目录
输入和输出集成概述
Docker 输入插件允许您使用 Docker Engine API 从 Docker 容器收集指标,从而增强容器化应用程序的可见性和监控。
Telegraf 的 SQL 插件有助于将指标存储在 SQL 数据库中。 当配置用于 Microsoft SQL Server 时,它支持特定的 DSN 格式和架构要求,从而实现与 SQL Server 的无缝集成。
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深入了解。 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。 借助按名称和状态过滤容器的选项,以及可自定义的标签,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考虑因素,并强调在容器化环境中部署时进行正确的配置。
Microsoft SQL Server
Telegraf 的 Microsoft SQL Server SQL 输出插件旨在通过动态创建与传入数据结构匹配的表和列来捕获和存储指标数据。 此集成利用 go-mssqldb 驱动程序,该驱动程序通过包含服务器、端口和数据库详细信息的 DSN 遵循 SQL Server 连接协议。 尽管该驱动程序由于单元测试有限而被认为是实验性的,但它为动态架构生成和数据插入提供了强大的支持,从而能够详细记录系统性能的时间戳记录。 这种灵活性使其成为需要可靠和精细指标日志记录的环境的宝贵工具,尽管其状态为实验性。
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
Microsoft SQL Server
[[outputs.sql]]
## Database driver
## Valid options: mssql (Microsoft SQL Server), mysql (MySQL), pgx (Postgres),
## sqlite (SQLite3), snowflake (snowflake.com), clickhouse (ClickHouse)
driver = "mssql"
## Data source name
## For Microsoft SQL Server, the DSN typically includes the server, port, username, password, and database name.
## Example DSN: "sqlserver://username:password@localhost:1433?database=telegraf"
data_source_name = "sqlserver://username:password@localhost:1433?database=telegraf"
## Timestamp column name
timestamp_column = "timestamp"
## Table creation template
## Available template variables:
## {TABLE} - table name as a quoted identifier
## {TABLELITERAL} - table name as a quoted string literal
## {COLUMNS} - column definitions (list of quoted identifiers and types)
table_template = "CREATE TABLE {TABLE} ({COLUMNS})"
## Table existence check template
## Available template variables:
## {TABLE} - table name as a quoted identifier
table_exists_template = "SELECT 1 FROM {TABLE} LIMIT 1"
## Initialization SQL (optional)
init_sql = ""
## Maximum amount of time a connection may be idle. "0s" means connections are never closed due to idle time.
connection_max_idle_time = "0s"
## Maximum amount of time a connection may be reused. "0s" means connections are never closed due to age.
connection_max_lifetime = "0s"
## Maximum number of connections in the idle connection pool. 0 means unlimited.
connection_max_idle = 2
## Maximum number of open connections to the database. 0 means unlimited.
connection_max_open = 0
## Metric type to SQL type conversion
## You can customize the mapping if needed.
#[outputs.sql.convert]
# integer = "INT"
# real = "DOUBLE"
# text = "TEXT"
# timestamp = "TIMESTAMP"
# defaultvalue = "TEXT"
# unsigned = "UNSIGNED"
# bool = "BOOL"
输入和输出集成示例
Docker
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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不同环境中的最佳应用程序性能。
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与 Kubernetes 集成:利用此插件收集由 Kubernetes 编排的 Docker 容器的指标。 通过过滤掉不必要的 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。
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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,从而根据实际使用趋势指导扩展或缩减的决策。
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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异常峰值或服务中断。 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。
Microsoft SQL Server
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企业应用程序监控:利用该插件捕获在 SQL Server 上运行的企业应用程序的详细性能指标。 此设置允许 IT 团队分析系统性能、跟踪事务时间并识别复杂的多层环境中的瓶颈。
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动态基础设施审计:部署该插件以在 SQL Server 中创建基础设施变更和性能指标的动态审计日志。 此用例非常适合需要实时监控和系统性能历史分析以进行合规性和优化的组织。
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自动性能基准测试:使用该插件持续记录和分析 SQL Server 数据库的性能指标。 这实现了自动基准测试,将历史数据与当前性能进行比较,从而有助于快速识别服务中的异常或降级。
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集成 DevOps 仪表板:将该插件与 DevOps 监控工具集成,以将来自 SQL Server 的实时指标馈送到集中式仪表板中。 这提供了应用程序运行状况的整体视图,使团队可以将 SQL Server 性能与应用程序级事件相关联,从而实现更快的故障排除和主动维护。
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