How to load Postmark data into Elasticsearch via Logstash

Elasticsearch is a popular distributed full-text search engine. By centrally storing data, you can perform ultra-fast searches, fine-tuning relevance, and powerful analytics with ease. Elasticsearch has a pipeline tool for loading data called "Logstash". You can use CData JDBC Drivers to easily import data from any data source into Elasticsearch for search and analysis.

This article explains how to use the CData JDBC Driver for Postmark to load data from Postmark into Elasticsearch via Logstash.

Using CData JDBC Driver for Postmark with Elasticsearch Logstash

• Install the CData JDBC Driver for Postmark on the machine where Logstash is running.
• The JDBC Driver will be installed at the following path (the year part, e.g. 20XX, will vary depending on the product version you are using). You will use this path later. Place this .jar file (and the .lic file if it's a licensed version) in Logstash.
  C:\Program Files\CData\CData JDBC Driver for API 20XX\lib\cdata.jdbc.api.jar
  
• Next, install the JDBC Input Plugin, which connects Logstash to the CData JDBC driver. The JDBC Plugin comes by default with the latest version of Logstash, but depending on the version, you may need to add it.
  https://www.elastic.co/guide/en/logstash/5.4/plugins-inputs-jdbc.html
• Move the CData JDBC Driver’s .jar file and .lic file to Logstash's "/logstash-core/lib/jars/".

Sending Postmark data to Elasticsearch with Logstash

Now, let's create a configuration file for Logstash to transfer Postmark data to Elasticsearch.

• Write the process to retrieve Postmark data in the logstash.conf file, which defines data processing in Logstash. The input will be JDBC, and the output will be Elasticsearch. The data loading job is set to run at 30-second intervals.
• Set the CData JDBC Driver's .jar file as the JDBC driver library, configure the class name, and set the connection properties to Postmark in the form of a JDBC URL. The JDBC URL allows detailed configuration, so please refer to the product documentation for more specifics.

Using API Key Authentication

Postmark uses server API tokens to authenticate requests. Each Postmark server has its own API token, which controls access to messages, bounces, templates, and statistics associated with that server.

To obtain your Server API Token, log in to your Postmark account and navigate to the server you want to connect to. Go to API Tokens under the server settings and copy the token labeled Server API token.

After setting the following connection properties, you are ready to connect:

• AuthScheme: Set this to APIKey.
• APIKey: Set this to your Postmark Server API Token. This value is sent as the X-Postmark-Server-Token header on every request.

Example connection string:

Profile=C:\profiles\Postmark.apip;AuthScheme=APIKey;ProfileSettings="APIKey=your-server-api-token"

Connecting to Postmark

Once the authentication is configured, you can connect to Postmark and query data from any of the available tables such as OutboundMessages, Bounces, and Templates.

Executing data movement with Logstash

Now let's run Logstash using the created "logstash.conf" file.

 logstash-7.8.0\bin\logstash -f logstash.conf

A log indicating success will appear. This means the Postmark data has been loaded into Elasticsearch.

For example, let's view the data transferred to Elasticsearch in Kibana.

 GET api_table/_search
 {
 "query": {
 "match_all": {}
 }
 }

We have confirmed that the data is stored in Elasticsearch.

By using the CData JDBC Driver for Postmark with Logstash, it functions as a Postmark connector, making it easy to load data into Elasticsearch. Please try the 30-day free trial.