JTI OpenConfig Telemetry and Librato Integration
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Input and output integration overview
The JTI OpenConfig Telemetry plugin allows users to collect real-time telemetry data from devices running Juniper’s implementation of the OpenConfig model, leveraging the Junos Telemetry Interface for efficient data retrieval.
The Librato plugin for Telegraf is designed to facilitate seamless integration with the Librato Metrics API, allowing for efficient metric reporting and monitoring.
Integration details
JTI OpenConfig Telemetry
This plugin reads data from Juniper Networks’ OpenConfig telemetry implementation using the Junos Telemetry Interface (JTI). OpenConfig is an initiative aimed at enabling standardized and open network device telemetry through a common model for various devices and protocols. The JTI allows for the collection of this telemetry data in a real-time manner from various sensors defined within the configuration. Configurable parameters for this plugin include the ability to specify device addresses, authentication credentials, sampling frequency, and multiple sensors with potentially different reporting rates. The plugin uniquely handles time-stamping either through the collection time or the timestamp provided in the data, allowing for flexibility in how data is processed. Given its support for TLS for secure communication, the plugin is well-suited for integration into both traditional and modern network management systems, enhancing visibility into network performance and reliability.
Librato
The Librato plugin enables Telegraf to send metrics to the Librato Metrics API. To authenticate, users must provide an api_user
and api_token
, which can be acquired from the Librato account settings. This integration allows for efficient monitoring and reporting of custom metrics within the Librato platform. The plugin also utilizes a source_tag
option that can enrich the metrics with contextual information from Point Tags; however, it does not currently support sending associated Point Tags. It is essential to note that any point value sent that cannot be converted to a float64 type will be skipped, ensuring that only valid metrics are processed and sent to Librato. The plugin also supports secret-store options for managing sensitive authentication credentials securely, facilitating best practices in credential management.
Configuration
JTI OpenConfig Telemetry
[[inputs.jti_openconfig_telemetry]]
## List of device addresses to collect telemetry from
servers = ["localhost:1883"]
## Authentication details. Username and password are must if device expects
## authentication. Client ID must be unique when connecting from multiple instances
## of telegraf to the same device
username = "user"
password = "pass"
client_id = "telegraf"
## Frequency to get data
sample_frequency = "1000ms"
## Sensors to subscribe for
## A identifier for each sensor can be provided in path by separating with space
## Else sensor path will be used as identifier
## When identifier is used, we can provide a list of space separated sensors.
## A single subscription will be created with all these sensors and data will
## be saved to measurement with this identifier name
sensors = [
"/interfaces/",
"collection /components/ /lldp",
]
## We allow specifying sensor group level reporting rate. To do this, specify the
## reporting rate in Duration at the beginning of sensor paths / collection
## name. For entries without reporting rate, we use configured sample frequency
sensors = [
"1000ms customReporting /interfaces /lldp",
"2000ms collection /components",
"/interfaces",
]
## Timestamp Source
## Set to 'collection' for time of collection, and 'data' for using the time
## provided by the _timestamp field.
# timestamp_source = "collection"
## Optional TLS Config
# enable_tls = false
# tls_ca = "/etc/telegraf/ca.pem"
# tls_cert = "/etc/telegraf/cert.pem"
# tls_key = "/etc/telegraf/key.pem"
## Minimal TLS version to accept by the client
# tls_min_version = "TLS12"
## Use TLS but skip chain & host verification
# insecure_skip_verify = false
## Delay between retry attempts of failed RPC calls or streams. Defaults to 1000ms.
## Failed streams/calls will not be retried if 0 is provided
retry_delay = "1000ms"
## Period for sending keep-alive packets on idle connections
## This is helpful to identify broken connections to the server
# keep_alive_period = "10s"
## To treat all string values as tags, set this to true
str_as_tags = false
Librato
[[outputs.librato]]
## Librato API Docs
## http://dev.librato.com/v1/metrics-authentication
## Librato API user
api_user = "[email protected]" # required.
## Librato API token
api_token = "my-secret-token" # required.
## Debug
# debug = false
## Connection timeout.
# timeout = "5s"
## Output source Template (same as graphite buckets)
## see https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_OUTPUT.md#graphite
## This template is used in librato's source (not metric's name)
template = "host"
Input and output integration examples
JTI OpenConfig Telemetry
-
Network Performance Monitoring: Use the JTI OpenConfig Telemetry plugin to monitor network performance metrics from multiple Juniper devices in real-time. By configuring various sensors, operators can gain insights into interface performance, traffic patterns, and error rates, allowing for proactive troubleshooting and optimization of the network.
-
Automated Fault Detection: Integrate the telemetry data collected via this plugin with a fault detection system that triggers alerts based on predefined thresholds. For example, when a specific sensor indicates a fault or threshold breach, automated scripts can be initiated to remediate the situation, dramatically improving response times.
-
Historical Performance Analysis: By forwarding the collected telemetry data into a time-series database, organizations can perform historical analysis on network performance. This enables teams to identify trends over time, spot anomalies, and make more informed decisions regarding network capacity planning and resource allocation.
-
Real-Time Dashboards for Network Operations: Leverage the real-time data gathered through this plugin to power visualization dashboards that provide network operators with live insights into performance metrics. This facilitates better operational awareness and quicker decision-making during critical events.
Librato
-
Real-time Application Monitoring: Utilize Librato to collect performance metrics from a web application in real-time. This setup involves sending response times, error rates, and user interactions to Librato, allowing developers to monitor the application’s health and performance metrics closely. By analyzing these metrics, teams can quickly identify and address performance bottlenecks or application failures before they impact end users.
-
Infrastructure Metrics Aggregation: Leverage this plugin to gather and send metrics from various infrastructure components, such as servers or containers, to Librato for centralized monitoring. Configuring the plugin to send CPU, memory usage, and disk I/O metrics enables system administrators to have a comprehensive view of infrastructure performance, assisting in capacity planning and resource optimization strategies.
-
Custom Metrics for Business Operations: Feed business-specific metrics, such as sales transactions or user sign-ups, to the Librato service using this plugin. By tracking these custom metrics, businesses can gain insights into their operational performance and make data-driven decisions to enhance their strategies, marketing efforts, or product development initiatives.
-
Anomaly Detection in Metrics: Implement monitoring tools that utilize machine learning for anomaly detection. By continuously sending real-time metrics to Librato, teams can analyze trends and automatically flag unusual behavior, such as sudden spikes in latency or unusual traffic patterns, enabling timely intervention and troubleshooting.
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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