OpenTelemetry and Graylog Integration

Input and output integration overview

This plugin receives traces, metrics, and logs from OpenTelemetry clients and agents via gRPC, enabling comprehensive observability of applications.

The Graylog plugin allows you to send Telegraf metrics to a Graylog server, utilizing the GELF format for structured logging.

Integration details

OpenTelemetry

The OpenTelemetry plugin is designed to receive telemetry data such as traces, metrics, and logs from clients and agents implementing OpenTelemetry via gRPC. This plugin initiates a gRPC service that listens for incoming telemetry data, making it distinct from standard plugins that collect metrics at defined intervals. The OpenTelemetry ecosystem aids developers in observing and understanding their applications’ performance by providing a vendor-neutral way to instrument, generate, collect, and export telemetry data. Key features of this plugin include customizable connection timeouts, adjustable maximum message sizes for incoming data, and options for specifying span, log, and profile dimensions to tag the incoming metrics. With this flexibility, organizations can tailor their telemetry collection to meet precise observability requirements and ensure seamless data integration into systems like InfluxDB.

Graylog

The Graylog plugin is designed for sending metrics to a Graylog instance using the GELF (Graylog Extended Log Format) format. GELF helps standardize the logging data, making it easier for systems to send and analyze logs. The plugin adheres to the GELF specification, which lays out requirements for specific fields within the payload. Notably, the timestamp must be in UNIX format, and if present, the plugin sends the timestamp as-is to Graylog without alterations. If omitted, it automatically generates a timestamp. Additionally, any extra fields not explicitly defined by the spec will be prefixed with an underscore, helping to keep the data organized and compliant with GELF’s requirements. This capability is particularly valuable for users monitoring applications and infrastructure in real-time, as it allows for seamless integration and improved visibility across multiple systems.

Configuration

OpenTelemetry

[[inputs.opentelemetry]]
  ## Override the default (0.0.0.0:4317) destination OpenTelemetry gRPC service
  ## address:port
  # service_address = "0.0.0.0:4317"

  ## Override the default (5s) new connection timeout
  # timeout = "5s"

  ## gRPC Maximum Message Size
  # max_msg_size = "4MB"

  ## Override the default span attributes to be used as line protocol tags.
  ## These are always included as tags:
  ## - trace ID
  ## - span ID
  ## Common attributes can be found here:
  ## - https://github.com/open-telemetry/opentelemetry-collector/tree/main/semconv
  # span_dimensions = ["service.name", "span.name"]

  ## Override the default log record attributes to be used as line protocol tags.
  ## These are always included as tags, if available:
  ## - trace ID
  ## - span ID
  ## Common attributes can be found here:
  ## - https://github.com/open-telemetry/opentelemetry-collector/tree/main/semconv
  ## When using InfluxDB for both logs and traces, be certain that log_record_dimensions
  ## matches the span_dimensions value.
  # log_record_dimensions = ["service.name"]

  ## Override the default profile attributes to be used as line protocol tags.
  ## These are always included as tags, if available:
  ## - profile_id
  ## - address
  ## - sample
  ## - sample_name
  ## - sample_unit
  ## - sample_type
  ## - sample_type_unit
  ## Common attributes can be found here:
  ## - https://github.com/open-telemetry/opentelemetry-collector/tree/main/semconv
  # profile_dimensions = []

  ## Override the default (prometheus-v1) metrics schema.
  ## Supports: "prometheus-v1", "prometheus-v2"
  ## For more information about the alternatives, read the Prometheus input
  ## plugin notes.
  # metrics_schema = "prometheus-v1"

  ## Optional TLS Config.
  ## For advanced options: https://github.com/influxdata/telegraf/blob/v1.18.3/docs/TLS.md
  ##
  ## Set one or more allowed client CA certificate file names to
  ## enable mutually authenticated TLS connections.
  # tls_allowed_cacerts = ["/etc/telegraf/clientca.pem"]
  ## Add service certificate and key.
  # tls_cert = "/etc/telegraf/cert.pem"
  # tls_key = "/etc/telegraf/key.pem"

Graylog

[[outputs.graylog]]
  ## Endpoints for your graylog instances.
  servers = ["udp://127.0.0.1:12201"]

  ## Connection timeout.
  # timeout = "5s"

  ## The field to use as the GELF short_message, if unset the static string
  ## "telegraf" will be used.
  ##   example: short_message_field = "message"
  # short_message_field = ""

  ## According to GELF payload specification, additional fields names must be prefixed
  ## with an underscore. Previous versions did not prefix custom field 'name' with underscore.
  ## Set to true for backward compatibility.
  # name_field_no_prefix = false

  ## Connection retry options
  ## Attempt to connect to the endpoints if the initial connection fails.
  ## If 'false', Telegraf will give up after 3 connection attempt and will
  ## exit with an error. If set to 'true', the plugin will retry to connect
  ## to the unconnected endpoints infinitely.
  # connection_retry = false
  ## Time to wait between connection retry attempts.
  # connection_retry_wait_time = "15s"

  ## 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

Input and output integration examples

OpenTelemetry

1. Unified Monitoring Across Services: Use the OpenTelemetry plugin to collect and consolidate telemetry data from various microservices within a Kubernetes environment. By instrumenting each service with OpenTelemetry, you can utilize this plugin to gather a holistic view of application performance and dependencies in real-time, enabling faster troubleshooting and improved reliability of complex systems.

2. Enhanced Debugging with Traces: Implement this plugin to capture end-to-end traces of requests flowing through multiple services. For instance, when a user initiates a transaction that triggers several backend services, the OpenTelemetry plugin can record detailed traces that highlight performance bottlenecks, giving developers the necessary insights to debug issues and optimize their code.

3. Dynamic Load Testing and Performance Monitoring: Leverage the capabilities of this plugin during load testing phases by collecting live metrics and traces under simulated higher loads. This approach helps to evaluate the resilience of the application components and identify potential performance degradations preemptively, ensuring a smooth user experience in production.

4. Integrated Logging and Metrics for Real-Time Monitoring: Combine the OpenTelemetry plugin with logging frameworks to gather real-time logs alongside metric data, creating a powerful observability platform. For example, integrate it within a CI/CD pipeline to monitor builds and deployments, while collecting logs that help diagnose failures or performance issues in real-time.

Graylog

1. Enhanced Log Management for Cloud Applications: Use the Graylog Telegraf plugin to aggregate logs from cloud-deployed applications across multiple servers. By integrating this plugin, teams can centralize logging data, making it easier to troubleshoot issues, monitor application performance, and maintain compliance with logging standards.

2. Real-Time Security Monitoring: Leverage the Graylog plugin to collect and send security-related metrics and logs to a Graylog server for real-time analysis. This allows security teams to quickly identify anomalies, track potential breaches, and respond to incidents promptly by correlating logs from various sources within the infrastructure.

3. Dynamic Alerting and Notification System: Implement the Graylog plugin to enhance alerting mechanisms in your infrastructure. By sending metrics to Graylog, teams can set up dynamic alerts based on log patterns or unexpected behavior, enabling proactive monitoring and rapid incident response strategies.

4. Cross-Platform Log Consolidation: Use the Graylog plugin to facilitate cross-platform log consolidation across diverse environments such as on-premises, hybrid, and cloud. By standardizing logging in the GELF format, organizations can ensure consistent monitoring and troubleshooting practices, regardless of where their services are hosted.

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.