OpenStack and Clarify 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.
The Clarify plugin allows users to publish Telegraf metrics directly to Clarify, enabling enhanced analysis and monitoring capabilities.
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.
Clarify
This plugin facilitates the writing of Telegraf metrics to Clarify, a platform for managing and analyzing time series data. By transforming metrics into Clarify signals, this output plugin enables seamless integration of collected telemetry data into the Clarify ecosystem. Users must obtain valid credentials, either through a credentials file or basic authentication, to configure the plugin. The configuration also provides options for fine-tuning how metrics are mapped to signals in Clarify, including the ability to specify unique identifiers using tags. Given that Clarify supports only floating point values, the plugin ensures that any unsupported types are effectively filtered out during the publishing process. This comprehensive connectivity aligns with use cases in monitoring, data analysis, and operational insights.
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
Clarify
[[outputs.clarify]]
## Credentials File (Oauth 2.0 from Clarify integration)
credentials_file = "/path/to/clarify/credentials.json"
## Clarify username password (Basic Auth from Clarify integration)
username = "i-am-bob"
password = "secret-password"
## Timeout for Clarify operations
# timeout = "20s"
## Optional tags to be included when generating the unique ID for a signal in Clarify
# id_tags = []
# clarify_id_tag = 'clarify_input_id'
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.
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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.
Clarify
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Automated Data Monitoring: By integrating the Clarify plugin with sensor data collection, organizations can automate the monitoring of environmental conditions, such as temperature and humidity. The plugin processes metrics in real-time, sending updates to Clarify where they can be analyzed for trends, alerts, and historical tracking. This use case makes it easier to maintain optimal conditions in data centers or production environments, reducing the risk of equipment failures.
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Performance Metrics Analysis: Companies can leverage this plugin to send application performance metrics to Clarify. By transmitting key indicators such as response times and error rates, developers and operations teams can utilize Clarify’s capabilities to visualize and analyze application performance over time. This insight can drive improvements in user experience and help identify areas in need of optimization.
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Sensor Data Aggregation: Utilizing the plugin to push data from multiple sensors to Clarify allows for a comprehensive view of physical environments. This aggregation is particularly beneficial in sectors such as agriculture, where metrics from various sensors can be correlated to decision-making about resource allocations, pest control, and crop management. The plugin ensures the data is accurately mapped and transformed for effective analysis.
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Real-Time Alerts and Notifications: Implement the Clarify plugin to trigger real-time alerts based on predefined thresholds within the metrics being sent. For instance, if temperature readings exceed certain levels, alerts can be generated and sent to operational staff. This proactive approach allows for immediate responses to potential issues, enhancing operational reliability and safety.
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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