OpenTelemetry and ServiceNow 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.

This output plugin streams metrics from Telegraf directly to a ServiceNow MID Server via HTTP, leveraging the nowmetric serializer for efficient integration with ServiceNow’s Operational Intelligence and Event Management.

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.

ServiceNow

Telegraf can be used to send metric data directly to a ServiceNow MID Server REST endpoint. Metrics are formatted either using ServiceNow’s Operational Intelligence (OI) format or JSONv2 format, enabling seamless integration with ServiceNow’s Event Management and Operational Intelligence platforms. The serializer batches metrics efficiently, reducing network overhead by minimizing the number of HTTP POST requests. This integration allows users to quickly leverage metrics in ServiceNow for enhanced observability, proactive incident management, and performance monitoring, with ServiceNow’s operational intelligence capabilities.

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"

ServiceNow

[[outputs.http]]
  ## ServiceNow MID Server metrics endpoint
  url = "http://mid-server.example.com:9082/api/mid/sa/metrics"

  ## HTTP request method
  method = "POST"

  ## Basic Authentication credentials
  username = "evt.integration"
  password = "P@$$w0rd!"

  ## Data serialization format for ServiceNow
  data_format = "nowmetric"

  ## Metric format type: "oi" (default) or "jsonv2"
  nowmetric_format = "oi"

  ## HTTP Headers
  [outputs.http.headers]
    Content-Type = "application/json"
    Accept = "application/json"

  ## Optional timeout
  # timeout = "5s"

  ## TLS configuration options
  # tls_ca = "/etc/telegraf/ca.pem"
  # tls_cert = "/etc/telegraf/cert.pem"
  # tls_key = "/etc/telegraf/key.pem"
  # 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.

ServiceNow

1. Proactive Incident Management: Utilize the Telegraf and ServiceNow integration to stream infrastructure and application metrics in real-time to ServiceNow Event Management. Automatically trigger incidents or remediation workflows based on thresholds, significantly reducing incident detection and response times.

2. End-to-End Application Monitoring: Deploy Telegraf agents across multiple layers of an application stack, sending performance metrics directly into ServiceNow. Leveraging ServiceNow’s Operational Intelligence, teams can correlate metrics across components, quickly identifying performance bottlenecks.

3. Dynamic CI Performance Tracking: Integrate Telegraf metrics with ServiceNow’s CMDB by using this plugin to push performance data, allowing automatic updates of Configuration Item (CI) health states based on live metrics. This ensures an accurate and current state of infrastructure health in ServiceNow.

4. Cloud Resource Optimization: Collect metrics from hybrid and multi-cloud infrastructures using Telegraf, streaming directly to ServiceNow. Leverage these metrics for real-time analytics, predictive capacity planning, and resource optimization, enabling proactive management and reduced operational costs.

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.