Consul and Google BigQuery 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 Consul Input Plugin collects health check metrics from a Consul server, allowing users to monitor service statuses effectively.
The Google BigQuery plugin allows Telegraf to write metrics to Google Cloud BigQuery, enabling robust data analytics capabilities for telemetry data.
Integration details
Consul
The Consul Input Plugin is designed to gather health check statuses from all services registered with Consul, a tool for service discovery and infrastructure management. By querying the Consul API, this plugin helps users monitor the health of their services and ensure that they are operational and meeting service level agreements. It does not provide telemetry data, but users can utilize StatsD if they want to collect those metrics. The plugin offers configuration options to connect to the Consul server, manage authentication, and specify how to handle tags derived from health checks.
Google BigQuery
The Google BigQuery plugin for Telegraf enables seamless integration with Google Cloud’s BigQuery service, a popular data warehousing and analytics platform. This plugin facilitates the transfer of metrics collected by Telegraf into BigQuery datasets, making it easier for users to perform analyses and generate insights from their telemetry data. It requires authentication through a service account or user credentials and is designed to handle various data types, ensuring that users can maintain the integrity and accuracy of their metrics as they are stored in BigQuery tables. The configuration options allow for customization around dataset specifications and handling metrics, including the management of hyphens in metric names, which are not supported by BigQuery for streaming inserts. This plugin is particularly useful for organizations leveraging the scalability and powerful query capabilities of BigQuery to analyze large volumes of monitoring data.
Configuration
Consul
[[inputs.consul]]
## Consul server address
# address = "localhost:8500"
## URI scheme for the Consul server, one of "http", "https"
# scheme = "http"
## Metric version controls the mapping from Consul metrics into
## Telegraf metrics. Version 2 moved all fields with string values
## to tags.
##
## example: metric_version = 1; deprecated in 1.16
## metric_version = 2; recommended version
# metric_version = 1
## ACL token used in every request
# token = ""
## HTTP Basic Authentication username and password.
# username = ""
# password = ""
## Data center to query the health checks from
# datacenter = ""
## 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 = true
## Consul checks' tag splitting
# When tags are formatted like "key:value" with ":" as a delimiter then
# they will be split and reported as proper key:value in Telegraf
# tag_delimiter = ":"
Google BigQuery
# Configuration for Google Cloud BigQuery to send entries
[[outputs.bigquery]]
## Credentials File
credentials_file = "/path/to/service/account/key.json"
## Google Cloud Platform Project
# project = ""
## The namespace for the metric descriptor
dataset = "telegraf"
## Timeout for BigQuery operations.
# timeout = "5s"
## Character to replace hyphens on Metric name
# replace_hyphen_to = "_"
## Write all metrics in a single compact table
# compact_table = ""
Input and output integration examples
Consul
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Service Health Monitoring Dashboard: Utilize the Consul Input Plugin to create a comprehensive health monitoring dashboard for all services registered with Consul. This allows operations teams to visualize the health status in real time, enabling quick identification of service issues and facilitating rapid responses to service outages or performance degradation.
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Automated Alerting System: Implement an automated alerting system that uses the health check data gathered by the Consul Input Plugin to trigger notifications whenever a service status changes to critical. This setup can integrate with notification systems like Slack or email, ensuring that team members are alerted immediately to address potential issues.
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Integration with Incident Management: Leverage the health check data from the Consul Input Plugin to feed into incident management systems. By analyzing the health status trends, teams can prioritize incidents based on the criticality of the affected services and streamline their resolution processes, improving overall service reliability and customer satisfaction.
Google BigQuery
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Real-Time Analytics Dashboard: Leverage the Google BigQuery plugin to feed live metrics into a custom analytics dashboard hosted on Google Cloud. This setup would allow teams to visualize performance data in real-time, providing insights into system health and usage patterns. By using BigQuery’s querying capabilities, users can easily create tailored reports and dashboards to meet their specific needs, thus enhancing decision-making processes.
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Cost Management and Optimization Analysis: Utilize the plugin to automatically send cost-related metrics from various services into BigQuery. Analyzing this data can help businesses identify unnecessary expenses and optimize resource usage. By performing aggregation and transformation queries in BigQuery, organizations can create accurate forecasts and manage their cloud spending efficiently.
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Cross-Team Collaboration on Monitoring Data: Enable different teams within an organization to share their monitoring data using BigQuery. With the help of this Telegraf plugin, teams can push their metrics to a central BigQuery instance, fostering collaboration. This data-sharing approach encourages best practices and cross-functional awareness, leading to collective improvements in system performance and reliability.
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Historical Analysis for Capacity Planning: By using the BigQuery plugin, companies can collect and store historical metrics data essential for capacity planning. Analyzing trends over time can help anticipate system needs and scale infrastructure proactively. Organizations can create time-series analyses and identify patterns that inform their long-term strategic decisions.
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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