目录
输入和输出集成概述
此插件监听通过 HTTP 从 AWS Data Firehose 以支持的数据格式发送的指标,提供实时数据摄取功能。
此输出插件为将 Telegraf 收集的指标直接路由到 TimescaleDB 提供了可靠高效的机制。 通过利用 PostgreSQL 的强大生态系统以及 TimescaleDB 的时序优化,它支持高性能数据摄取和高级查询功能。
集成详情
AWS Data Firehose
AWS Data Firehose Telegraf 插件旨在通过 HTTP 从 AWS Data Firehose 接收指标。 此插件监听各种格式的传入数据,并根据 AWS 官方文档中概述的请求-响应模式对其进行处理。 与按固定间隔运行的标准输入插件不同,此服务插件初始化一个保持活动状态的侦听器,等待传入的指标。 这允许从 AWS Data Firehose 实时摄取数据,使其适用于需要立即进行数据处理的场景。 主要功能包括指定服务地址、路径以及支持 TLS 连接以进行安全数据传输。 此外,该插件还支持可选的身份验证密钥和自定义标签,从而增强了其在涉及数据流和处理的各种用例中的灵活性。
TimescaleDB
TimescaleDB 是一个开源时序数据库,作为 PostgreSQL 的扩展构建,旨在高效处理大规模、面向时间的数据。 TimescaleDB 于 2017 年推出,是为了响应对强大、可扩展的解决方案日益增长的需求而诞生的,该解决方案可以管理具有高插入率和复杂查询的海量数据。 通过利用 PostgreSQL 熟悉的 SQL 接口并使用专门的时序功能对其进行增强,TimescaleDB 在希望将时序功能集成到现有关系数据库中的开发人员中迅速普及。 它的混合方法使用户能够受益于 PostgreSQL 的灵活性、可靠性和生态系统,同时为时序数据提供优化的性能。
该数据库在需要快速摄取数据点以及对历史时期进行复杂分析查询的环境中尤其有效。 TimescaleDB 具有许多创新功能,例如将数据透明地分区为可管理块的超表和内置的持续聚合。 这些功能可以显着提高查询速度和资源效率。
配置
AWS Data Firehose
[[inputs.firehose]]
## Address and port to host HTTP listener on
service_address = ":8080"
## Paths to listen to.
# paths = ["/telegraf"]
## maximum duration before timing out read of the request
# read_timeout = "5s"
## maximum duration before timing out write of the response
# write_timeout = "5s"
## Set one or more allowed client CA certificate file names to
## enable mutually authenticated TLS connections
# tls_allowed_cacerts = ["/etc/telegraf/clientca.pem"]
## Add service certificate and key
# tls_cert = "/etc/telegraf/cert.pem"
# tls_key = "/etc/telegraf/key.pem"
## Minimal TLS version accepted by the server
# tls_min_version = "TLS12"
## Optional access key to accept for authentication.
## AWS Data Firehose uses "x-amz-firehose-access-key" header to set the access key.
## If no access_key is provided (default), authentication is completely disabled and
## this plugin will accept all request ignoring the provided access-key in the request!
# access_key = "foobar"
## Optional setting to add parameters as tags
## If the http header "x-amz-firehose-common-attributes" is not present on the
## request, no corresponding tag will be added. The header value should be a
## json and should follow the schema as describe in the official documentation:
## https://docs.aws.amazon.com/firehose/latest/dev/httpdeliveryrequestresponse.html#requestformat
# parameter_tags = ["env"]
## 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"
TimescaleDB
# Publishes metrics to a TimescaleDB database
[[outputs.postgresql]]
