feat: add Datadog integration tile (#517)

* add datadog entry

* add logo

Author: sjrl

integrations/datadog.md

@@ -0,0 +1,94 @@
+---
+layout: integration
+name: Datadog
+description: Monitor and trace your Haystack pipelines with Datadog.
+
+authors:
+    - name: deepset
+      socials:
+        github: deepset-ai
+        twitter: haystack_ai
+        linkedin: https://www.linkedin.com/company/deepset-ai/
+pypi: https://pypi.org/project/datadog-haystack/
+repo: https://github.com/deepset-ai/haystack-core-integrations/tree/main/integrations/datadog
+type: Monitoring Tool
+report_issue: https://github.com/deepset-ai/haystack-core-integrations/issues
+logo: /logos/datadog.png
+version: Haystack 2.0
+toc: true
+---
+### **Table of Contents**
+- [Overview](#overview)
+- [Installation](#installation)
+- [Usage](#usage)
+- [License](#license)
+
+## Overview
+
+This integration lets you use [Datadog](https://www.datadoghq.com/) to trace and monitor your Haystack
+pipelines and agents. It relies on [Datadog's tracing library `ddtrace`](https://ddtrace.readthedocs.io/en/stable/)
+and provides a `DatadogConnector` component that, once added to your pipeline, sends Haystack traces to Datadog.
+
+## Installation
+
+```bash
+pip install datadog-haystack
+```
+
+## Usage
+
+Add the `DatadogConnector` to your pipeline without connecting it to any other component. It enables Datadog
+tracing for all pipeline operations.
+
+You also need to set the `HAYSTACK_CONTENT_TRACING_ENABLED` environment variable to `true` to trace the content
+(inputs and outputs) of the pipeline components.
+
+Datadog itself is configured through the standard `ddtrace` mechanisms, for example the `DD_SERVICE`, `DD_ENV` and
+`DD_VERSION` environment variables, or by running your application with the `ddtrace-run` command. See the
+[ddtrace documentation](https://ddtrace.readthedocs.io/en/stable/) for more details.
+
+```python
+import os
+
+os.environ["HAYSTACK_CONTENT_TRACING_ENABLED"] = "true"
+
+from haystack import Pipeline
+from haystack.components.builders import ChatPromptBuilder
+from haystack.components.generators.chat import OpenAIChatGenerator
+from haystack.dataclasses import ChatMessage
+
+from haystack_integrations.components.connectors.datadog import DatadogConnector
+
+pipe = Pipeline()
+pipe.add_component("tracer", DatadogConnector("Chat example"))
+pipe.add_component("prompt_builder", ChatPromptBuilder())
+pipe.add_component("llm", OpenAIChatGenerator(model="gpt-4o-mini"))
+
+pipe.connect("prompt_builder.prompt", "llm.messages")
+
+messages = [
+    ChatMessage.from_system("Always respond in German even if some input data is in other languages."),
+    ChatMessage.from_user("Tell me about {{location}}"),
+]
+
+response = pipe.run(
+    data={"prompt_builder": {"template_variables": {"location": "Berlin"}, "template": messages}}
+)
+print(response["llm"]["replies"][0])
+```
+
+Your traces will then be available in your Datadog dashboard under the configured service.
+
+If you prefer not to use the connector, you can also enable the tracer manually:
+
+```python
+import ddtrace
+from haystack import tracing
+from haystack_integrations.tracing.datadog import DatadogTracer
+
+tracing.enable_tracing(DatadogTracer(ddtrace.tracer))
+```
+
+## License
+
+`datadog-haystack` is distributed under the terms of the [Apache-2.0](https://spdx.org/licenses/Apache-2.0.html) license.