Implementing Cisco Enterprise Network Core Technologies (ENCOR) 350-401 Practice Test 71
Question 700
During acceptance testing after extract each dictionary's hostname field in a loop or comprehension., which evidence is most relevant?
The interpreter parses the corrected function and executes its nested block.
The result contains hostnames in the same order as input records.
A missing edge key returns the default without raising KeyError.
The result parses as JSON and preserves the expected dictionary values.
Explanation
Correct Answer
B:
The result contains hostnames in the same order as input records. This is the targeted operational evidence for the change. Nested Python collections require key lookup per record. Merely entering the configuration or seeing a management session is less conclusive than observing the resulting behavior.
Incorrect Answers
A:
This observation validates another operation: Use consistent indentation within Python suites. Indentation defines Python block structure rather than cosmetic whitespace. It is not decisive evidence that the change under examination works as required. A relevant verification must exercise its particular control or forwarding outcome.
C:
This observation validates another operation: Use dictionary `.get` with an appropriate default instead of direct indexing. Dictionary get can avoid a KeyError for a missing key. It is not decisive evidence that the change under examination works as required. A relevant verification must exercise its particular control or forwarding outcome.
D:
This observation validates another operation: Use `json.dumps` to produce properly encoded JSON text. The dumps function serializes Python structures into JSON strings. It is not decisive evidence that the change under examination works as required. A relevant verification must exercise its particular control or forwarding outcome.
Question 701
A script mixes tabs and spaces and raises IndentationError. How should the team implement the required behavior?
Use consistent indentation within Python suites.
Recognize Python iteration over the list elements.
Use `json.loads` on the JSON-encoded string.
Use the equality comparison operator `==` in conditions.
Explanation
Correct Answer
A:
Indentation defines Python block structure rather than cosmetic whitespace. The most direct remediation is use consistent indentation within Python suites. A practical acceptance test is the interpreter parses the corrected function and executes its nested block. This distinguishes a configured intention from operational success.
Incorrect Answers
B:
This choice addresses a different situation: A Python script uses `for interface in interfaces` and operators expect one iteration per port. A for loop visits each value in the iterable in sequence. It does not specifically correct the issue here: a script mixes tabs and spaces and raises IndentationError.
C:
This choice addresses a different situation: A Python tool needs to convert JSON text received from an API into data objects. The loads function parses JSON text into Python-native values. It does not specifically correct the issue here: a script mixes tabs and spaces and raises IndentationError.
D:
This choice addresses a different situation: A script tests `if status == 200` but writes `if status = 200`. A single equals sign is assignment syntax, not an equality expression. It does not specifically correct the issue here: a script mixes tabs and spaces and raises IndentationError.
Question 702
An operator has applied the following change: use consistent indentation within Python suites. Which observation best confirms it works?
A test list of three interfaces produces three loop-body executions.
The parser returns a dictionary with accessible keys after valid input.
The corrected code runs and enters the branch only for status 200.
The interpreter parses the corrected function and executes its nested block.
Explanation
Correct Answer
D:
The interpreter parses the corrected function and executes its nested block. This is the targeted operational evidence for the change. Indentation defines Python block structure rather than cosmetic whitespace. Merely entering the configuration or seeing a management session is less conclusive than observing the resulting behavior.
Incorrect Answers
A:
This observation validates another operation: Recognize Python iteration over the list elements. A for loop visits each value in the iterable in sequence. It is not decisive evidence that the change under examination works as required. A relevant verification must exercise its particular control or forwarding outcome.
B:
This observation validates another operation: Use `json.loads` on the JSON-encoded string. The loads function parses JSON text into Python-native values. It is not decisive evidence that the change under examination works as required. A relevant verification must exercise its particular control or forwarding outcome.
C:
This observation validates another operation: Use the equality comparison operator `==` in conditions. A single equals sign is assignment syntax, not an equality expression. It is not decisive evidence that the change under examination works as required. A relevant verification must exercise its particular control or forwarding outcome.
Question 703
A REST request is rejected because a JSON object has a trailing comma. Which action most directly addresses this situation?