## Specify connection address via the standard libpq connection string:
## host=... user=... password=... sslmode=... dbname=...
## Or a URL:
## postgres://[user[:password]]@localhost[/dbname]?sslmode=[disable|verify-ca|verify-full]
## See https://postgresql.ac.cn/docs/current/libpq-connect.html#LIBPQ-CONNSTRING
##
## All connection parameters are optional. Environment vars are also supported.
## e.g. PGPASSWORD, PGHOST, PGUSER, PGDATABASE
## All supported vars can be found here:
## https://postgresql.ac.cn/docs/current/libpq-envars.html
##
## Non-standard parameters:
## pool_max_conns (default: 1) - Maximum size of connection pool for parallel (per-batch per-table) inserts.
## pool_min_conns (default: 0) - Minimum size of connection pool.
## pool_max_conn_lifetime (default: 0s) - Maximum connection age before closing.
## pool_max_conn_idle_time (default: 0s) - Maximum idle time of a connection before closing.
## pool_health_check_period (default: 0s) - Duration between health checks on idle connections.
# connection = ""
## Postgres schema to use.
# schema = "public"
## Store tags as foreign keys in the metrics table. Default is false.
# tags_as_foreign_keys = false
## Suffix to append to table name (measurement name) for the foreign tag table.
# tag_table_suffix = "_tag"
## Deny inserting metrics if the foreign tag can't be inserted.
# foreign_tag_constraint = false
## Store all tags as a JSONB object in a single 'tags' column.
# tags_as_jsonb = false
## Store all fields as a JSONB object in a single 'fields' column.
# fields_as_jsonb = false
## Name of the timestamp column
## NOTE: Some tools (e.g. Grafana) require the default name so be careful!
# timestamp_column_name = "time"
## Type of the timestamp column
## Currently, "timestamp without time zone" and "timestamp with time zone"
## are supported
# timestamp_column_type = "timestamp without time zone"
## Templated statements to execute when creating a new table.
# create_templates = [
# '''CREATE TABLE {{ .table }} ({{ .columns }})''',
# ]
## Templated statements to execute when adding columns to a table.
## Set to an empty list to disable. Points containing tags for which there is
## no column will be skipped. Points containing fields for which there is no
## column will have the field omitted.
# add_column_templates = [
# '''ALTER TABLE {{ .table }} ADD COLUMN IF NOT EXISTS {{ .columns|join ", ADD COLUMN IF NOT EXISTS " }}''',
# ]
## Templated statements to execute when creating a new tag table.
# tag_table_create_templates = [
# '''CREATE TABLE {{ .table }} ({{ .columns }}, PRIMARY KEY (tag_id))''',
# ]
## Templated statements to execute when adding columns to a tag table.
## Set to an empty list to disable. Points containing tags for which there is
## no column will be skipped.
# tag_table_add_column_templates = [
# '''ALTER TABLE {{ .table }} ADD COLUMN IF NOT EXISTS {{ .columns|join ", ADD COLUMN IF NOT EXISTS " }}''',
# ]
## The postgres data type to use for storing unsigned 64-bit integer values
## (Postgres does not have a native unsigned 64-bit integer type).
## The value can be one of:
## numeric - Uses the PostgreSQL "numeric" data type.
## uint8 - Requires pguint extension (https://github.com/petere/pguint)
# uint64_type = "numeric"
## When using pool_max_conns > 1, and a temporary error occurs, the query is
## retried with an incremental backoff. This controls the maximum duration.
# retry_max_backoff = "15s"
## Approximate number of tag IDs to store in in-memory cache (when using
## tags_as_foreign_keys). This is an optimization to skip inserting known
## tag IDs. Each entry consumes approximately 34 bytes of memory.
# tag_cache_size = 100000
## Cut column names at the given length to not exceed PostgreSQL's
## 'identifier length' limit (default: no limit)
## (see https://postgresql.ac.cn/docs/current/limits.html)
## Be careful to not create duplicate column names!
# column_name_length_limit = 0
## Enable & set the log level for the Postgres driver.
# log_level = "warn" # trace, debug, info, warn, error, none
输入和输出集成示例
AWS Data Firehose
-
实时数据分析: 通过使用 AWS Data Firehose 插件,组织可以将来自各种来源(例如应用程序日志或物联网设备)的数据实时流式传输到分析平台。 这使数据团队能够在其生成时分析传入数据,从而根据最新的指标快速获得见解和进行运营调整。
-
分析访问模式以进行优化: 通过收集有关客户端如何通过 AWS Data Firehose 与应用程序交互的数据,企业可以深入了解用户行为。 这可以推动内容个性化策略或根据流量模式优化服务器架构以获得更好的性能。
-
自动化警报机制: 通过此插件将 AWS Data Firehose 与警报系统集成,团队可以根据收集的特定指标设置自动警报。 例如,如果在输入数据中达到特定阈值,则警报可以触发运营团队调查潜在问题,以防问题升级。
TimescaleDB
-
实时物联网数据摄取: 使用该插件实时收集和存储来自数千个物联网设备的传感器数据。 此设置有助于立即进行分析,帮助组织监控运营效率并对不断变化的条件做出快速响应。
-
云应用程序性能监控: 利用该插件将分布式云应用程序的详细性能指标馈送到 TimescaleDB。 这种集成支持实时仪表板和警报,使团队能够快速识别和缓解性能瓶颈。
-
历史数据分析和报告: 实施一个系统,将长期指标存储在 TimescaleDB 中,以进行全面的历史分析。 这种方法使企业能够执行趋势分析、生成详细报告并根据存档的时序数据做出数据驱动的决策。
-
自适应警报和异常检测: 将该插件与自动化异常检测工作流程集成。 通过将指标持续流式传输到 TimescaleDB,机器学习模型可以分析数据模式并在发生异常时触发警报,从而提高系统可靠性和主动维护。
反馈
感谢您成为我们社区的一份子! 如果您有任何一般性反馈或在这些页面上发现了任何错误,我们欢迎并鼓励您提出意见。 请在 InfluxDB 社区 Slack 中提交您的反馈。