Synchronizing Data from Azure Event Hubs to Alibaba Cloud Elasticsearch using Logstash

In the era of big data, organizations require powerful tools to process and make sense of the vast streams of information generated every second. This article will explain how to bridge Azure Event Hubs with Alibaba Cloud Elasticsearch, creating a robust data processing pipeline. For more insights, check out the Alibaba Cloud Elasticsearch product page

Preparation Steps

To begin, we need to set up our work environment:

Deploy an Alibaba Cloud Elasticsearch cluster and enable Auto Indexing. In this case, a V7.10 cluster suits our needs. Additional information on cluster creation and YML configuration can be found here
Set up an Alibaba Cloud Logstash cluster (V7.4 is used for this example). If you opt for a self-managed Logstash, make sure it's in the same VPC as your Elasticsearch cluster. Info on the setup can be found in the Alibaba Cloud documentation.
Prepare Azure Event Hubs and familiarize yourself with Azure Event Hubs documentation

Step 1: Create and Configure a Logstash Pipeline

After logging into the Elasticsearch console and navigating to your cluster, create a pipeline in the Logstash section. A pipeline configuration example might look like this:

input {
  azure_event_hubs {
    event_hub_connections => ["{Event Hub connection string with EntityPath}"]
    initial_position => "beginning"
    threads => 2
    decorate_events => true
    consumer_group => "alibaba-logstash"
    storage_connection => "{Azure Blob storage connection string}"
    storage_container => "eventhub-offsets"
  }
}

output {
  elasticsearch {
    hosts => ["{Alibaba Elasticsearch cluster endpoint}:9200"]
    index => "azure-logs"
    user => "elastic"
    password => "{Elasticsearch password}"
  }
}

filter {
  # Depending on your data processing needs, you can add filter plugins here
}

Step 2: Pipeline Parameter Configuration

Configure your pipeline parameters with the following settings:

Pipeline Workers: # Set according to the number of vCPUs
Pipeline Batch Size: # Default size: 125 (adjust based on your heap size)
Pipeline Batch Delay: # Default delay: 50 milliseconds
Queue Type: MEMORY (for a traditional memory-based queue)
Queue Max Bytes: # Ensure it's less than the total disk capacity
Queue Checkpoint Writes: # Default: 1024

Ensure you correctly deploy the pipeline settings without disrupting services.

Step 3: Verify Data Synchronization

To confirm data is being indexed correctly into your Alibaba Elasticsearch cluster:

1）Log into your Kibana console.

2）Access Dev Tools.

3）Execute a query to find the synchronized data:

GET azure-logs/_search
{
  "query": {
    "match": {
      "message": "ExampleKeyword"
    }
  }
}

Benefits

This integration offers real-time searchability for your Azure Event Hubs data within the resilient ecosystem of Alibaba Cloud Elasticsearch. Provided examples in this article should get you started, but remember that each integration can be unique depending on specific data and infrastructural needs.

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Synchronizing Data from Azure Event Hubs to Alibaba Cloud Elasticsearch using Logstash

Preparation Steps

Step 1: Create and Configure a Logstash Pipeline

Step 2: Pipeline Parameter Configuration

Step 3: Verify Data Synchronization

Benefits

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