Syslog and Clarify Integration
Powerful performance with an easy integration, powered by Telegraf, the open source data connector built by InfluxData.
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Table of Contents
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.
The Clarify plugin allows users to publish Telegraf metrics directly to Clarify, enabling enhanced analysis and monitoring capabilities.
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.
Clarify
This plugin facilitates the writing of Telegraf metrics to Clarify, a platform for managing and analyzing time series data. By transforming metrics into Clarify signals, this output plugin enables seamless integration of collected telemetry data into the Clarify ecosystem. Users must obtain valid credentials, either through a credentials file or basic authentication, to configure the plugin. The configuration also provides options for fine-tuning how metrics are mapped to signals in Clarify, including the ability to specify unique identifiers using tags. Given that Clarify supports only floating point values, the plugin ensures that any unsupported types are effectively filtered out during the publishing process. This comprehensive connectivity aligns with use cases in monitoring, data analysis, and operational 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 = "_"
Clarify
[[outputs.clarify]]
## Credentials File (Oauth 2.0 from Clarify integration)
credentials_file = "/path/to/clarify/credentials.json"
## Clarify username password (Basic Auth from Clarify integration)
username = "i-am-bob"
password = "secret-password"
## Timeout for Clarify operations
# timeout = "20s"
## Optional tags to be included when generating the unique ID for a signal in Clarify
# id_tags = []
# clarify_id_tag = 'clarify_input_id'
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.
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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.
Clarify
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Automated Data Monitoring: By integrating the Clarify plugin with sensor data collection, organizations can automate the monitoring of environmental conditions, such as temperature and humidity. The plugin processes metrics in real-time, sending updates to Clarify where they can be analyzed for trends, alerts, and historical tracking. This use case makes it easier to maintain optimal conditions in data centers or production environments, reducing the risk of equipment failures.
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Performance Metrics Analysis: Companies can leverage this plugin to send application performance metrics to Clarify. By transmitting key indicators such as response times and error rates, developers and operations teams can utilize Clarify’s capabilities to visualize and analyze application performance over time. This insight can drive improvements in user experience and help identify areas in need of optimization.
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Sensor Data Aggregation: Utilizing the plugin to push data from multiple sensors to Clarify allows for a comprehensive view of physical environments. This aggregation is particularly beneficial in sectors such as agriculture, where metrics from various sensors can be correlated to decision-making about resource allocations, pest control, and crop management. The plugin ensures the data is accurately mapped and transformed for effective analysis.
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Real-Time Alerts and Notifications: Implement the Clarify plugin to trigger real-time alerts based on predefined thresholds within the metrics being sent. For instance, if temperature readings exceed certain levels, alerts can be generated and sent to operational staff. This proactive approach allows for immediate responses to potential issues, enhancing operational reliability and safety.
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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