[100% Off] F5 Big-Ip Dns/Gtm 302 — Practice Test: 1500 Exam Questions
Wide-IP, pools, datacenters, topology, monitors, load balancing methods, DNSSEC, and GTM troubleshooting
What you’ll learn
- Build clean Wide-IP designs that survive partial outages without confusing failover behavior.
- Predict GTM answers by understanding resolution flow
- caching
- and TTL impact.
- Use topology to steer traffic with deterministic
- testable decision order.
- Design monitors that provide trustworthy health signals under load and degradation.
- Select load balancing methods that match capacity
- resilience goals
- and failure reality.
- Troubleshoot SERVFAIL
- timeouts
- and wrong answers using evidence-first workflows.
- Reduce flapping and oscillation with monitor tuning and stable selection patterns.
- Apply DNSSEC concepts operationally and recognize validation failure symptoms quickly.
- Validate changes safely and avoid fixes that create secondary failures.
- Explain GTM behavior clearly to teams and stakeholders with defensible reasoning.
Requirements
- Basic understanding of DNS records and recursive resolvers (A
- CNAME
- NS
- TTL).
- Familiarity with common networking concepts: IP routing
- latency
- and basic TCP/HTTP.
- Comfort using simple DNS query tools such as dig or nslookup is helpful.
- Exposure to BIG-IP administration is useful
- but not required to benefit from the drills.
- Willingness to retake sections and learn from mistakes to build faster
- safer decisions.
Description
If you manage global applications, you already know the uncomfortable truth: DNS is not ‘just a record.’ It is a distributed decision system where caching, health signals, topology intent, and load balancing logic all collide. BIG-IP DNS (GTM) sits right in the blast radius of that collision. When it is designed well, users never think about it. When it is designed poorly, the outage looks random, the symptoms are inconsistent, and the war room spirals into guesswork.
This course is built to give you decision-quality instincts for the F5 BIG-IP DNS/GTM 302 scope. Not shallow memorization. Not ‘recognize the right keyword.’ Instead, you will train how a real operator thinks: observe the symptom, identify the decision point, validate the inputs, then apply the safest fix. That is how you keep production stable while everyone else is debating theories.
You get six full-length practice sections, each with two hundred and fifty questions, for a total of one thousand five hundred questions. The design intent is deliberate: repetition builds speed, and speed builds safety. Retake sections as many times as you want, focus on what you missed, and keep going until your choices are not only correct, but explainable. In production, ‘I think’ is expensive. Clear reasoning is what scales.
In the first section, you will lock in the object model that everything depends on: Wide-IP design, pools and members, datacenters, servers, and links, and how these objects behave when traffic is actually flowing. You will learn to avoid common architectures that look neat on paper but fail under partial outages. You will also train how availability states propagate and how to design your objects so that failures are clean, observable, and recoverable.
In the second section, you will go deep on DNS resolution flow and response behavior, because that is what your users and resolvers actually experience. You will practice the real-world effects of caching, TTL decisions, and resolver-side symptoms such as timeouts, SERVFAIL, and unexpected answers. This section trains you to map what you see from tools like dig and resolver logs back to GTM decision logic. When you can predict the next answer, you control the incident.
In the third section, you will master topology and source-aware steering without turning your config into a haunted house. Topology is powerful, but it punishes sloppy thinking. You will drill how matches are evaluated, how regions and rules interact, and why LDNS location assumptions can mislead you. You will learn to build deterministic rule sets that you can validate and defend, especially when stakeholders ask why users in one region are landing in the ‘wrong’ site. Predictability beats cleverness.
In the fourth section, you will treat monitoring as an engineering system. Monitors create your definition of truth, and if your truth is wrong, every downstream decision is wrong. You will practice choosing the correct monitor depth, tuning intervals and timeouts, handling flapping signals, and designing dependencies that reflect real service health. You will also learn how to prove whether a monitor is telling the truth during load, partial failures, and application degradation. Good monitors reduce panic. Bad monitors create it.
In the fifth section, you will turn load balancing methods into a controlled toolbox. You will drill Global Availability, Ratio, Round Robin, Topology, and practical resilience patterns such as preferred site behavior and clean fallback. You will face scenarios where capacity is uneven, where one data center is ‘up’ but degraded, and where emergency reroutes must be done safely. You will learn to design selection logic that avoids oscillation and keeps user experience stable even when inputs change. Resilience is not a setting; it is a design outcome.
In the sixth section, you will combine DNSSEC and operational troubleshooting into one discipline, because secure DNS that breaks is not helpful, and fast troubleshooting without security awareness is risky. You will drill DNSSEC purpose and operational impacts, common validation failure patterns, and how to reason through secure answer delivery. You will also train GTM troubleshooting workflows that work in production: fast evidence, correct failure domain, minimal-risk change, and verification that does not create collateral damage.
By the end of this course, you should feel something simple and valuable: calm. Calm because you understand where the DNS decision is made, what inputs drive it, and how to fix it without guessing. BIG-IP DNS/GTM is not magic. It is a system. And systems become manageable when you can explain them, test them, and operate them with discipline.
