for telegraf agent
[agent]
  ## Default data collection interval for all inputs
  interval = "10s"
  ## Rounds collection interval to 'interval'
  ## ie, if interval="10s" then always collect on :00, :10, :20, etc.
  round_interval = true

  ## Telegraf will send metrics to outputs in batches of at most
  ## metric_batch_size metrics.
  ## This controls the size of writes that Telegraf sends to output plugins.
  metric_batch_size = 1000

  ## For failed writes, telegraf will cache metric_buffer_limit metrics for each
  ## output, and will flush this buffer on a successful write. Oldest metrics
  ## are dropped first when this buffer fills.
  ## This buffer only fills when writes fail to output plugin(s).
  metric_buffer_limit = 10000

  ## Collection jitter is used to jitter the collection by a random amount.
  ## Each plugin will sleep for a random time within jitter before collecting.
  ## This can be used to avoid many plugins querying things like sysfs at the
  ## same time, which can have a measurable effect on the system.
  collection_jitter = "0s"

  ## Default flushing interval for all outputs. Maximum flush_interval will be
  ## flush_interval + flush_jitter
  flush_interval = "10s"
  ## Jitter the flush interval by a random amount. This is primarily to avoid
  ## large write spikes for users running a large number of telegraf instances.
  ## ie, a jitter of 5s and interval 10s means flushes will happen every 10-15s
  flush_jitter = "0s"

  ## By default or when set to "0s", precision will be set to the same
  ## timestamp order as the collection interval, with the maximum being 1s.
  ##   ie, when interval = "10s", precision will be "1s"
  ##       when interval = "250ms", precision will be "1ms"
  ## Precision will NOT be used for service inputs. It is up to each individual
  ## service input to set the timestamp at the appropriate precision.
  ## Valid time units are "ns", "us" (or "µs"), "ms", "s".
  precision = ""

  ## Logging configuration:
  ## Run telegraf with debug log messages.
  debug = false
  ## Run telegraf in quiet mode (error log messages only).
  quiet = false
  ## Specify the log file name. The empty string means to log to stderr.
  logfile = ""

  ## Override default hostname, if empty use os.Hostname()
  hostname = ""
  ## If set to true, do no set the "host" tag in the telegraf agent.
  omit_hostname = false


###############################################################################
#                            OUTPUT PLUGINS                                   #
###############################################################################

# Configuration for sending metrics to 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"]

  ## The target database for metrics; will be created as needed.
  # database = "telegraf"

  ## 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 = ""

  ## 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 = 512

  ## 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 = "identity"

  ## 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



###############################################################################
#                            PROCESSOR PLUGINS                                #
###############################################################################

# # Convert values to another metric value type
# [[processors.converter]]
#   ## Tags to convert
#   ##
#   ## The table key determines the target type, and the array of key-values
#   ## select the keys to convert.  The array may contain globs.
#   ##   <target-type> = [<tag-key>...]
#   [processors.converter.tags]
#     string = []
#     integer = []
#     unsigned = []
#     boolean = []
#     float = []
#
#   ## Fields to convert
#   ##
#   ## The table key determines the target type, and the array of key-values
#   ## select the keys to convert.  The array may contain globs.
#   ##   <target-type> = [<field-key>...]
#   [processors.converter.fields]
#     tag = []
#     string = []
#     integer = []
#     unsigned = []
#     boolean = []
#     float = []


# # Map enum values according to given table.
# [[processors.enum]]
#   [[processors.enum.mapping]]
#     ## Name of the field to map
#     field = "status"
#
#     ## Destination field to be used for the mapped value.  By default the source
#     ## field is used, overwriting the original value.
#     # dest = "status_code"
#
#     ## Default value to be used for all values not contained in the mapping
#     ## table.  When unset, the unmodified value for the field will be used if no
#     ## match is found.
#     # default = 0
#
#     ## Table of mappings
#     [processors.enum.mapping.value_mappings]
#       green = 1
#       yellow = 2
#       red = 3


# # Apply metric modifications using override semantics.
# [[processors.override]]
#   ## All modifications on inputs and aggregators can be overridden:
#   # name_override = "new_name"
#   # name_prefix = "new_name_prefix"
#   # name_suffix = "new_name_suffix"
#
#   ## Tags to be added (all values must be strings)
#   # [processors.override.tags]
#   #   additional_tag = "tag_value"


# # Parse a value in a specified field/tag(s) and add the result in a new metric
# [[processors.parser]]
#   ## The name of the fields whose value will be parsed.
#   parse_fields = []
#
#   ## If true, incoming metrics are not emitted.
#   drop_original = false
#
#   ## If set to override, emitted metrics will be merged by overriding the
#   ## original metric using the newly parsed metrics.
#   merge = "override"
#
#   ## The dataformat to be read from files
#   ## Each data format has its own unique set of configuration options, read
#   ## more about them here:
#   ## https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md
#   data_format = "influx"


