OpenStack and Snowflake 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
This plugin collects metrics from essential OpenStack services, facilitating the monitoring and management of cloud infrastructures.
Telegraf’s SQL plugin allows seamless metric storage in SQL databases. When configured for Snowflake, it employs a specialized DSN format and dynamic table creation to map metrics to the appropriate schema.
Integration details
OpenStack
The OpenStack plugin allows users to collect performance metrics from various OpenStack services such as CINDER, GLANCE, HEAT, KEYSTONE, NEUTRON, and NOVA. It supports multiple OpenStack APIs to fetch critical metrics related to these services, enabling comprehensive monitoring and management of cloud resources. As organizations increasingly adopt OpenStack for their cloud infrastructure, this plugin plays a vital role in providing insights into resource usage, availability, and performance across the cloud environment. Configuration options allow for customized polling intervals and filtering unwanted tags to optimize performance and cardinals.
Snowflake
Telegraf’s SQL plugin is engineered to dynamically write metrics into an SQL database by creating tables and columns based on the incoming data. When configured for Snowflake, it employs the gosnowflake driver, which uses a DSN that encapsulates credentials, account details, and database configuration in a compact format. This setup allows for the automatic generation of tables where each metric is recorded with precise timestamps, thereby ensuring detailed historical tracking. Although the integration is considered experimental, it leverages Snowflake’s powerful data warehousing capabilities, making it suitable for scalable, cloud-based analytics and reporting solutions.
Configuration
OpenStack
[[inputs.openstack]]
## The recommended interval to poll is '30m'
## The identity endpoint to authenticate against and get the service catalog from.
authentication_endpoint = "https://my.openstack.cloud:5000"
## The domain to authenticate against when using a V3 identity endpoint.
# domain = "default"
## The project to authenticate as.
# project = "admin"
## User authentication credentials. Must have admin rights.
username = "admin"
password = "password"
## Available services are:
## "agents", "aggregates", "cinder_services", "flavors", "hypervisors",
## "networks", "nova_services", "ports", "projects", "servers",
## "serverdiagnostics", "services", "stacks", "storage_pools", "subnets",
## "volumes"
# enabled_services = ["services", "projects", "hypervisors", "flavors", "networks", "volumes"]
## Query all instances of all tenants for the volumes and server services
## NOTE: Usually this is only permitted for administrators!
# query_all_tenants = true
## output secrets (such as adminPass(for server) and UserID(for volume)).
# output_secrets = false
## Amount of time allowed to complete the HTTP(s) request.
# timeout = "5s"
## HTTP Proxy support
# http_proxy_url = ""
## Optional TLS Config
# tls_ca = /path/to/cafile
# tls_cert = /path/to/certfile
# tls_key = /path/to/keyfile
## Use TLS but skip chain & host verification
# insecure_skip_verify = false
## Options for tags received from Openstack
# tag_prefix = "openstack_tag_"
# tag_value = "true"
## Timestamp format for timestamp data received from Openstack.
## If false format is unix nanoseconds.
# human_readable_timestamps = false
## Measure Openstack call duration
# measure_openstack_requests = false
Snowflake
[[outputs.sql]]
## Database driver
## Valid options: mssql (Microsoft SQL Server), mysql (MySQL), pgx (Postgres),
## sqlite (SQLite3), snowflake (snowflake.com), clickhouse (ClickHouse)
driver = "snowflake"
## Data source name
## For Snowflake, the DSN format typically includes the username, password, account identifier, and optional warehouse, database, and schema.
## Example DSN: "username:password@account/warehouse/db/schema"
data_source_name = "username:password@account/warehouse/db/schema"
## 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
## Defaults to ANSI/ISO SQL types unless overridden. Adjust if needed for Snowflake compatibility.
#[outputs.sql.convert]
# integer = "INT"
# real = "DOUBLE"
# text = "TEXT"
# timestamp = "TIMESTAMP"
# defaultvalue = "TEXT"
# unsigned = "UNSIGNED"
# bool = "BOOL"
Input and output integration examples
OpenStack
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Cross-Cloud Management: Leverage the OpenStack plugin to monitor and manage multiple OpenStack clouds from a single Telegraf instance. By aggregating metrics across different clouds, organizations can gain insights into resource utilization and optimize their cloud architecture for cost and performance.
-
Automated Scaling Based on Metrics: Integrate the metrics gathered from OpenStack into an automated scaling solution. For example, if the plugin detects that a specific service’s performance is degraded, it can trigger auto-scaling rules to launch additional instances, ensuring that system performance remains optimal under varying workloads.
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Performance Monitoring Dashboard: Use data collected by the OpenStack Telegraf plugin to power real-time monitoring dashboards. This setup provides visualizations of key metrics from OpenStack services, enabling stakeholders to quickly identify trends, pinpoint issues, and make data-driven decisions in managing their cloud infrastructure.
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Reporting and Analysis of Service Availability: By utilizing the metrics collected from various OpenStack services, teams can generate detailed reports on service availability and performance over time. This information can help identify recurring issues, improve service delivery, and make informed decisions regarding changes in infrastructure or service configuration.
Snowflake
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Cloud-Based Data Lake Integration: Utilize the plugin to stream real-time metrics from various sources into Snowflake, enabling the creation of a centralized data lake. This integration supports complex analytics and machine learning workflows on cloud data.
-
Dynamic Business Intelligence Dashboards: Leverage the plugin to automatically generate tables from incoming metrics and feed them into BI tools. This allows businesses to create dynamic dashboards that visualize performance trends and operational insights without manual schema management.
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Scalable IoT Analytics: Deploy the plugin to capture high-frequency data from IoT devices into Snowflake. This use case facilitates the aggregation and analysis of sensor data, enabling predictive maintenance and real-time monitoring at scale.
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Historical Trend Analysis for Compliance: Use the plugin to log and archive detailed metric data in Snowflake, which can then be queried for long-term trend analysis and compliance reporting. This setup ensures that organizations can maintain a robust audit trail and perform forensic analysis if needed.
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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