kafka_consumer

README

Kafka Consumer Input Plugin

The Kafka consumer plugin reads from Kafka and creates metrics using one of the supported input data formats.

For old kafka version (< 0.8), please use the kafka_consumer_legacy input plugin and use the old zookeeper connection method.

Global configuration options

In addition to the plugin-specific configuration settings, plugins support additional global and plugin configuration settings. These settings are used to modify metrics, tags, and field or create aliases and configure ordering, etc. See the CONFIGURATION.md for more details.

Secret-store support

This plugin supports secrets from secret-stores for the sasl_username, sasl_password and sasl_access_token option. See the secret-store documentation for more details on how to use them.

Configuration

# Read metrics from Kafka topics
[[inputs.kafka_consumer]]
  ## Kafka brokers.
  brokers = ["localhost:9092"]

  ## Topics to consume.
  topics = ["telegraf"]

  ## When set this tag will be added to all metrics with the topic as the value.
  # topic_tag = ""

  ## Optional Client id
  # client_id = "Telegraf"

  ## Set the minimal supported Kafka version.  Setting this enables the use of new
  ## Kafka features and APIs.  Must be 0.10.2.0 or greater.
  ##   ex: version = "1.1.0"
  # version = ""

  ## Optional TLS Config
  # enable_tls = false
  # 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

  ## Period between keep alive probes.
  ## Defaults to the OS configuration if not specified or zero.
  # keep_alive_period = "15s"

  ## SASL authentication credentials.  These settings should typically be used
  ## with TLS encryption enabled
  # sasl_username = "kafka"
  # sasl_password = "secret"

  ## Optional SASL:
  ## one of: OAUTHBEARER, PLAIN, SCRAM-SHA-256, SCRAM-SHA-512, GSSAPI
  ## (defaults to PLAIN)
  # sasl_mechanism = ""

  ## used if sasl_mechanism is GSSAPI (experimental)
  # sasl_gssapi_service_name = ""
  # ## One of: KRB5_USER_AUTH and KRB5_KEYTAB_AUTH
  # sasl_gssapi_auth_type = "KRB5_USER_AUTH"
  # sasl_gssapi_kerberos_config_path = "/"
  # sasl_gssapi_realm = "realm"
  # sasl_gssapi_key_tab_path = ""
  # sasl_gssapi_disable_pafxfast = false

  ## used if sasl_mechanism is OAUTHBEARER (experimental)
  # sasl_access_token = ""

  ## SASL protocol version.  When connecting to Azure EventHub set to 0.
  # sasl_version = 1

  # Disable Kafka metadata full fetch
  # metadata_full = false

  ## Name of the consumer group.
  # consumer_group = "telegraf_metrics_consumers"

  ## Compression codec represents the various compression codecs recognized by
  ## Kafka in messages.
  ##  0 : None
  ##  1 : Gzip
  ##  2 : Snappy
  ##  3 : LZ4
  ##  4 : ZSTD
  # compression_codec = 0
  ## Initial offset position; one of "oldest" or "newest".
  # offset = "oldest"

  ## Consumer group partition assignment strategy; one of "range", "roundrobin" or "sticky".
  # balance_strategy = "range"

  ## Maximum number of retries for metadata operations including
  ## connecting. Sets Sarama library's Metadata.Retry.Max config value. If 0 or
  ## unset, use the Sarama default of 3,
  # metadata_retry_max = 0

  ## Type of retry backoff. Valid options: "constant", "exponential"
  # metadata_retry_type = "constant"

  ## Amount of time to wait before retrying. When metadata_retry_type is
  ## "constant", each retry is delayed this amount. When "exponential", the
  ## first retry is delayed this amount, and subsequent delays are doubled. If 0
  ## or unset, use the Sarama default of 250 ms
  # metadata_retry_backoff = 0

  ## Maximum amount of time to wait before retrying when metadata_retry_type is
  ## "exponential". Ignored for other retry types. If 0, there is no backoff
  ## limit.
  # metadata_retry_max_duration = 0

  ## Strategy for making connection to kafka brokers. Valid options: "startup",
  ## "defer". If set to "defer" the plugin is allowed to start before making a
  ## connection. This is useful if the broker may be down when telegraf is
  ## started, but if there are any typos in the broker setting, they will cause
  ## connection failures without warning at startup
  # connection_strategy = "startup"

  ## Maximum length of a message to consume, in bytes (default 0/unlimited);
  ## larger messages are dropped
  max_message_len = 1000000

  ## Max undelivered messages
  ## This plugin uses tracking metrics, which ensure messages are read to
  ## outputs before acknowledging them to the original broker to ensure data
  ## is not lost. This option sets the maximum messages to read from the
  ## broker that have not been written by an output.
  ##
  ## This value needs to be picked with awareness of the agent's
  ## metric_batch_size value as well. Setting max undelivered messages too high
  ## can result in a constant stream of data batches to the output. While
  ## setting it too low may never flush the broker's messages.
  # max_undelivered_messages = 1000

  ## Maximum amount of time the consumer should take to process messages. If
  ## the debug log prints messages from sarama about 'abandoning subscription
  ## to [topic] because consuming was taking too long', increase this value to
  ## longer than the time taken by the output plugin(s).
  ##
  ## Note that the effective timeout could be between 'max_processing_time' and
  ## '2 * max_processing_time'.
  # max_processing_time = "100ms"

  ## The default number of message bytes to fetch from the broker in each
  ## request (default 1MB). This should be larger than the majority of
  ## your messages, or else the consumer will spend a lot of time
  ## negotiating sizes and not actually consuming. Similar to the JVM's
  ## `fetch.message.max.bytes`.
  # consumer_fetch_default = "1MB"

  ## Data format to consume.
  ## 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"

Metrics

The plugin accepts arbitrary input and parses it according to the data_format setting. There is no predefined metric format.

