Memcached and Loki 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.
See Ways to Get Started
Input and output integration overview
This plugin gathers statistics data from a Memcached server.
The Loki plugin allows users to send logs to Loki for aggregation and querying, leveraging Loki’s efficient storage capabilities.
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.
Loki
This Loki plugin integrates with Grafana Loki, a powerful log aggregation system. By sending logs in a format compatible with Loki, this plugin allows for efficient storage and querying of logs. Each log entry is structured in a key-value format where keys represent the field names and values represent the corresponding log information. The sorting of logs by timestamp ensures that the log streams maintain chronological order when queried through Loki. This plugin’s support for secrets makes it easier to manage authentication parameters securely, while options for HTTP headers, gzip encoding, and TLS configuration enhance the adaptability and security of log transmission, fitting various deployment needs.
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
Loki
[[outputs.loki]]
## The domain of Loki
domain = "https://loki.domain.tld"
## Endpoint to write api
# endpoint = "/loki/api/v1/push"
## Connection timeout, defaults to "5s" if not set.
# timeout = "5s"
## Basic auth credential
# username = "loki"
# password = "pass"
## Additional HTTP headers
# http_headers = {"X-Scope-OrgID" = "1"}
## If the request must be gzip encoded
# gzip_request = false
## Optional TLS Config
# tls_ca = "/etc/telegraf/ca.pem"
# tls_cert = "/etc/telegraf/cert.pem"
# tls_key = "/etc/telegraf/key.pem"
## Sanitize Tag Names
## If true, all tag names will have invalid characters replaced with
## underscores that do not match the regex: ^[a-zA-Z_:][a-zA-Z0-9_:]*.
# sanitize_label_names = false
## Metric Name Label
## Label to use for the metric name to when sending metrics. If set to an
## empty string, this will not add the label. This is NOT suggested as there
## is no way to differentiate between multiple metrics.
# metric_name_label = "__name"
Input and output integration examples
Memcached
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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.
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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.
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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.
Loki
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Centralized Logging for Microservices: Utilize the Loki plugin to gather logs from multiple microservices running in a Kubernetes cluster. By directing logs to a centralized Loki instance, developers can monitor, search, and analyze logs from all services in one place, facilitating easier troubleshooting and performance monitoring. This setup streamlines operations and supports rapid response to issues across distributed applications.
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Real-Time Log Anomaly Detection: Combine Loki with monitoring tools to analyze log outputs in real-time for unusual patterns that could indicate system errors or security threats. Implementing anomaly detection on log streams enables teams to proactively identify and respond to incidents, thereby improving system reliability and enhancing security postures.
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Enhanced Log Processing with Gzip Compression: Configure the Loki plugin to utilize gzip compression for log transmission. This approach can reduce bandwidth usage and improve transmission speeds, especially beneficial in environments where network bandwidth may be a constraint. It’s particularly useful for high-volume logging applications where every byte counts and performance is critical.
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Multi-Tenancy Support with Custom Headers: Leverage the ability to add custom HTTP headers to segregate logs from different tenants in a multi-tenant application environment. By using the Loki plugin to send different headers for each tenant, operators can ensure proper log management and compliance with data isolation requirements, making it a versatile solution for SaaS applications.
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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