Syslog and Cortex Integration

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 plugin enables Telegraf to send metrics to Cortex using the Prometheus remote write protocol, allowing seamless ingestion into Cortex’s scalable, multi-tenant time series storage.

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.

Cortex

With Telegraf’s HTTP output plugin and the prometheusremotewrite data format you can send metrics directly to Cortex, a horizontally scalable, long-term storage backend for Prometheus. Cortex supports multi-tenancy and accepts remote write requests using the Prometheus protobuf format. By using Telegraf as the collection agent and Remote Write as the transport mechanism, organizations can extend observability into sources not natively supported by Prometheus—such as Windows hosts, SNMP-enabled devices, or custom application metrics—while leveraging Cortex’s high-availability and long-retention capabilities.

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 = "_"

Cortex

[[outputs.http]]
  ## Cortex Remote Write endpoint
  url = "http://cortex.example.com/api/v1/push"

  ## Use POST to send data
  method = "POST"

  ## Send metrics using Prometheus remote write format
  data_format = "prometheusremotewrite"

  ## Optional HTTP headers for authentication
  # [outputs.http.headers]
  #   X-Scope-OrgID = "your-tenant-id"
  #   Authorization = "Bearer YOUR_API_TOKEN"

  ## Optional TLS configuration
  # tls_ca = "/path/to/ca.pem"
  # tls_cert = "/path/to/cert.pem"
  # tls_key = "/path/to/key.pem"
  # insecure_skip_verify = false

  ## Request timeout
  timeout = "10s"

Input and output integration examples

Syslog

1. 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.

2. 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.

3. 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.

4. 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.

Cortex

1. Unified Multi-Tenant Monitoring: Use Telegraf to collect metrics from different teams or environments and push them to Cortex with separate X-Scope-OrgID headers. This enables isolated data ingestion and querying per tenant, ideal for managed services and platform teams.

2. Extending Prometheus Coverage to Edge Devices: Deploy Telegraf on edge or IoT devices to collect system metrics and send them to a centralized Cortex cluster. This approach ensures consistent observability even for environments without local Prometheus scrapers.

3. Global Service Observability with Federated Tenants: Aggregate metrics from global infrastructure by configuring Telegraf agents to push data into regional Cortex clusters, each tagged with tenant identifiers. Cortex handles deduplication and centralized access across regions.

4. Custom App Telemetry Pipeline: Collect app-specific telemetry via Telegraf’s exec or http input plugins and forward it to Cortex. This allows DevOps teams to monitor app-specific KPIs in a scalable, query-efficient format while keeping metrics logically grouped by tenant or service.

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