Syslog and Splunk Integration
Powerful performance with an easy integration, powered by Telegraf, the open source data connector built by InfluxData.
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Powerful Performance, Limitless Scale
Collect, organize, and act on massive volumes of high-velocity data. Any data is more valuable when you think of it as time series data. with InfluxDB, the #1 time series platform built to scale with Telegraf.
See Ways to Get Started
Input and output integration overview
The Syslog plugin enables the collection of syslog messages from various sources using standard networking protocols. This functionality is critical for environments where systems need to be monitored and logged efficiently.
This output plugin facilitates direct streaming of Telegraf collected metrics into Splunk via the HTTP Event Collector, enabling easy integration with Splunk’s powerful analytics platform.
Integration details
Syslog
The Syslog plugin for Telegraf captures syslog messages transmitted over various protocols such as TCP, UDP, and TLS. It supports both RFC 5424 (the newer syslog protocol) and the older RFC 3164 (BSD syslog protocol). This plugin operates as a service input, effectively starting a service that listens for incoming syslog messages. Unlike traditional plugins, service inputs may not function with standard interval settings or CLI options like --once
. It includes options for setting network configurations, socket permissions, message handling, and connection handling. Furthermore, the integration with Rsyslog allows forwarding of logging messages, making it a powerful tool for collecting and relaying system logs in real-time, thus seamlessly integrating into monitoring and logging systems.
Splunk
Use Telegraf to easily collect and aggregate metrics from many different sources and send them to Splunk. Utilizing the HTTP output plugin combined with the specialized Splunk metrics serializer, this configuration ensures efficient data ingestion into Splunk’s metrics indexes. The HEC is an advanced mechanism provided by Splunk designed to reliably collect data at scale via HTTP or HTTPS, providing critical capabilities for security, monitoring, and analytics workloads. Telegraf’s integration with Splunk HEC streamlines operations by leveraging standard HTTP protocols, built-in authentication, and structured data serialization, optimizing metrics ingestion and enabling immediate actionable insights.
Configuration
Syslog
[[inputs.syslog]]
## Protocol, address and port to host the syslog receiver.
## If no host is specified, then localhost is used.
## If no port is specified, 6514 is used (RFC5425#section-4.1).
## ex: server = "tcp://localhost:6514"
## server = "udp://:6514"
## server = "unix:///var/run/telegraf-syslog.sock"
## When using tcp, consider using 'tcp4' or 'tcp6' to force the usage of IPv4
## or IPV6 respectively. There are cases, where when not specified, a system
## may force an IPv4 mapped IPv6 address.
server = "tcp://127.0.0.1:6514"
