JTI OpenConfig Telemetry and MySQL Integration
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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.
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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 Telegraf SQL plugin allows you to store metrics from Telegraf directly into a MySQL database, making it easier to analyze and visualize the collected metrics.
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.
MySQL
Telegraf’s SQL output plugin is designed to seamlessly write metric data to a SQL database by dynamically creating tables and columns based on the incoming metrics. When configured for MySQL, the plugin leverages the go-sql-driver/mysql, which requires enabling the ANSI_QUOTES SQL mode to ensure proper handling of quoted identifiers. This dynamic schema creation approach ensures that each metric is stored in its own table with a structure derived from its fields and tags, providing a detailed, timestamped record of system performance. The flexibility of the plugin allows it to handle high-throughput environments, making it ideal for scenarios that demand robust, granular metric logging and historical data analysis.
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
MySQL
[[outputs.sql]]
## Database driver
## Valid options: mssql (Microsoft SQL Server), mysql (MySQL), pgx (Postgres),
## sqlite (SQLite3), snowflake (snowflake.com) clickhouse (ClickHouse)
driver = "mysql"
## Data source name
## The format of the data source name is different for each database driver.
## See the plugin readme for details.
data_source_name = "username:password@tcp(host:port)/dbname"
## Timestamp column name
timestamp_column = "timestamp"
## Table creation template
## Available template variables:
## {TABLE} - table name as a quoted identifier
## {TABLELITERAL} - table name as a quoted string literal
## {COLUMNS} - column definitions (list of quoted identifiers and types)
table_template = "CREATE TABLE {TABLE}({COLUMNS})"
## Table existence check template
## Available template variables:
## {TABLE} - tablename as a quoted identifier
table_exists_template = "SELECT 1 FROM {TABLE} LIMIT 1"
## Initialization SQL
init_sql = "SET sql_mode='ANSI_QUOTES';"
## Maximum amount of time a connection may be idle. "0s" means connections are
## never closed due to idle time.
connection_max_idle_time = "0s"
## Maximum amount of time a connection may be reused. "0s" means connections
## are never closed due to age.
connection_max_lifetime = "0s"
## Maximum number of connections in the idle connection pool. 0 means unlimited.
connection_max_idle = 2
## Maximum number of open connections to the database. 0 means unlimited.
connection_max_open = 0
## NOTE: Due to the way TOML is parsed, tables must be at the END of the
## plugin definition, otherwise additional config options are read as part of the
## table
## Metric type to SQL type conversion
## The values on the left are the data types Telegraf has and the values on
## the right are the data types Telegraf will use when sending to a database.
##
## The database values used must be data types the destination database
## understands. It is up to the user to ensure that the selected data type is
## available in the database they are using. Refer to your database
## documentation for what data types are available and supported.
#[outputs.sql.convert]
# integer = "INT"
# real = "DOUBLE"
# text = "TEXT"
# timestamp = "TIMESTAMP"
# defaultvalue = "TEXT"
# unsigned = "UNSIGNED"
# bool = "BOOL"
# ## This setting controls the behavior of the unsigned value. By default the
# ## setting will take the integer value and append the unsigned value to it. The other
# ## option is "literal", which will use the actual value the user provides to
# ## the unsigned option. This is useful for a database like ClickHouse where
# ## the unsigned value should use a value like "uint64".
# # conversion_style = "unsigned_suffix"
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.
MySQL
-
Real-Time Web Analytics Storage: Leverage the plugin to capture website performance metrics and store them in MySQL. This setup enables teams to monitor user interactions, analyze traffic patterns, and dynamically adjust site features based on real-time data insights.
-
IoT Device Monitoring: Utilize the plugin to collect metrics from a network of IoT sensors and log them into a MySQL database. This use case supports continuous monitoring of device health and performance, allowing for predictive maintenance and immediate response to anomalies.
-
Financial Transaction Logging: Record high-frequency financial transaction data with precise timestamps. This approach supports robust audit trails, real-time fraud detection, and comprehensive historical analysis for compliance and reporting purposes.
-
Application Performance Benchmarking: Integrate the plugin with application performance monitoring systems to log metrics into MySQL. This facilitates detailed benchmarking and trend analysis over time, enabling organizations to identify performance bottlenecks and optimize resource allocation effectively.
Feedback
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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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