Memcached and Cortex Integration
Powerful performance with an easy integration, powered by Telegraf, the open source data connector built by InfluxData.
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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.
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Input and output integration overview
This plugin gathers statistics data from a Memcached server.
This plugin enables Telegraf to send metrics to Cortex using the Prometheus remote write protocol, allowing seamless ingestion into Cortex’s scalable, multi-tenant time series storage.
Integration details
Memcached
The Telegraf Memcached plugin is designed to gather statistics data from Memcached servers, allowing users to monitor the performance and health of their caching layer. Memcached, a distributed memory caching system, is commonly used for speeding up dynamic web applications by alleviating database load and storing frequently accessed data in memory for quick retrieval. This plugin collects various metrics such as the number of connections, bytes used, and hits/misses, enabling administrators to analyze cache performance, troubleshoot issues, and optimize resource allocation. The configuration supports multiple Memcached server addresses and offers optional TLS settings, ensuring flexibility and secure data transmission across the network. By leveraging this plugin, organizations can gain insights into their caching strategies and improve application responsiveness and efficiency.
Cortex
With Telegraf’s HTTP output plugin and the prometheusremotewrite
data format you can send metrics directly to Cortex, a horizontally scalable, long-term storage backend for Prometheus. Cortex supports multi-tenancy and accepts remote write requests using the Prometheus protobuf format. By using Telegraf as the collection agent and Remote Write as the transport mechanism, organizations can extend observability into sources not natively supported by Prometheus—such as Windows hosts, SNMP-enabled devices, or custom application metrics—while leveraging Cortex’s high-availability and long-retention capabilities.
Configuration
Memcached
[[inputs.memcached]]
# An array of address to gather stats about. Specify an ip on hostname
# with optional port. ie localhost, 10.0.0.1:11211, etc.
servers = ["localhost:11211"]
# An array of unix memcached sockets to gather stats about.
# unix_sockets = ["/var/run/memcached.sock"]
## Optional TLS Config
# enable_tls = false
# tls_ca = "/etc/telegraf/ca.pem"
# tls_cert = "/etc/telegraf/cert.pem"
# tls_key = "/etc/telegraf/key.pem"
## If false, skip chain & host verification
# insecure_skip_verify = true
Cortex
[[outputs.http]]
## Cortex Remote Write endpoint
url = "http://cortex.example.com/api/v1/push"
## Use POST to send data
method = "POST"
## Send metrics using Prometheus remote write format
data_format = "prometheusremotewrite"
## Optional HTTP headers for authentication
# [outputs.http.headers]
# X-Scope-OrgID = "your-tenant-id"
# Authorization = "Bearer YOUR_API_TOKEN"
## Optional TLS configuration
# tls_ca = "/path/to/ca.pem"
# tls_cert = "/path/to/cert.pem"
# tls_key = "/path/to/key.pem"
# insecure_skip_verify = false
## Request timeout
timeout = "10s"
Input and output integration examples
Memcached
-
Dynamic Cache Performance Monitoring: Use the Memcached plugin to set up a performance monitoring dashboard that displays real-time statistics about cache hit ratios, connection counts, and memory usage. This setup can help developers and system admins quickly identify performance bottlenecks and optimize caching strategies to improve application speed.
-
Alerting on Cache Performance Metrics: Implement an alerting system that triggers notifications whenever certain thresholds are breached, such as a decrease in cache hit rates or an increase in rejected connections. This proactive approach can help teams respond to potential issues before they affect user experience and maintain optimal application performance.
-
Integrating Cache Metrics with Business Analytics: Combine Memcached metrics with business intelligence tools to analyze the impact of caching on user engagement and transaction volumes. By correlating cache performance with key business metrics, teams can derive insights into how caching strategies contribute to overall business objectives and improve decision-making processes.
Cortex
-
Unified Multi-Tenant Monitoring: Use Telegraf to collect metrics from different teams or environments and push them to Cortex with separate
X-Scope-OrgID
headers. This enables isolated data ingestion and querying per tenant, ideal for managed services and platform teams. -
Extending Prometheus Coverage to Edge Devices: Deploy Telegraf on edge or IoT devices to collect system metrics and send them to a centralized Cortex cluster. This approach ensures consistent observability even for environments without local Prometheus scrapers.
-
Global Service Observability with Federated Tenants: Aggregate metrics from global infrastructure by configuring Telegraf agents to push data into regional Cortex clusters, each tagged with tenant identifiers. Cortex handles deduplication and centralized access across regions.
-
Custom App Telemetry Pipeline: Collect app-specific telemetry via Telegraf’s
exec
orhttp
input plugins and forward it to Cortex. This allows DevOps teams to monitor app-specific KPIs in a scalable, query-efficient format while keeping metrics logically grouped by tenant or service.
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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