## Permission for unix sockets (only available on unix sockets)
## This setting may not be respected by some platforms. To safely restrict
## permissions it is recommended to place the socket into a previously
## created directory with the desired permissions.
## ex: socket_mode = "777"
# socket_mode = ""
## Maximum number of concurrent connections (only available on stream sockets like TCP)
## Zero means unlimited.
# max_connections = 0
## Read timeout (only available on stream sockets like TCP)
## Zero means unlimited.
# read_timeout = "0s"
## Optional TLS configuration (only available on stream sockets like TCP)
# tls_cert = "/etc/telegraf/cert.pem"
# tls_key = "/etc/telegraf/key.pem"
## Enables client authentication if set.
# tls_allowed_cacerts = ["/etc/telegraf/clientca.pem"]
## Maximum socket buffer size (in bytes when no unit specified)
## For stream sockets, once the buffer fills up, the sender will start
## backing up. For datagram sockets, once the buffer fills up, metrics will
## start dropping. Defaults to the OS default.
# read_buffer_size = "64KiB"
## Period between keep alive probes (only applies to TCP sockets)
## Zero disables keep alive probes. Defaults to the OS configuration.
# keep_alive_period = "5m"
## Content encoding for message payloads
## Can be set to "gzip" for compressed payloads or "identity" for no encoding.
# content_encoding = "identity"
## Maximum size of decoded packet (in bytes when no unit specified)
# max_decompression_size = "500MB"
## Framing technique used for messages transport
## Available settings are:
## octet-counting -- see RFC5425#section-4.3.1 and RFC6587#section-3.4.1
## non-transparent -- see RFC6587#section-3.4.2
# framing = "octet-counting"
## The trailer to be expected in case of non-transparent framing (default = "LF").
## Must be one of "LF", or "NUL".
# trailer = "LF"
## Whether to parse in best effort mode or not (default = false).
## By default best effort parsing is off.
# best_effort = false
## The RFC standard to use for message parsing
## By default RFC5424 is used. RFC3164 only supports UDP transport (no streaming support)
## Must be one of "RFC5424", or "RFC3164".
# syslog_standard = "RFC5424"
## Character to prepend to SD-PARAMs (default = "_").
## A syslog message can contain multiple parameters and multiple identifiers within structured data section.
## Eg., [id1 name1="val1" name2="val2"][id2 name1="val1" nameA="valA"]
## For each combination a field is created.
## Its name is created concatenating identifier, sdparam_separator, and parameter name.
# sdparam_separator = "_"
Splunk
[[outputs.http]]
## Splunk HTTP Event Collector endpoint
url = "https://splunk.example.com:8088/services/collector"
## HTTP method to use
method = "POST"
## Splunk authentication token
headers = {"Authorization" = "Splunk YOUR_SPLUNK_HEC_TOKEN"}
## Serializer for formatting metrics specifically for Splunk
data_format = "splunkmetric"
## Optional parameters
# timeout = "5s"
# insecure_skip_verify = false
# tls_ca = "/path/to/ca.pem"
# tls_cert = "/path/to/cert.pem"
# tls_key = "/path/to/key.pem"
Input and output integration examples
Syslog
-
Centralized Log Management: Use the Syslog plugin to aggregate log messages from multiple servers into a central logging system. This setup can help in monitoring overall system health, troubleshooting issues effectively, and maintaining audit trails by collecting syslog data from different sources.
-
Real-Time Alerting: Integrate the Syslog plugin with alerting tools to trigger real-time notifications when specific log patterns or errors are detected. For example, if a critical system error appears in the logs, an alert can be sent to the operations team, minimizing downtime and performing proactive maintenance.
-
Security Monitoring: Leverage the Syslog plugin for security monitoring by capturing logs from firewalls, intrusion detection systems, and other security devices. This logging capability enhances security visibility and helps in investigating potentially malicious activities by analyzing the captured syslog data.
-
Application Performance Tracking: Utilize the Syslog plugin to monitor application performance by collecting logs from various applications. This integration helps in analyzing the application’s behavior and performance trends, thus aiding in optimizing application processes and ensuring smoother operation.
Splunk
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Real-Time Security Analytics: Utilize this plugin to stream security-related metrics from various applications into Splunk in real-time. Organizations can detect threats instantly by correlating data streams across systems, significantly reducing detection and response times.
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Multi-Cloud Infrastructure Monitoring: Integrate Telegraf to consolidate metrics from multi-cloud environments directly into Splunk, enabling comprehensive visibility and operational intelligence. This unified monitoring allows teams to detect performance issues quickly and streamline cloud resource management.
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Dynamic Capacity Planning: Deploy the plugin to continuously push resource metrics from container orchestration platforms (like Kubernetes) into Splunk. Leveraging Splunk’s analytics capabilities, teams can automate predictive scaling and resource allocation, avoiding resource bottlenecks and minimizing costs.
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Automated Incident Response Workflows: Combine this plugin with Splunk’s alerting system to create automated incident response workflows. Metrics collected by Telegraf trigger real-time alerts and automated remediation scripts, ensuring rapid resolution and maintaining high system availability.
Feedback
Thank you for being part of our community! If you have any general feedback or found any bugs on these pages, we welcome and encourage your input. Please submit your feedback in the InfluxDB community Slack.
Powerful Performance, Limitless Scale
Collect, organize, and act on massive volumes of high-velocity data. Any data is more valuable when you think of it as time series data. with InfluxDB, the #1 time series platform built to scale with Telegraf.
See Ways to Get Started
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