Use JSON boolean `true` without Python capitalization.
Enclose JSON property names and strings in double quotes.
Remove the trailing comma from the JSON object.
Use JSON `null` when the value should be absent rather than a literal word.
Explanation
Correct Answer
C:
Standard JSON does not allow trailing commas in objects or arrays. The most direct remediation is remove the trailing comma from the JSON object. A practical acceptance test is a strict JSON parser accepts the corrected payload. This distinguishes a configured intention from operational success.
Incorrect Answers
A:
This choice addresses a different situation: A client emits Python `True` inside a JSON payload. JSON literals `true` `false` and `null` have lowercase spelling. It does not specifically correct the issue here: a REST request is rejected because a JSON object has a trailing comma.
B:
This choice addresses a different situation: An API request uses single-quoted JSON object keys. JSON string syntax requires double quotation marks. It does not specifically correct the issue here: a REST request is rejected because a JSON object has a trailing comma.
D:
This choice addresses a different situation: An empty API field is being represented by the string `"null"`. A string and null carry different semantic types. It does not specifically correct the issue here: a REST request is rejected because a JSON object has a trailing comma.
Question 704
An operator has applied the following change: remove the trailing comma from the JSON object. Which observation best confirms it works?
The JSON decoder returns a boolean value for the field.
A strict JSON parser accepts the corrected payload.
A strict decoder parses the object with the expected key/value pair.
Decoded field is Python None rather than four-character text.
Explanation
Correct Answer
B:
A strict JSON parser accepts the corrected payload. This is the targeted operational evidence for the change. Standard JSON does not allow trailing commas in objects or arrays. Merely entering the configuration or seeing a management session is less conclusive than observing the resulting behavior.
Incorrect Answers
A:
This observation validates another operation: Use JSON boolean `true` without Python capitalization. JSON literals `true` `false` and `null` have lowercase spelling. It is not decisive evidence that the change under examination works as required. A relevant verification must exercise its particular control or forwarding outcome.
C:
This observation validates another operation: Enclose JSON property names and strings in double quotes. JSON string syntax requires double quotation marks. It is not decisive evidence that the change under examination works as required. A relevant verification must exercise its particular control or forwarding outcome.
D:
This observation validates another operation: Use JSON `null` when the value should be absent rather than a literal word. A string and null carry different semantic types. It is not decisive evidence that the change under examination works as required. A relevant verification must exercise its particular control or forwarding outcome.
Question 705
A client emits Python `True` inside a JSON payload. What is the most effective configuration or design response?
Use JSON boolean `true` without Python capitalization.
Represent the devices as a JSON array inside the correct object key.
Build nested objects using braces and arrays using brackets as required.
Escape the newline as `\n` inside the JSON string.
Explanation
Correct Answer
A:
JSON literals `true` `false` and `null` have lowercase spelling. The most direct remediation is use JSON boolean `true` without Python capitalization. A practical acceptance test is the JSON decoder returns a boolean value for the field. This distinguishes a configured intention from operational success.
Incorrect Answers
B:
This choice addresses a different situation: A JSON API expects a list of network devices and the engineer sends a scalar. JSON arrays use square brackets and contain ordered values. It does not specifically correct the issue here: a client emits Python `True` inside a JSON payload.
C:
This choice addresses a different situation: An automation client needs a nested JSON object for interface configuration. JSON hierarchy represents structured configuration directly. It does not specifically correct the issue here: a client emits Python `True` inside a JSON payload.
D:
This choice addresses a different situation: A JSON payload contains an unescaped newline inside an ordinary string. Control characters inside JSON strings require escape sequences. It does not specifically correct the issue here: a client emits Python `True` inside a JSON payload.
Question 706
After implementing use JSON boolean `true` without Python capitalization., which operational evidence should an engineer collect?
Parser returns a list with the intended number of device objects.
Decoded JSON retains the intended object and child properties.
The JSON decoder preserves the newline as string content.
The JSON decoder returns a boolean value for the field.
