Hashicorp Vault and Loki Integration
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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
The Hashicorp Vault plugin for Telegraf allows for the collection of metrics from Hashicorp Vault services, facilitating monitoring and operational insights.
The Loki plugin allows users to send logs to Loki for aggregation and querying, leveraging Loki’s efficient storage capabilities.
Integration details
Hashicorp Vault
The Hashicorp Vault plugin is designed to collect metrics from Vault agents running within a cluster. It enables Telegraf, an agent for collecting and reporting metrics, to interface with the Vault services, typically listening on a local address such as http://127.0.0.1:8200
. This plugin requires a valid token for authorization, ensuring secure access to the Vault API. Users must configure either a token directly or provide a path to a token file, enhancing flexibility in authentication methods. Proper configuration of the timeout and optional TLS settings further relates to the security and responsiveness of the metrics collection process. As Vault is a critical tool in managing secrets and protecting sensitive data, monitoring its performance and health through this plugin is essential for maintaining operational security 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
Hashicorp Vault
[[inputs.vault]]
## URL for the Vault agent
# url = "http://127.0.0.1:8200"
## Use Vault token for authorization.
## Vault token configuration is mandatory.
## If both are empty or both are set, an error is thrown.
# token_file = "/path/to/auth/token"
## OR
token = "s.CDDrgg5zPv5ssI0Z2P4qxJj2"
## Set response_timeout (default 5 seconds)
# response_timeout = "5s"
## Optional TLS Config
# tls_ca = /path/to/cafile
# tls_cert = /path/to/certfile
# tls_key = /path/to/keyfile
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
Hashicorp Vault
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Centralized Secret Management Monitoring: Utilize the Vault plugin to monitor multiple Vault instances across a distributed system, allowing for a unified view of secret access patterns and system health. This setup can help DevOps teams quickly identify any anomalies in secret access, providing essential insights into security postures across different environments.
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Audit Logging Integration: Configure this plugin to feed monitoring metrics into an audit logging system, enabling organizations to have a comprehensive view of their Vault interactions. By correlating audit logs with metrics, teams can investigate issues, optimize performance, and ensure compliance with security policies more effectively.
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Performance Benchmarking During Deployments: During application deployments that interact with Vault, use the plugin to monitor the effects of those deployments on Vault performance. This allows engineering teams to understand how changes impact secret management workflows and to proactively address performance bottlenecks, ensuring smooth deployment processes.
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Alerting for Threshold Exceedance: Integrate this plugin with alerting mechanisms to notify administrators when metrics exceed predefined thresholds. This proactive monitoring can help teams respond swiftly to potential issues, maintaining system reliability and uptime by allowing them to take action before any serious incidents arise.
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
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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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