目录
输入和输出集成概述
此插件报告 Suricata IDS/IPS 引擎的内部性能计数器,并处理传入数据以适应 Telegraf 的格式。
此输出插件为将 Telegraf 收集的指标直接路由到 TimescaleDB 中提供了可靠高效的机制。通过利用 PostgreSQL 强大的生态系统以及 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
Suricata
Suricata 插件捕获并报告来自 Suricata IDS/IPS 引擎的内部性能指标,其中包括各种统计信息,例如流量、内存使用情况、正常运行时间以及流和警报的计数器。此插件侦听来自 Suricata 的 JSON 格式的日志输出,从而可以解析数据并将其格式化以与 Telegraf 集成。它作为服务输入插件运行,这意味着它主动等待来自 Suricata 的指标或事件,而不是按预定义的时间间隔收集指标。该插件支持不同指标版本的配置,从而提高了灵活性和详细的数据收集能力。
TimescaleDB
TimescaleDB 是一个开源时序数据库,它是 PostgreSQL 的扩展,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,该解决方案可以管理大量数据,并具有高插入速率和复杂查询。通过利用 PostgreSQL 熟悉的 SQL 接口,并通过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。它的混合方法允许用户受益于 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,例如透明地将数据划分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
Suricata
[[inputs.suricata]]
## Source
## Data sink for Suricata stats log. This is expected to be a filename of a
## unix socket to be created for listening.
# source = "/var/run/suricata-stats.sock"
## Delimiter
## Used for flattening field keys, e.g. subitem "alert" of "detect" becomes
## "detect_alert" when delimiter is "_".
# delimiter = "_"
## Metric version
## Version 1 only collects stats and optionally will look for alerts if
## the configuration setting alerts is set to true.
## Version 2 parses any event type message by default and produced metrics
## under a single metric name using a tag to differentiate between event
## types. The timestamp for the message is applied to the generated metric.
## Additional tags and fields are included as well.
# version = "1"
## Alerts
## In metric version 1, only status is captured by default, alerts must be
## turned on with this configuration option. This option does not apply for
## metric version 2.
# alerts = false
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
Suricata
-
网络流量分析:利用 Suricata 插件跟踪有关网络入侵尝试和性能的详细指标,从而帮助进行实时威胁检测和响应。通过可视化捕获的警报和流量统计信息,安全团队可以快速查明漏洞并降低风险。
-
性能监控仪表板:使用 Suricata Telegraf 插件指标创建仪表板,以监控 IDS/IPS 引擎的健康状况和性能。此用例提供了内存使用情况、捕获的数据包和警报统计信息的概览,使团队能够保持最佳运行状态。
-
自动化安全报告:利用该插件生成有关警报统计信息和流量模式的定期报告,帮助安全分析师识别长期趋势并制定战略防御计划。自动化报告还可以确保持续评估网络的安全性。
-
实时警报处理:将 Suricata 的警报指标集成到更广泛的事件响应自动化框架中。通过整合来自 Suricata 插件的输入,组织可以开发用于警报和自动化响应工作流程的智能触发器,从而提高对潜在威胁的反应时间。
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快速响应不断变化的状况。
-
云应用程序性能监控:利用该插件将来自分布式云应用程序的详细性能指标馈送到 TimescaleDB 中。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,以便进行全面的历史分析。这种方法允许企业执行趋势分析、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。
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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。
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