Docker 和 PostgreSQL 集成

强大的性能和简单的集成,由 InfluxData 构建的开源数据连接器 Telegraf 提供支持。

info

对于大规模实时查询,这不是推荐的配置。为了进行查询和压缩优化、高速摄取和高可用性,您可能需要考虑 Docker 和 InfluxDB

50 亿+

Telegraf 下载量

#1

时间序列数据库
来源:DB Engines

10 亿+

InfluxDB 下载量

2,800+

贡献者

目录

强大的性能,无限的扩展

收集、组织和处理海量高速数据。当您将任何数据视为时间序列数据时,它都更有价值。使用 InfluxDB,这是 #1 的时间序列平台,旨在与 Telegraf 一起扩展。

查看入门方法

输入和输出集成概览

Docker 输入插件允许您使用 Docker Engine API 从 Docker 容器中收集指标,从而增强容器化应用程序的可视性和监控。

Telegraf PostgreSQL 插件允许您高效地将指标写入 PostgreSQL 数据库,同时自动管理数据库模式。

集成详情

Docker

Telegraf 的 Docker 输入插件从 Docker Engine API 收集有价值的指标,从而提供对正在运行的容器的洞察。此插件利用官方 Docker 客户端与 Engine API 交互,允许用户监控各种容器状态、资源分配和性能指标。通过按名称和状态筛选容器的选项,以及可自定义的标签和标签,此插件支持在各种环境中(无论是在本地系统上还是在 Kubernetes 等编排平台内)灵活监控容器化应用程序。此外,它通过要求访问 Docker 守护程序的权限来解决安全注意事项,并强调在容器化环境中部署时进行正确的配置。

PostgreSQL

PostgreSQL 插件使用户能够将指标写入 PostgreSQL 数据库或兼容的数据库,为模式管理提供强大的支持,通过自动更新缺少的列。该插件旨在促进与监控解决方案的集成,使用户能够高效地存储和管理时间序列数据。它为连接设置、并发性和错误处理提供可配置的选项,并支持高级功能,例如用于标签和字段的 JSONB 存储、外键标记、模板化模式修改以及通过 pguint 扩展支持无符号整数数据类型。

配置

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

PostgreSQL

# Publishes metrics to a postgresql 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 age of a connection 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 backoff 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

  ## 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

Docker

  1. 监控容器化应用程序的性能:使用 Docker 输入插件来跟踪在 Docker 容器中运行的应用程序的 CPU、内存、磁盘 I/O 和网络活动。通过收集这些指标,DevOps 团队可以主动管理资源分配、排除性能瓶颈并确保跨不同环境的最佳应用程序性能。

  2. 与 Kubernetes 集成:利用此插件从 Kubernetes 编排的 Docker 容器中收集指标。通过滤除不必要的 Kubernetes 标签并专注于关键指标,团队可以简化其监控解决方案并创建仪表板,从而深入了解 Kubernetes 集群中运行的微服务的整体健康状况。

  3. 容量规划和资源优化:使用 Docker 输入插件收集的指标来执行 Docker 部署的容量规划。分析使用模式有助于识别未充分利用的资源和过度配置的容器,从而指导根据实际使用趋势进行向上或向下扩展的决策。

  4. 容器异常的自动警报:根据通过 Docker 插件收集的指标设置警报规则,以通知团队资源使用量异常飙升或服务中断。这种主动监控方法有助于维护服务可靠性并优化容器化应用程序的性能。

PostgreSQL

  1. 使用复杂查询进行实时分析:利用 PostgreSQL 插件将来自各种来源的指标存储在 PostgreSQL 数据库中,从而使用复杂查询实现实时分析。这种设置可以帮助数据科学家和分析师发现模式和趋势,因为他们可以跨多个表操作关系数据,同时利用 PostgreSQL 强大的查询优化功能。具体来说,用户可以使用跨不同指标表的 JOIN 操作创建复杂的报告,从而揭示通常在嵌入式系统中仍然隐藏的见解。

  2. 与 TimescaleDB 集成以进行时间序列数据处理:在 TimescaleDB 实例中利用 PostgreSQL 插件来高效处理和分析时间序列数据。通过实施超表,用户可以在时间维度上实现更高的性能和主题分区。此集成允许用户对大量时间序列数据运行分析查询,同时保留 PostgreSQL SQL 查询的全部功能,从而确保指标分析的可靠性和效率。

  3. 数据版本控制和历史分析:实施使用 PostgreSQL 插件的策略,以维护指标的不同版本。用户可以设置一个不可变的数据表结构,其中保留较旧版本的表,从而轻松进行历史分析。这种方法不仅提供了对数据演变的洞察,还有助于遵守数据保留策略,确保数据集的历史完整性保持不变。

  4. 用于不断发展的指标的动态模式管理:使用插件的模板功能来创建动态变化的模式,以响应指标变化。此用例允许组织在指标发展时调整其数据结构,添加必要的字段并确保遵守数据完整性策略。通过利用模板化的 SQL 命令,用户无需手动干预即可扩展其数据库,从而促进敏捷数据管理实践。

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。

强大的性能,无限的扩展

收集、组织和处理海量高速数据。当您将任何数据视为时间序列数据时,它都更有价值。使用 InfluxDB,这是 #1 的时间序列平台,旨在与 Telegraf 一起扩展。

查看入门方法

相关集成

HTTP 和 InfluxDB 集成

HTTP 插件从一个或多个 HTTP(S) 端点收集指标。它支持各种身份验证方法和数据格式的配置选项。

查看集成

Kafka 和 InfluxDB 集成

此插件从 Kafka 读取消息,并允许基于这些消息创建指标。它支持各种配置,包括不同的 Kafka 设置和消息处理选项。

查看集成

Kinesis 和 InfluxDB 集成

Kinesis 插件允许从 AWS Kinesis 流中读取指标。它支持多种输入数据格式,并为可靠的消息处理提供带有 DynamoDB 的检查点功能。

查看集成