HAProxy and Mimir Integration
Powerful performance with an easy integration, powered by Telegraf, the open source data connector built by InfluxData.
5B+
Telegraf downloads
#1
Time series database
Source: DB Engines
1B+
Downloads of InfluxDB
2,800+
Contributors
Table of Contents
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
This plugin gathers and reports statistics from HAProxy, a popular open-source load balancer and proxy server, to help in monitoring and optimizing its performance.
This plugin sends Telegraf metrics directly to Grafana’s Mimir database using HTTP, providing scalable and efficient long-term storage and analysis for Prometheus-compatible metrics.
Integration details
HAProxy
The HAProxy plugin for Telegraf enables users to gather statistics directly from a HAProxy server via its stats socket or HTTP statistics page. HAProxy is a widely employed software load balancer and proxy server that provides high availability and performance for TCP and HTTP applications. By integrating with HAProxy, this plugin allows users to monitor and analyze various performance metrics such as active server counts, request rates, response codes, and session statuses in real-time, facilitating better decision-making and proactive management of network resources. Key features include support for both HTTP and socket-based metrics collection, compatibility with basic authentication for secure access, and configurable options for metric field naming, allowing for customization tailored to user preferences.
Mimir
Grafana Mimir supports the Prometheus Remote Write protocol, enabling Telegraf collected metrics to be efficiently ingested into Mimir clusters for large-scale, long-term storage. This integration leverages Prometheus’s well-established standards, allowing users to combine Telegraf’s extensive data collection capabilities with Mimir’s advanced features, such as query federation, multi-tenancy, high availability, and cost-efficient storage. Grafana Mimir’s architecture is optimized for handling high volumes of metric data and delivering fast query responses, making it ideal for complex monitoring environments and distributed systems.
Configuration
HAProxy
[[inputs.haproxy]]
## List of stats endpoints. Metrics can be collected from both http and socket
## endpoints. Examples of valid endpoints:
## - http://myhaproxy.com:1936/haproxy?stats
## - https://myhaproxy.com:8000/stats
## - socket:/run/haproxy/admin.sock
## - /run/haproxy/*.sock
## - tcp://127.0.0.1:1936
##
## Server addresses not starting with 'http://', 'https://', 'tcp://' will be
## treated as possible sockets. When specifying local socket, glob patterns are
## supported.
servers = ["http://myhaproxy.com:1936/haproxy?stats"]
## By default, some of the fields are renamed from what haproxy calls them.
## Setting this option to true results in the plugin keeping the original
## field names.
# keep_field_names = 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
Mimir
[[outputs.http]]
url = "http://data-load-balancer-backend-1:9009/api/v1/push"
data_format = "prometheusremotewrite"
username = "*****"
password = "******"
[outputs.http.headers]
Content-Type = "application/x-protobuf"
Content-Encoding = "snappy"
X-Scope-OrgID = "****"
Input and output integration examples
HAProxy
-
Dynamic Load Adjustment: Utilize the HAProxy plugin to monitor traffic patterns in real time, enabling automated adjustments to load balancing algorithms. By continuously gathering metrics on server loads and request rates, system administrators can dynamically allocate resources, ensuring that no single server becomes a bottleneck, thus enhancing overall application performance and availability.
-
Historical Performance Analytics: Integrate this plugin with a time series database to collect HAProxy metrics over time, allowing you to analyze historical performance and traffic trends. This can facilitate predictive analysis and planning for capacity, giving businesses insights into peak traffic times and helping to identify potential future resource needs.
-
Alerting on Anomalies: Implement alerting workflows that trigger when unusual patterns are detected in HAProxy metrics, such as sudden spikes in error rates or drops in request handling capacity. By leveraging this plugin, operations teams can receive timely notifications, allowing for swift intervention and minimizing the impact of potential downtime on end-users.
Mimir
-
Enterprise-Scale Kubernetes Monitoring: Integrate Telegraf with Grafana Mimir to stream metrics from Kubernetes clusters at enterprise scale. This enables comprehensive visibility, improved resource allocation, and proactive troubleshooting across hundreds of clusters, leveraging Mimir’s horizontal scalability and high availability.
-
Multi-tenant SaaS Application Observability: Use this plugin to centralize metrics from diverse SaaS tenants into Grafana Mimir, enabling tenant isolation and accurate billing based on resource usage. This approach provides reliable observability, efficient cost management, and secure multi-tenancy support.
-
Global Edge Network Performance Tracking: Stream latency and availability metrics from globally distributed edge servers into Grafana Mimir. Organizations can quickly identify performance degradation or outages, leveraging Mimir’s fast querying capabilities to ensure optimal service reliability and user experience.
-
Real-Time Analytics for High-Volume Microservices: Implement Telegraf metrics collection in high-volume microservices architectures, feeding data into Grafana Mimir for real-time analytics and anomaly detection. Mimir’s powerful querying enables teams to detect anomalies and quickly respond, maintaining high service availability and performance.
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
Related Integrations
Related Integrations
HTTP and InfluxDB Integration
The HTTP plugin collects metrics from one or more HTTP(S) endpoints. It supports various authentication methods and configuration options for data formats.
View IntegrationKafka and InfluxDB Integration
This plugin reads messages from Kafka and allows the creation of metrics based on those messages. It supports various configurations including different Kafka settings and message processing options.
View IntegrationKinesis and InfluxDB Integration
The Kinesis plugin allows for reading metrics from AWS Kinesis streams. It supports multiple input data formats and offers checkpointing features with DynamoDB for reliable message processing.
View Integration