NATS and SQLite Integration
Powerful performance with an easy integration, powered by Telegraf, the open source data connector built by InfluxData.
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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
Input and output integration overview
The NATS Consumer Input Plugin enables real-time data consumption from NATS messaging subjects, integrating seamlessly into the Telegraf data pipeline for monitoring and metrics gathering.
Telegraf’s SQL output plugin stores metrics in an SQL database by creating tables dynamically for each metric type. When configured for SQLite, it utilizes a file-based DSN and a minimal SQL schema tailored for lightweight, embedded database usage.
Integration details
NATS
The NATS Consumer Plugin allows Telegraf to read metrics from specified NATS subjects and create metrics based on supported input data formats. Utilizing a Queue Group allows multiple instances of Telegraf to read from a NATS cluster in parallel, enhancing throughput and reliability. This plugin also supports various authentication methods, including username/password, NATS credentials files, and nkey seed files, ensuring secure communication with the NATS servers. It is particularly useful in environments where data persistence and message reliability are critical, thanks to features such as JetStream that facilitate the consumption of historical messages. Additionally, the ability to configure various operational parameters makes this plugin suitable for high-throughput scenarios while maintaining performance integrity.
SQLite
The SQL output plugin writes Telegraf metrics to an SQL database using a dynamic schema where each metric type corresponds to a table. For SQLite, the plugin uses the modernc.org/sqlite driver and requires a DSN in the format of a file URI (e.g., ‘file:/path/to/telegraf.db?cache=shared’). This configuration leverages standard ANSI SQL for table creation and data insertion, ensuring compatibility with SQLite’s capabilities.
Configuration
NATS
[[inputs.nats_consumer]]
## urls of NATS servers
servers = ["nats://localhost:4222"]
## subject(s) to consume
## If you use jetstream you need to set the subjects
## in jetstream_subjects
subjects = ["telegraf"]
## jetstream subjects
## jetstream is a streaming technology inside of nats.
## With jetstream the nats-server persists messages and
## a consumer can consume historical messages. This is
## useful when telegraf needs to restart it don't miss a
## message. You need to configure the nats-server.
## https://docs.nats.io/nats-concepts/jetstream.
jetstream_subjects = ["js_telegraf"]
## name a queue group
queue_group = "telegraf_consumers"
## Optional authentication with username and password credentials
# username = ""
# password = ""
## Optional authentication with NATS credentials file (NATS 2.0)
# credentials = "/etc/telegraf/nats.creds"
## Optional authentication with nkey seed file (NATS 2.0)
# nkey_seed = "/etc/telegraf/seed.txt"
## Use Transport Layer Security
# secure = false
## 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
## Sets the limits for pending msgs and bytes for each subscription
## These shouldn't need to be adjusted except in very high throughput scenarios
# pending_message_limit = 65536
# pending_bytes_limit = 67108864
## Max undelivered messages
## This plugin uses tracking metrics, which ensure messages are read to
## outputs before acknowledging them to the original broker to ensure data
## is not lost. This option sets the maximum messages to read from the
## broker that have not been written by an output.
##
## This value needs to be picked with awareness of the agent's
## metric_batch_size value as well. Setting max undelivered messages too high
## can result in a constant stream of data batches to the output. While
## setting it too low may never flush the broker's messages.
# max_undelivered_messages = 1000
## Data format to consume.
## Each data format has its own unique set of configuration options, read
## more about them here:
## https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_INPUT.md
data_format = "influx"
SQLite
[[outputs.sql]]
## Database driver
## Valid options: mssql (Microsoft SQL Server), mysql (MySQL), pgx (Postgres),
## sqlite (SQLite3), snowflake (snowflake.com), clickhouse (ClickHouse)
driver = "sqlite"
## Data source name
## For SQLite, the DSN is a filename or URL with the scheme "file:".
## Example: "file:/path/to/telegraf.db?cache=shared"
data_source_name = "file:/path/to/telegraf.db?cache=shared"
## 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} - table name as a quoted identifier
table_exists_template = "SELECT 1 FROM {TABLE} LIMIT 1"
## Initialization SQL (optional)
init_sql = ""
## 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
## 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 SQL types used when writing to SQLite.
#[outputs.sql.convert]
# integer = "INT"
# real = "DOUBLE"
# text = "TEXT"
# timestamp = "TIMESTAMP"
# defaultvalue = "TEXT"
# unsigned = "UNSIGNED"
# bool = "BOOL"
Input and output integration examples
NATS
-
Real-Time Analytics Dashboard: Utilize the NATS plugin to gather metrics from various NATS subjects in real time and feed them into a centralized analytics dashboard. This setup allows for immediate visibility into live application performance, enabling teams to react swiftly to operational issues or performance degradation.
-
Distributed System Monitoring: Deploy multiple instances of Telegraf configured with the NATS plugin across a distributed architecture. This approach allows teams to aggregate metrics from various microservices efficiently, providing a holistic view of system health and performance while ensuring no messages are dropped during transmission.
-
Historical Message Recovery: Leverage the capabilities of NATS JetStream along with this plugin to recover and process historical messages after Telegraf has been restarted. This feature is particularly beneficial for applications that require high reliability, ensuring that no critical metrics are lost even in case of service disruptions.
-
Dynamic Load Balancing: Implement a dynamic load balancing scenario where Telegraf instances consume messages from a NATS cluster based on load. Adjust the queue group settings to control the number of active consumers, allowing for better resource utilization and performance scaling as demand fluctuations occur.
SQLite
- Local Monitoring Storage: Configure the plugin to write metrics to a local SQLite database file. This is ideal for lightweight deployments where setting up a full-scale database server is not required.
- Embedded Applications: Use SQLite as the backend for applications embedded in edge devices, benefiting from its file-based architecture and minimal resource requirements.
- Quick Setup for Testing: Leverage SQLite’s ease of use to quickly set up a testing environment for Telegraf metrics collection without the need for external database services.
- Custom Schema Management: Adjust the table creation templates to predefine your schema if you require specific column types or indexes, ensuring compatibility with your application’s needs.
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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