# # Print all metrics that pass through this filter.
# [[processors.printer]]


# # Transforms tag and field values with regex pattern
# [[processors.regex]]
#   ## Tag and field conversions defined in a separate sub-tables
#   # [[processors.regex.tags]]
#   #   ## Tag to change
#   #   key = "resp_code"
#   #   ## Regular expression to match on a tag value
#   #   pattern = "^(\\d)\\d\\d$"
#   #   ## Pattern for constructing a new value (${1} represents first subgroup)
#   #   replacement = "${1}xx"
#
#   # [[processors.regex.fields]]
#   #   key = "request"
#   #   ## All the power of the Go regular expressions available here
#   #   ## For example, named subgroups
#   #   pattern = "^/api(?P<method>/[\\w/]+)\\S*"
#   #   replacement = "${method}"
#   #   ## If result_key is present, a new field will be created
#   #   ## instead of changing existing field
#   #   result_key = "method"
#
#   ## Multiple conversions may be applied for one field sequentially
#   ## Let's extract one more value
#   # [[processors.regex.fields]]
#   #   key = "request"
#   #   pattern = ".*category=(\\w+).*"
#   #   replacement = "${1}"
#   #   result_key = "search_category"


# # Rename measurements, tags, and fields that pass through this filter.
# [[processors.rename]]


# # Perform string processing on tags, fields, and measurements
# [[processors.strings]]
#   ## Convert a tag value to uppercase
#   # [[processors.strings.uppercase]]
#   #   tag = "method"
#
#   ## Convert a field value to lowercase and store in a new field
#   # [[processors.strings.lowercase]]
#   #   field = "uri_stem"
#   #   dest = "uri_stem_normalised"
#
#   ## Trim leading and trailing whitespace using the default cutset
#   # [[processors.strings.trim]]
#   #   field = "message"
#
#   ## Trim leading characters in cutset
#   # [[processors.strings.trim_left]]
#   #   field = "message"
#   #   cutset = "\t"
#
#   ## Trim trailing characters in cutset
#   # [[processors.strings.trim_right]]
#   #   field = "message"
#   #   cutset = "\r\n"
#
#   ## Trim the given prefix from the field
#   # [[processors.strings.trim_prefix]]
#   #   field = "my_value"
#   #   prefix = "my_"
#
#   ## Trim the given suffix from the field
#   # [[processors.strings.trim_suffix]]
#   #   field = "read_count"
#   #   suffix = "_count"


# # Print all metrics that pass through this filter.
# [[processors.topk]]
#   ## How many seconds between aggregations
#   # period = 10
#
#   ## How many top metrics to return
#   # k = 10
#
#   ## Over which tags should the aggregation be done. Globs can be specified, in
#   ## which case any tag matching the glob will aggregated over. If set to an
#   ## empty list is no aggregation over tags is done
#   # group_by = ['*']
#
#   ## Over which fields are the top k are calculated
#   # fields = ["value"]
#
#   ## What aggregation to use. Options: sum, mean, min, max
#   # aggregation = "mean"
#
#   ## Instead of the top k largest metrics, return the bottom k lowest metrics
#   # bottomk = false
#
#   ## The plugin assigns each metric a GroupBy tag generated from its name and
#   ## tags. If this setting is different than "" the plugin will add a
#   ## tag (which name will be the value of this setting) to each metric with
#   ## the value of the calculated GroupBy tag. Useful for debugging
#   # add_groupby_tag = ""
#
#   ## These settings provide a way to know the position of each metric in
#   ## the top k. The 'add_rank_field' setting allows to specify for which
#   ## fields the position is required. If the list is non empty, then a field
#   ## will be added to each and every metric for each string present in this
#   ## setting. This field will contain the ranking of the group that
#   ## the metric belonged to when aggregated over that field.
#   ## The name of the field will be set to the name of the aggregation field,
#   ## suffixed with the string '_topk_rank'
#   # add_rank_fields = []
#
#   ## These settings provide a way to know what values the plugin is generating
#   ## when aggregating metrics. The 'add_agregate_field' setting allows to
#   ## specify for which fields the final aggregation value is required. If the
#   ## list is non empty, then a field will be added to each every metric for
#   ## each field present in this setting. This field will contain
#   ## the computed aggregation for the group that the metric belonged to when
#   ## aggregated over that field.
#   ## The name of the field will be set to the name of the aggregation field,
#   ## suffixed with the string '_topk_aggregate'
#   # add_aggregate_fields = []