Example Output

There is no predefined metric format, so output depends on plugin input.

Documentation

Index

• type ConsumerGroup
• type ConsumerGroupCreator
• type ConsumerGroupHandler
  • func NewConsumerGroupHandler(acc telegraf.Accumulator, maxUndelivered int, parser parsers.Parser, ...) *ConsumerGroupHandler
  • func (h *ConsumerGroupHandler) Cleanup(sarama.ConsumerGroupSession) error
  • func (h *ConsumerGroupHandler) ConsumeClaim(session sarama.ConsumerGroupSession, claim sarama.ConsumerGroupClaim) error
  • func (h *ConsumerGroupHandler) Handle(session sarama.ConsumerGroupSession, msg *sarama.ConsumerMessage) error
  • func (h *ConsumerGroupHandler) Reserve(ctx context.Context) error
  • func (h *ConsumerGroupHandler) Setup(sarama.ConsumerGroupSession) error
• type KafkaConsumer
  • func (k *KafkaConsumer) Gather(_ telegraf.Accumulator) error
  • func (k *KafkaConsumer) Init() error
  • func (*KafkaConsumer) SampleConfig() string
  • func (k *KafkaConsumer) SetParser(parser parsers.Parser)
  • func (k *KafkaConsumer) Start(acc telegraf.Accumulator) error
  • func (k *KafkaConsumer) Stop()
• type Message
• type SaramaCreator
  • func (*SaramaCreator) Create(brokers []string, group string, cfg *sarama.Config) (ConsumerGroup, error)

Types

type ConsumerGroup

type ConsumerGroup interface {
	Consume(ctx context.Context, topics []string, handler sarama.ConsumerGroupHandler) error
	Errors() <-chan error
	Close() error
}

type ConsumerGroupCreator

type ConsumerGroupCreator interface {
	Create(brokers []string, group string, cfg *sarama.Config) (ConsumerGroup, error)
}

type ConsumerGroupHandler

type ConsumerGroupHandler struct {
	MaxMessageLen int
	TopicTag      string
	// contains filtered or unexported fields
}

ConsumerGroupHandler is a sarama.ConsumerGroupHandler implementation.

func NewConsumerGroupHandler

func NewConsumerGroupHandler(acc telegraf.Accumulator, maxUndelivered int, parser parsers.Parser, log telegraf.Logger) *ConsumerGroupHandler

func (*ConsumerGroupHandler) Cleanup

func (h *ConsumerGroupHandler) Cleanup(sarama.ConsumerGroupSession) error

Cleanup stops the internal goroutine and is called after all ConsumeClaim functions have completed.

func (*ConsumerGroupHandler) ConsumeClaim

func (h *ConsumerGroupHandler) ConsumeClaim(session sarama.ConsumerGroupSession, claim sarama.ConsumerGroupClaim) error

ConsumeClaim is called once each claim in a goroutine and must be thread-safe. Should run until the claim is closed.

func (*ConsumerGroupHandler) Handle

func (h *ConsumerGroupHandler) Handle(session sarama.ConsumerGroupSession, msg *sarama.ConsumerMessage) error

Handle processes a message and if successful saves it to be acknowledged after delivery.

func (*ConsumerGroupHandler) Reserve

func (h *ConsumerGroupHandler) Reserve(ctx context.Context) error

Reserve blocks until there is an available slot for a new message.

func (*ConsumerGroupHandler) Setup

func (h *ConsumerGroupHandler) Setup(sarama.ConsumerGroupSession) error

Setup is called once when a new session is opened. It setups up the handler and begins processing delivered messages.

type KafkaConsumer

type KafkaConsumer struct {
	Brokers                []string        `toml:"brokers"`
	ConsumerGroup          string          `toml:"consumer_group"`
	MaxMessageLen          int             `toml:"max_message_len"`
	MaxUndeliveredMessages int             `toml:"max_undelivered_messages"`
	MaxProcessingTime      config.Duration `toml:"max_processing_time"`
	Offset                 string          `toml:"offset"`
	BalanceStrategy        string          `toml:"balance_strategy"`
	Topics                 []string        `toml:"topics"`
	TopicTag               string          `toml:"topic_tag"`
	ConsumerFetchDefault   config.Size     `toml:"consumer_fetch_default"`
	ConnectionStrategy     string          `toml:"connection_strategy"`

	kafka.ReadConfig

	kafka.Logger

	Log telegraf.Logger `toml:"-"`

	ConsumerCreator ConsumerGroupCreator `toml:"-"`
	// contains filtered or unexported fields
}

func (*KafkaConsumer) Gather

func (k *KafkaConsumer) Gather(_ telegraf.Accumulator) error

func (*KafkaConsumer) Init

func (k *KafkaConsumer) Init() error

func (*KafkaConsumer) SampleConfig

func (*KafkaConsumer) SampleConfig() string

func (*KafkaConsumer) SetParser

func (k *KafkaConsumer) SetParser(parser parsers.Parser)

func (*KafkaConsumer) Start

func (k *KafkaConsumer) Start(acc telegraf.Accumulator) error

func (*KafkaConsumer) Stop

func (k *KafkaConsumer) Stop()

type Message

type Message struct {
	// contains filtered or unexported fields
}

Message is an aggregate type binding the Kafka message and the session so that offsets can be updated.

type SaramaCreator

type SaramaCreator struct{}

func (*SaramaCreator) Create

func (*SaramaCreator) Create(brokers []string, group string, cfg *sarama.Config) (ConsumerGroup, error)