Prometheus, a leading open-source monitoring and alerting toolkit, is renowned for its robust capabilities in collecting and querying time-series data. However, as organizations scale, the need to store and analyze data beyond the local Prometheus instance becomes crucial. This is where Prometheus’s remote write feature comes into play, enabling the seamless transmission of time-series data to external storage systems for long-term storage, advanced analytics, or centralized monitoring.
What is Remote Write?
Remote write in Prometheus is a feature that allows Prometheus to send its time-series data to remote endpoints. This is particularly useful for organizations that require long-term storage solutions or need to integrate with other data processing systems. By leveraging remote write, users can offload data from Prometheus to a variety of backends, including cloud-based storage solutions, distributed databases, or other monitoring systems.
How Remote Write Works
1. Configuration
The remote write feature is configured in the Prometheus configuration file (prometheus.yml). Users specify one or more remote write endpoints under the remote_write section. Each endpoint configuration includes the URL of the remote storage system and optional parameters such as authentication credentials, write relabeling, and queue configurations.
remote_write:
- url: "http://remote-storage-system/api/v1/write"
basic_auth:
username: "user"
password: "password"
2. Data Flow
Once configured, Prometheus begins to send data to the specified remote endpoints. The data flow involves the following steps:
- Sample Collection: Prometheus scrapes metrics from configured targets at regular intervals.
- Queueing: The collected samples are placed into a queue for each remote write endpoint. This queue ensures that data is sent in an orderly manner and helps manage the load on the remote storage system.
- Batching and Compression: Samples are batched together to optimize network usage. Prometheus uses a snappy compression algorithm to reduce the size of the data being transmitted.
- Transmission: The batched and compressed data is sent to the remote endpoint using HTTP POST requests. Prometheus handles retries and backoff strategies in case of transmission failures.
3. Error Handling and Retries
Prometheus implements a robust error handling mechanism for remote write operations. If a write request fails, Prometheus retries the request with an exponential backoff strategy. This ensures that transient network issues or temporary unavailability of the remote endpoint do not result in data loss.
4. Write Relabeling
Prometheus provides a write relabeling feature that allows users to modify or filter the data before it is sent to the remote endpoint. This is useful for scenarios where only a subset of the data needs to be stored remotely or when labels need to be adjusted for compatibility with the remote storage schema.
remote_write:
- url: "http://remote-storage-system/api/v1/write"
write_relabel_configs:
- source_labels: [__name__]
regex: "up"
action: keep
Use Cases for Remote Write
- Long-term Storage: Offload data to a scalable storage solution for historical analysis and compliance.
- Centralized Monitoring: Aggregate data from multiple Prometheus instances into a single system for a unified view.
- Advanced Analytics: Integrate with data processing platforms for machine learning or complex event processing.
Conclusion
The remote write feature in Prometheus is a powerful tool for extending the capabilities of your monitoring infrastructure. By understanding its internal workings, you can effectively leverage remote write to meet your organization’s data storage and analysis needs. Whether you’re aiming for long-term retention, centralized monitoring, or advanced analytics, remote write provides the flexibility and scalability required for modern observability solutions.