###############################################################################
#                            AGGREGATOR PLUGINS                               #
###############################################################################

# # Keep the aggregate basicstats of each metric passing through.
# [[aggregators.basicstats]]
#   ## General Aggregator Arguments:
#   ## The period on which to flush & clear the aggregator.
#   period = "30s"
#   ## If true, the original metric will be dropped by the
#   ## aggregator and will not get sent to the output plugins.
#   drop_original = false


# # Create aggregate histograms.
# [[aggregators.histogram]]
#   ## The period in which to flush the aggregator.
#   period = "30s"
#
#   ## If true, the original metric will be dropped by the
#   ## aggregator and will not get sent to the output plugins.
#   drop_original = false
#
#   ## Example config that aggregates all fields of the metric.
#   # [[aggregators.histogram.config]]
#   #   ## The set of buckets.
#   #   buckets = [0.0, 15.6, 34.5, 49.1, 71.5, 80.5, 94.5, 100.0]
#   #   ## The name of metric.
#   #   measurement_name = "cpu"
#
#   ## Example config that aggregates only specific fields of the metric.
#   # [[aggregators.histogram.config]]
#   #   ## The set of buckets.
#   #   buckets = [0.0, 10.0, 20.0, 30.0, 40.0, 50.0, 60.0, 70.0, 80.0, 90.0, 100.0]
#   #   ## The name of metric.
#   #   measurement_name = "diskio"
#   #   ## The concrete fields of metric
#   #   fields = ["io_time", "read_time", "write_time"]


# # Keep the aggregate min/max of each metric passing through.
# [[aggregators.minmax]]
#   ## General Aggregator Arguments:
#   ## The period on which to flush & clear the aggregator.
#   period = "30s"
#   ## If true, the original metric will be dropped by the
#   ## aggregator and will not get sent to the output plugins.
#   drop_original = false


# # Count the occurance of values in fields.
# [[aggregators.valuecounter]]
#   ## General Aggregator Arguments:
#   ## The period on which to flush & clear the aggregator.
#   period = "30s"
#   ## If true, the original metric will be dropped by the
#   ## aggregator and will not get sent to the output plugins.
#   drop_original = false
#   ## The fields for which the values will be counted
#   fields = []



###############################################################################
#                            INPUT PLUGINS                                    #
###############################################################################

# Read metrics about cpu usage
[[inputs.cpu]]
  ## Whether to report per-cpu stats or not
  percpu = false
  ## Whether to report total system cpu stats or not
  totalcpu = true
  ## If true, collect raw CPU time metrics.
  collect_cpu_time = false
  ## If true, compute and report the sum of all non-idle CPU states.
  report_active = true


# Read metrics about memory usage
[[inputs.mem]]
  # no configuration


# Read metrics about swap memory usage
[[inputs.swap]]
  # no configuration


# Read metrics about disk usage by mount point
[[inputs.disk]]
  ## By default stats will be gathered for all mount points.
  ## Set mount_points will restrict the stats to only the specified mount points.
  # mount_points = ["/"]

  ## Ignore mount points by filesystem type.
  ## ignore_fs = ["tmpfs", "devtmpfs", "devfs", "overlay", "aufs", "squashfs"]


###########################################
# Monitor process cpu and memory usage
[[inputs.procstat]]
  ## PID file to monitor process
  # pid_file = "/var/run/nginx.pid"
  ## executable name (ie, pgrep <exe>)
  # exe = "nginx"
  ## pattern as argument for pgrep (ie, pgrep -f <pattern>)
  # pattern = "nginx"
  ## user as argument for pgrep (ie, pgrep -u <user>)
  # user = "nginx"
  ## Systemd unit name
  # systemd_unit = "nginx.service"
  ## CGroup name or path
  # cgroup = "systemd/system.slice/nginx.service"
  exe = "grafana"
  prefix = "grafana"

  ## override for process_name
  ## This is optional; default is sourced from /proc/<pid>/status
  # process_name = "bar"

  ## Field name prefix
  # prefix = ""

  ## Add PID as a tag instead of a field; useful to differentiate between
  ## processes whose tags are otherwise the same.  Can create a large number
  ## of series, use judiciously.
  # pid_tag = false

  ## Method to use when finding process IDs.  Can be one of 'pgrep', or
  ## 'native'.  The pgrep finder calls the pgrep executable in the PATH while
  ## the native finder performs the search directly in a manor dependent on the
  ## platform.  Default is 'pgrep'
  # pid_finder = "pgrep"
  
[[inputs.procstat]]
  exe = "telegraf"
  prefix = "telegraf"

[[inputs.procstat]]
  exe = "mds_record"
  prefix = "mds_record"

[[inputs.procstat]]
  exe = "influxd"
  prefix = "influxd"