Ceph and Nebius Cloud Monitoring 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
The Ceph plugin for Telegraf helps in gathering performance metrics from both MON and OSD nodes in a Ceph storage cluster for effective monitoring and management.
This plugin allows users to effortlessly send aggregated metrics to Nebius Cloud Monitoring, leveraging the cloud’s monitoring solutions.
Integration details
Ceph
The Ceph Storage Telegraf plugin is designed to collect performance metrics from Monitor (MON) and Object Storage Daemon (OSD) nodes within a Ceph storage cluster. Ceph, a highly scalable storage system, integrates its metrics collection through this plugin, facilitating easy monitoring of its components. With the introduction of this plugin in the 13.x Mimic release, users can effectively gather detailed insights into the performance and health of their Ceph infrastructure. It functions by scanning configured socket directories for specific Ceph service socket files, executing commands via the Ceph administrative interface, and parsing the returned JSON data for metrics. The metrics are organized based on top-level keys, allowing for efficient monitoring and analysis of cluster performance. This plugin provides valuable capabilities for managing and maintaining the performance of a Ceph cluster by allowing administrators to understand system behavior and identify potential issues proactively.
Nebius Cloud Monitoring
The Nebius Cloud Monitoring plugin serves as an intermediary to send custom metrics to the Nebius Cloud Monitoring service. It is designed specifically to facilitate the monitoring of applications and services running within the Nebius ecosystem. This plugin is especially useful for users of the Nebius Cloud Platform who need to leverage cloud-based monitoring capabilities without significant configuration overhead. The plugin’s integration relies on Google Cloud metadata, allowing it to automatically fetch the necessary authentication credentials from the Compute instance it operates within. Key technical considerations include the management of reserved labels to ensure metrics are recorded correctly without conflicts.
Configuration
Ceph
[[inputs.ceph]]
## This is the recommended interval to poll. Too frequent and you
## will lose data points due to timeouts during rebalancing and recovery
interval = '1m'
## All configuration values are optional, defaults are shown below
## location of ceph binary
ceph_binary = "/usr/bin/ceph"
## directory in which to look for socket files
socket_dir = "/var/run/ceph"
## prefix of MON and OSD socket files, used to determine socket type
mon_prefix = "ceph-mon"
osd_prefix = "ceph-osd"
mds_prefix = "ceph-mds"
rgw_prefix = "ceph-client"
## suffix used to identify socket files
socket_suffix = "asok"
## Ceph user to authenticate as, ceph will search for the corresponding
## keyring e.g. client.admin.keyring in /etc/ceph, or the explicit path
## defined in the client section of ceph.conf for example:
##
## [client.telegraf]
## keyring = /etc/ceph/client.telegraf.keyring
##
## Consult the ceph documentation for more detail on keyring generation.
ceph_user = "client.admin"
## Ceph configuration to use to locate the cluster
ceph_config = "/etc/ceph/ceph.conf"
## Whether to gather statistics via the admin socket
gather_admin_socket_stats = true
## Whether to gather statistics via ceph commands, requires ceph_user
## and ceph_config to be specified
gather_cluster_stats = false
Nebius Cloud Monitoring
[[outputs.nebius_cloud_monitoring]]
## Timeout for HTTP writes.
# timeout = "20s"
## Nebius.Cloud monitoring API endpoint. Normally should not be changed
# endpoint = "https://monitoring.api.il.nebius.cloud/monitoring/v2/data/write"
Input and output integration examples
Ceph
-
Dynamic Monitoring Dashboard: Utilize the Ceph plugin to create a real-time monitoring dashboard that visually represents the performance metrics of your Ceph cluster. By integrating these metrics into a centralized dashboard, system administrators can gain immediate insights into the health of the storage infrastructure, which aids in quickly identifying and addressing potential issues before they escalate.
-
Automated Alerting System: Implement the Ceph plugin in conjunction with an alerting solution to automatically notify administrators of performance degradation or operational issues within the Ceph cluster. By defining thresholds for key metrics, organizations can ensure prompt response actions, thereby improving overall system reliability and performance.
-
Performance Benchmarking: Use the metrics collected by this plugin to conduct performance benchmarking tests across different configurations or hardware setups of your Ceph storage cluster. This process can assist organizations in identifying optimal configurations that enhance performance and resource utilization, promoting a more efficient storage environment.
-
Capacity Planning and Forecasting: Integrate the metrics gathered from the Ceph storage plugin into broader data analytics and reporting tools to facilitate capacity planning. By analyzing historical metrics, organizations can forecast future utilization trends, enabling informed decisions about scaling storage resources effectively.
Nebius Cloud Monitoring
-
Dynamic Application Monitoring: Integrate this plugin with your application to continuously send metrics related to resource usage, such as CPU and memory utilization, to Nebius Cloud Monitoring. By doing so, you can gain insights into the performance of your application, allowing for adjustments in real-time based on the metrics received.
-
Incident Response Automation: Use the Nebius Cloud Monitoring plugin to automatically send alerts and metrics when certain thresholds are reached. For instance, if a particular service’s uptime drops below a certain percentage, the plugin can be configured to report this directly to the monitoring service, enabling quicker incident response and resolution.
-
Comparative Service Analysis: Set up the plugin to send metrics from multiple cloud instances running different versions of the same application to Nebius Cloud Monitoring. This approach allows for a comparative analysis of resource usage and performance, helping teams determine which version performs best under similar workloads.
-
Aggregated Metrics Dashboard: Use this plugin to create a centralized dashboard displaying metrics from various services across your cloud instances. By aggregating different application metrics into one interface, stakeholders can assess the overall health and performance of their cloud environment easily.
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