---
title: Scaling and Performance
description: Datadog, the leading service for cloud-scale monitoring.
breadcrumbs: Docs > Observability Pipelines > Scaling and Performance
---

# Scaling and Performance

{% callout %}
# Important note for users on the following Datadog sites: app.ddog-gov.com

{% alert level="danger" %}
This product is not supported for your selected [Datadog site](https://docs.datadoghq.com/getting_started/site.md). ().
{% /alert %}

{% /callout %}

As you scale your Observability Pipelines architecture to cover your different use cases:

- If you want to run multiple pipelines on a host so that you can send data from different sources, follow the instructions in [Run Multiple Pipelines on a Host](https://docs.datadoghq.com/observability_pipelines/configuration/install_the_worker/run_multiple_pipelines_on_a_host.md).
- Observability Pipelines uses backpressure signals and buffering to handle situations where the system cannot process events immediately upon receiving them. See [Buffering and Backpressure](https://docs.datadoghq.com/observability_pipelines/scaling_and_performance/buffering_and_backpressure.md) for more information.
- When you scale Observability Pipelines Workers, each Worker operates independently. See [Best Practices for Scaling Pipelines](https://docs.datadoghq.com/observability_pipelines/scaling_and_performance/best_practices_for_scaling_observability_pipelines.md) for the recommended aggregator architecture.