LDAP and Graphite Integration
Powerful performance with an easy integration, powered by Telegraf, the open source data connector built by InfluxData.
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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
Input and output integration overview
The LDAP plugin collects monitoring metrics from LDAP servers, including OpenLDAP and 389 Directory Server. This plugin is essential for tracking the performance and health of LDAP services, enabling administrators to gain insights into their directory operations.
The Graphite plugin enables users to send metrics collected by Telegraf into Graphite via TCP. This integration allows for efficient storage and visualization of time-series data using Graphite’s powerful capabilities.
Integration details
LDAP
This plugin gathers metrics from LDAP servers’ monitoring backend, specifically from the cn=Monitor
entries. It supports two prominent LDAP implementations: OpenLDAP and 389 Directory Server (389ds). With a focus on collecting various operational metrics, the LDAP plugin enables administrators to monitor performance, connection status, and server health in real-time, which is vital for maintaining robust directory services. By allowing customizable connection parameters and security configurations, such as TLS support, the plugin ensures compliance with best practices for security and performance. Metrics gathered can be instrumental in identifying trends, optimizing server configurations, and enforcing service-level agreements with stakeholders.
Graphite
This plugin writes metrics to Graphite via raw TCP, allowing for seamless integration of Telegraf collected metrics into the Graphite ecosystem. With this plugin, users can configure multiple TCP endpoints for load balancing, ensuring high availability and reliability in metric transmission. The ability to customize metric naming with prefixes and utilize various templating options enhances flexibility in how data is represented within Graphite. Additionally, support for Graphite tags and options for strict sanitization of metric names allow for robust data management, catering to the varying needs of users. This capability is essential for organizations looking to leverage Graphite’s powerful metrics storage and visualization while maintaining control over data representation.
Configuration
LDAP
[[inputs.ldap]]
## Server to monitor
## The scheme determines the mode to use for connection with
## ldap://... -- unencrypted (non-TLS) connection
## ldaps://... -- TLS connection
## starttls://... -- StartTLS connection
## If no port is given, the default ports, 389 for ldap and starttls and
## 636 for ldaps, are used.
server = "ldap://localhost"
## Server dialect, can be "openldap" or "389ds"
# dialect = "openldap"
# DN and password to bind with
## If bind_dn is empty an anonymous bind is performed.
bind_dn = ""
bind_password = ""
## Reverse the field names constructed from the monitoring DN
# reverse_field_names = false
## Optional TLS Config
## Set to true/false to enforce TLS being enabled/disabled. If not set,
## enable TLS only if any of the other options are specified.
# tls_enable =
## Trusted root certificates for server
# tls_ca = "/path/to/cafile"
## Used for TLS client certificate authentication
# tls_cert = "/path/to/certfile"
## Used for TLS client certificate authentication
# tls_key = "/path/to/keyfile"
## Password for the key file if it is encrypted
# tls_key_pwd = ""
## Send the specified TLS server name via SNI
# tls_server_name = "kubernetes.example.com"
## Minimal TLS version to accept by the client
# tls_min_version = "TLS12"
## List of ciphers to accept, by default all secure ciphers will be accepted
## See https://pkg.go.dev/crypto/tls#pkg-constants for supported values.
## Use "all", "secure" and "insecure" to add all support ciphers, secure
## suites or insecure suites respectively.
# tls_cipher_suites = ["secure"]
## Renegotiation method, "never", "once" or "freely"
# tls_renegotiation_method = "never"
## Use TLS but skip chain & host verification
# insecure_skip_verify = false
Graphite
# Configuration for Graphite server to send metrics to
[[outputs.graphite]]
## TCP endpoint for your graphite instance.
## If multiple endpoints are configured, the output will be load balanced.
## Only one of the endpoints will be written to with each iteration.
servers = ["localhost:2003"]
## Local address to bind when connecting to the server
## If empty or not set, the local address is automatically chosen.
# local_address = ""
## Prefix metrics name
prefix = ""
## Graphite output template
## see https://github.com/influxdata/telegraf/blob/master/docs/DATA_FORMATS_OUTPUT.md
template = "host.tags.measurement.field"
## Strict sanitization regex
## This is the default sanitization regex that is used on data passed to the
## graphite serializer. Users can add additional characters here if required.
## Be aware that the characters, '/' '@' '*' are always replaced with '_',
## '..' is replaced with '.', and '\' is removed even if added to the
## following regex.
# graphite_strict_sanitize_regex = '[^a-zA-Z0-9-:._=\p{L}]'
## Enable Graphite tags support
# graphite_tag_support = false
## Applied sanitization mode when graphite tag support is enabled.
## * strict - uses the regex specified above
## * compatible - allows for greater number of characters
# graphite_tag_sanitize_mode = "strict"
## Character for separating metric name and field for Graphite tags
# graphite_separator = "."
## Graphite templates patterns
## 1. Template for cpu
## 2. Template for disk*
## 3. Default template
# templates = [
# "cpu tags.measurement.host.field",
# "disk* measurement.field",
# "host.measurement.tags.field"
#]
## timeout in seconds for the write connection to graphite
# timeout = "2s"
## 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
Input and output integration examples
LDAP
-
Monitoring Directory Performance: Use the LDAP Telegraf plugin to continuously track and analyze the number of operations completed, initiated connections, and server response times. By visualizing this data over time, administrators can identify performance bottlenecks in directory services, enabling proactive optimization.
-
Alerting on Security Events: Integrate the plugin with an alerting system to notify administrators when certain metrics, such as
bind_security_errors
orunauth_binds
, exceed predefined thresholds. This setup can enhance security monitoring by providing real-time insights into potential unauthorized access attempts. -
Capacity Planning: Leverage the metrics collected by the LDAP plugin to perform capacity planning. Analyze connection trends, maximum threads in use, and operational statistics to forecast future resource needs, ensuring the LDAP server can handle expected peak loads without degrading performance.
-
Compliance and Auditing: Use the operational metrics obtained via this plugin to assist in compliance audits. By regularly checking metrics like
anonymous_binds
andsecurity_errors
, organizations can ensure that their directory services adhere to security policies and regulatory requirements.
Graphite
-
Dynamic Metric Visualization: The Graphite plugin can be utilized to feed real-time metrics from various sources, such as application performance data or server health metrics, into Graphite. This dynamic integration allows teams to create interactive dashboards that visualize key performance indicators, track trends over time, and make data-driven decisions to enhance system performance.
-
Load Balanced Metrics Collection: By configuring multiple TCP endpoints within the plugin, organizations can implement load balancing for metric transmission. This use case ensures that metric delivery is both resilient and efficient, reducing the risk of data loss during high-traffic periods and maintaining a reliable flow of information to Graphite.
-
Customized Metrics Tagging: With support for Graphite tags, users can employ the Graphite plugin to enhance the granularity of their metrics. Tagging metrics with relevant information, such as application environment or service type, allows for more refined queries and analytics, enabling teams to drill down into specific areas of interest for better operational insights.
-
Enhanced Data Sanitization: Leveraging the plugin’s strict sanitization options, users can ensure that their metric names comply with Graphite’s requirements. This proactive measure eliminates potential issues arising from invalid characters in metric names, allowing for cleaner data management and more accurate visualizations.
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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