Data Engineering for Cybersecurity Build Secure Data Pipelines with Free and Open-Source Tools

Turn raw logs into real intelligence.
Security teams rely on telemetry-the continuous stream of logs, events, metrics, and signals that reveal what's happening across systems, endpoints, and cloud services. But that data doesn't organize itself. It has to be collected, normalized, enriched, and secured before it becomes useful. That's where data engineering comes in.
In this hands-on guide, cybersecurity engineer James Bonifield teaches you how to design and build scalable, secure data pipelines using free, open source tools such as Filebeat, Logstash, Redis, Kafka, and Elasticsearch and more. You'll learn how to collect telemetry from Windows including Sysmon and PowerShell events, Linux files and syslog, and streaming data from network and security appliances. You'll then transform it into structured formats, secure it in transit, and automate your deployments using Ansible.
You'll also learn how to:
Encrypt and secure data in transit using TLS and SSH
Centrally manage code and configuration files using Git
Transform messy logs into structured events
Enrich data with threat intelligence using Redis and Memcached
Stream and centralize data at scale with Kafka
Automate with Ansible for repeatable deployments
Whether you're building a pipeline on a tight budget or deploying an enterprise-scale system, this book shows you how to centralize your security data, support real-time detection, and lay the groundwork for incident response and long-term forensics.

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