RabbitMQ and ServiceNow 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
This plugin reads metrics from RabbitMQ servers, providing essential insights into the performance and state of the messaging system.
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
RabbitMQ
The RabbitMQ plugin for Telegraf allows users to gather metrics from RabbitMQ servers via the RabbitMQ Management Plugin. This capability is crucial for monitoring the performance and health of RabbitMQ instances, which are widely utilized for message queuing and processing in various applications. The plugin provides comprehensive insights into key RabbitMQ metrics, including message rates, queue depths, and node health statistics, thereby enabling operators to maintain optimal performance and robustness of their messaging infrastructure. Additionally, it supports secret-stores for managing sensitive credentials securely, making integration with existing systems smoother. Configuration options allow for flexibility in specifying the nodes, queues, and exchanges to monitor, providing valuable adaptability for diverse deployment scenarios.
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
RabbitMQ
[[inputs.rabbitmq]]
## Management Plugin url. (default: http://localhost:15672)
# url = "http://localhost:15672"
## Tag added to rabbitmq_overview series; deprecated: use tags
# name = "rmq-server-1"
## Credentials
# username = "guest"
# password = "guest"
## 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
## Optional request timeouts
## ResponseHeaderTimeout, if non-zero, specifies the amount of time to wait
## for a server's response headers after fully writing the request.
# header_timeout = "3s"
##
## client_timeout specifies a time limit for requests made by this client.
## Includes connection time, any redirects, and reading the response body.
# client_timeout = "4s"
## A list of nodes to gather as the rabbitmq_node measurement. If not
## specified, metrics for all nodes are gathered.
# nodes = ["rabbit@node1", "rabbit@node2"]
## A list of queues to gather as the rabbitmq_queue measurement. If not
## specified, metrics for all queues are gathered.
## Deprecated in 1.6: Use queue_name_include instead.
# queues = ["telegraf"]
## A list of exchanges to gather as the rabbitmq_exchange measurement. If not
## specified, metrics for all exchanges are gathered.
# exchanges = ["telegraf"]
## Metrics to include and exclude. Globs accepted.
## Note that an empty array for both will include all metrics
## Currently the following metrics are supported: "exchange", "federation", "node", "overview", "queue"
# metric_include = []
# metric_exclude = []
## Queues to include and exclude. Globs accepted.
## Note that an empty array for both will include all queues
# queue_name_include = []
# queue_name_exclude = []
## Federation upstreams to include and exclude specified as an array of glob
## pattern strings. Federation links can also be limited by the queue and
## exchange filters.
# federation_upstream_include = []
# federation_upstream_exclude = []
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
RabbitMQ
-
Monitoring Queue Performance Metrics: Use the RabbitMQ plugin to keep track of queue performance over time. This involves setting up monitoring dashboards that visualize crucial queue metrics such as message rates, the number of consumers, and message delivery rates. With this information, teams can proactively address any bottlenecks or performance issues by analyzing trends and making data-informed decisions about scaling or optimizing their RabbitMQ configuration.
-
Alerting on System Health: Integrate the RabbitMQ plugin with an alerting system to notify operational teams of potential issues within RabbitMQ instances. For example, if the number of unacknowledged messages reaches a critical threshold or if queues become overwhelmed, alerts can trigger, allowing for immediate investigation and swift remedial action to maintain the health of message flows.
-
Analyzing Message Processing Metrics: Employ the plugin to gather detailed metrics on message processing performance, such as the rates of messages published, acknowledged, and redelivered. By analyzing these metrics, teams can evaluate the efficiency of their message consumer applications and make adjustments to configuration or code where necessary, thereby enhancing overall system throughput and resilience.
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Cross-System Data Integration: Leverage the metrics collected by the RabbitMQ plugin to integrate data flows between RabbitMQ and other systems or services. For example, use the gathered metrics to drive automated workflows or analytics pipelines that utilize messages processed in RabbitMQ, enabling organizations to optimize workflows and enhance data agility across their ecosystems.
ServiceNow
-
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.
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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.
-
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.
-
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.
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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