Fahrul Dwi
Anugrah
Network Engineer · F5 BIG-IP LTM Engineer
I keep enterprise application traffic flowing — load balancing, routing, and security across a 133-device F5 fleet, backed by active certifications in networking, cloud, and cybersecurity.
Four domains I work across — open one to see the courses behind it.
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Network9 courses →
Routing & Switching · Load Balancing · Wireless · Network Simulation
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Security9 courses →
Network & Infra Security · Offensive Security · Security Operations
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Cloud5 courses →
Identity & Access · Compute · Networking & DNS · Storage & Database · Scalability
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Linux3 courses →
System Administration · Server Services · Virtualization
Summary
Network Engineer specializing in Application Delivery and enterprise networking, with hands-on experience in a large-scale F5 BIG-IP LTM environment supporting mission-critical applications. At PT. Mastersystem Infotama I run a client fleet of 133 devices and 7,000+ virtual servers — load balancing, virtual server/pool/node management, SSL/TLS certificate administration, traffic monitoring, and application access troubleshooting.
Supported by a strong foundation in routing & switching, network security, cloud computing, and Linux, with certifications including F5-CA, MTCNA, OCNA, NSE 1-3, and AWS-CCP — plus a public set of study notes and exam simulators built from that same material.
Working Experience

- Deployed on-site at a client enterprise, representing PT. Mastersystem Infotama in managing F5 BIG-IP LTM infrastructure across 133 devices (including primary/secondary High Availability pairs) supporting 7,000+ virtual servers for critical application delivery and traffic management.
- Executed 1,300+ F5 configuration changes (140+ per month on average) across virtual servers, pools, nodes, and SSL certificates within established change-management procedures.
- Monitored traffic patterns, pool health, and service availability across the F5 fleet using real-time dashboards, catching potential issues before they affected application users.
- Diagnosed application access and load-balancing issues — including virtual server status, pool member health, SSL/TLS, and persistence — escalating complex cases for senior-level review.

- Identified a monitoring gap in the existing tracer study system and independently built a multi-level Google Sheets dashboard that automatically calculated response rates and weighted IKU1 achievement across 50+ study programs, 15 faculties, and university-wide reporting.
- Automated IKU1 scoring across employment status, salary benchmarks, and waiting-period variables for 5,500+ alumni respondents annually, supporting survey response rates above 80% year-over-year and university accreditation reporting.
- Restructured the university's annual tracer study dataset into the government-prescribed schema, ensuring on-time submission to the national Dikti reporting platform.

- Analyzed network topology and hardware inventory of a large-scale industrial complex, and assisted with LAN cabling and VoIP deployment across the facility, gaining hands-on exposure to enterprise-scale network operations.

- Represented Tanoto Foundation as a campus ambassador for the TELADAN scholarship program, guiding prospective applicants through the selection process.
Certifications & Trainings


Skills & Toolset
Application Delivery
Routing & Switching
Network Security
Offensive Security
Cloud & Systems
Monitoring & Analysis
Programming
Languages
Soft Skills
Courses & Bootcamps
Courses and bootcamps taken outside formal certification tracks. A Bootcamp entry is an intensive, instructor-led program; everything else was self-paced. Open a course to see exactly what it covered.
23 of 23 completed courses have their topics documented.
Education

TELADAN Scholarship, Tanoto Foundation — recipient of the highly competitive TELADAN Scholarship awarded to selected students nationwide, covering full financial support and a leadership development program for 8 semesters.
Final Project — designed and built a standalone edge-AI device using Raspberry Pi, integrating a camera module with a custom-trained Convolutional Neural Network (CNN) to detect rice plant diseases from leaf images in real time, enabling low-cost, offline diagnosis for farmers without internet access — image capture, inference, and result output all handled on-device.
Relevant coursework — Computer Networking, Information Security, Cloud Computing, Operating Systems.






