Network telemetry Tuning and Optimization
RCCE students will learn cloud network security fundamentals including virtual network design, subnet architecture, security groups, network ACLs, load balancer security, CDN protection, and hybrid connectivity security. RCCE students will learn to design secure cloud network architectures across AWS VPC, Azure VNet, and GCP VPC, implement micro-segmentation strategies, configure web application firewalls for cloud workloads, secure inter-region and hybrid connections using VPN and private connectivity services, monitor cloud network traffic for anomalies, and troubleshoot cloud network security issues while maintaining least-privilege network access. This optimization course focuses on maximizing effectiveness and efficiency in production security operations. At an expert level, RCCE students will learn to reduce noise, improve signal quality, tune configurations for optimal performance, and measure operational improvements. Students gain the operational maturity to transform good security programs into exceptional ones.
- Security Engineers building defensive controls
- Security Analysts and Blue Team members
- Systems Administrators with security responsibilities
- GRC and Risk Professionals supporting controls
- Professionals implementing Network telemetry Tuning and Optimization
- Monitor and audit privilege usage; detect escalation attempts
- Execute hands-on tasks for cloud network security · signal optimization · operational maturity
- Explain Course Overview & Learning Objectives fundamentals
- Execute hands-on tasks for cloud network security — covering AWS VPC, Azure VNet, GCP VPC, Subnet architecture & security.
- Execute hands-on tasks for aws vpc, azure vnet, gcp vpc — covering Subnet architecture & security.
- Monitor and audit privilege usage; detect escalation attempts, including Noise reduction & signal quality, and Alert threshold tuning.
- Execute hands-on tasks for operational maturity — covering KPI frameworks & measurement, Continuous improvement cycles.
- Execute hands-on tasks for flow data
- Execute hands-on tasks for packet data
- Execute hands-on tasks for log data — covering NetFlow v5/v9, IPFIX, sFlow, Full packet capture (PCAP).
- Execute hands-on tasks for synthetic probes — covering Enriched contextual data.
| Module 01 | Network Telemetry |
| Module 02 | Cloud Network Security · Signal Optimization · Operational Maturity |
| Module 03 | Course Overview & Learning Objectives |
| Module 04 | Cloud Network Security |
| Module 05 | AWS VPC, Azure VNet, GCP VPC |
| Module 06 | Telemetry Optimization |
| Module 07 | Operational Maturity |
| Module 08 | Network Telemetry Fundamentals |
| Module 09 | Flow Data |
| Module 10 | Packet Data |
| Module 11 | Log Data |
| Module 12 | Synthetic Probes |
| Module 13 | Telemetry Data Source Taxonomy |
| Module 14 | Source Type |
All hands-on labs run on Rocheston Rose X OS. Students practice network telemetry tuning and optimization by implementing the controls discussed in class, with a focus on real-world deployment, monitoring, and validation.
- Lab 1: Monitor and audit privilege usage; detect escalation attempts
- Lab 2: Execute hands-on tasks for cloud network security · signal optimization · operational maturity
- Lab 3: Explain Course Overview & Learning Objectives fundamentals
- Lab 4: Execute hands-on tasks for cloud network security
- Lab 5: Execute hands-on tasks for aws vpc, azure vnet, gcp vpc
Upon successful completion of this course, students will receive an official RCCE Course Completion Certificate for Network telemetry Tuning and Optimization, verifiable through the Rocheston certification portal.
- Full access to all course materials and slide decks
- Hands-on lab access on Rocheston Rose X OS environment
- Access to Rocheston CyberNotes
- Access to Rocheston Zelfire — EDR/XDR SIEM platform
- Access to Rocheston Raven — online cyber range exercise platform
- Access to Rocheston Vulnerability Vines AI