How do you store and manage vast amounts of MTA log file message header data?

Email marketer from Server Fault advises storing message header data in a relational database like PostgreSQL or MySQL. It recommends using appropriate indexing strategies and partitioning the data by date or other relevant criteria for efficient querying.

Email marketer from Stack Overflow recommends using a centralized logging system like Graylog, ELK stack (Elasticsearch, Logstash, Kibana), or Splunk to aggregate and analyze MTA logs. It shares this approach allows for efficient searching, filtering, and reporting on large datasets.

Email marketer from Loggly explains that centralized log management is the process of consolidating logs from multiple sources into a single, central location. This makes it easier to search, analyze, and monitor logs for security threats, performance issues, and other anomalies.

Email marketer from SuperUser explains that its possible to store all kinds of logs in SQL database and process them. You can normalise data before inserting them to save on space.

Email marketer from Reddit suggests using log parsing tools like rsyslog or fluentd to normalize log data before storing it in a database or data warehouse. It explains that normalising the data will improve query performance and reduce storage requirements.

Marketer from Email Geeks shares that depending on your MTA, you may be able to store the message metadata in a database and suggests that something cloud based, e.g., AWS would be ideal.

Email marketer from DigitalOcean, Shahzeb Saeed, explains how to use Logrotate on Ubuntu 18.04. He details how to configure it to rotate logs daily, keep a certain number of old logs, compress them, and even run a script after rotation.

Email marketer from LinuxBabe responds that Rsyslog is a popular open-source log processing tool that collects logs from different sources and writes them to various destinations. Can be used to filter and sort logs and store only the message header data.

Marketer from Email Geeks explains that it depends on what you need the data for and that they are plain text so don't take up space in the same way as storing the whole message would. Suggests that If you are doing analytics and are space conscious, then one approach is to do an ETL (Extract Transform Load). Basically, you calculate the desired analytical values once on the raw data, then delete it and only use the transformed information going forward.

Marketer from Email Geeks suggests considering an archiver and storing just the header data you want. Mentions djb's qmail with qmail tap for archiving and EPS (Email Parsing System) for writing your own email processing tools.

Expert from Email Geeks responds that there are many things you can do to lessen the logs, such as keeping full logs for a period, then picking what you want to have to hand for a period of time and dropping them through a processor to make edits. Suggests looking at dev ops forums about how they manage logs and data.

Expert from Word to the Wise, Laura Atkins, responds that MTA logs are useful for understanding what is happening with your email program. You can use them to troubleshoot delivery problems, identify spam traps, and track bounce rates. You can also use them to identify trends in your email program, such as changes in open rates or click-through rates.

Expert from SpamResource explains that logs can be used to diagnose email delivery problems. A guide on interpreting different server responses and identifying common issues from SMTP logs, such as bounces, deferrals, or blocks.

Documentation from Postfix.org explains that Postfix logs can be managed using syslog or other logging facilities. It recommends configuring logrotate to archive and compress old log files to manage disk space effectively.

Documentation from Scalyr explains that the best option is using the agent that is designed to be deployed to machines and collect logs. They also have other methods that are available.

Documentation from Microsoft Learn explains that Exchange Server provides extensive logging capabilities. It advises using PowerShell cmdlets to export and filter message tracking logs. It also recommends configuring logging levels and retention policies to manage data volume.

Documentation from Graylog explains the different methods of configuration and use cases for their services. Such as collecting vast amounts of email log data and providing actionable information.

Documentation from Elastic explains how to utilise ELK stack in different configurations. ELK stack is most commonly used in conjunction with Logstash, to configure and normalise incoming log data.

Documentation from Exim.org details how Exim's log files can be rotated using the `log_file_rotate_number` and `log_file_rotate_size` options in the Exim configuration. It shares that these settings automatically manage the log file size and number of archived logs.