Explanation
Correct Answer
D:
The JSON decoder returns a boolean value for the field. This is the targeted operational evidence for the change. JSON literals `true` `false` and `null` have lowercase spelling. Merely entering the configuration or seeing a management session is less conclusive than observing the resulting behavior.
Incorrect Answers
A:
This observation validates another operation: Represent the devices as a JSON array inside the correct object key. JSON arrays use square brackets and contain ordered values. It is not decisive evidence that the change under examination works as required. A relevant verification must exercise its particular control or forwarding outcome.
B:
This observation validates another operation: Build nested objects using braces and arrays using brackets as required. JSON hierarchy represents structured configuration directly. It is not decisive evidence that the change under examination works as required. A relevant verification must exercise its particular control or forwarding outcome.
C:
This observation validates another operation: Escape the newline as `\n` inside the JSON string. Control characters inside JSON strings require escape sequences. It is not decisive evidence that the change under examination works as required. A relevant verification must exercise its particular control or forwarding outcome.
Question 707
A JSON API expects a list of network devices and the engineer sends a scalar. Which change should the network engineer prioritize?
Enclose JSON property names and strings in double quotes.
Use JSON `null` when the value should be absent rather than a literal word.
Represent the devices as a JSON array inside the correct object key.
Use a JSON string for dotted-decimal address and mask values.
Explanation
Correct Answer
C:
JSON arrays use square brackets and contain ordered values. The most direct remediation is represent the devices as a JSON array inside the correct object key. A practical acceptance test is parser returns a list with the intended number of device objects. This distinguishes a configured intention from operational success.
Incorrect Answers
A:
This choice addresses a different situation: An API request uses single-quoted JSON object keys. JSON string syntax requires double quotation marks. It does not specifically correct the issue here: a JSON API expects a list of network devices and the engineer sends a scalar.
B:
This choice addresses a different situation: An empty API field is being represented by the string `"null"`. A string and null carry different semantic types. It does not specifically correct the issue here: a JSON API expects a list of network devices and the engineer sends a scalar.
D:
This choice addresses a different situation: A device API sends IP prefix objects but one mask is unquoted as `255.255.255.0`. Dotted-quad addresses are text values, not JSON numeric literals. It does not specifically correct the issue here: a JSON API expects a list of network devices and the engineer sends a scalar.
Question 708
The change request says: represent the devices as a JSON array inside the correct object key. Which verification result is most decisive?
A strict decoder parses the object with the expected key/value pair.
Parser returns a list with the intended number of device objects.
Decoded field is Python None rather than four-character text.
A strict JSON parser accepts the dotted-decimal value as string.
Explanation
Correct Answer
B:
Parser returns a list with the intended number of device objects. This is the targeted operational evidence for the change. JSON arrays use square brackets and contain ordered values. Merely entering the configuration or seeing a management session is less conclusive than observing the resulting behavior.
Incorrect Answers
A:
This observation validates another operation: Enclose JSON property names and strings in double quotes. JSON string syntax requires double quotation marks. It is not decisive evidence that the change under examination works as required. A relevant verification must exercise its particular control or forwarding outcome.
C:
This observation validates another operation: Use JSON `null` when the value should be absent rather than a literal word. A string and null carry different semantic types. It is not decisive evidence that the change under examination works as required. A relevant verification must exercise its particular control or forwarding outcome.
D:
This observation validates another operation: Use a JSON string for dotted-decimal address and mask values. Dotted-quad addresses are text values, not JSON numeric literals. It is not decisive evidence that the change under examination works as required. A relevant verification must exercise its particular control or forwarding outcome.
Question 709
An API request uses single-quoted JSON object keys. Which remediation best resolves the described symptom?
Enclose JSON property names and strings in double quotes.
Build nested objects using braces and arrays using brackets as required.
Escape the newline as `\n` inside the JSON string.
Remove the trailing comma from the JSON object.
Explanation
Correct Answer
A:
JSON string syntax requires double quotation marks. The most direct remediation is enclose JSON property names and strings in double quotes. A practical acceptance test is a strict decoder parses the object with the expected key/value pair. This distinguishes a configured intention from operational success.
Incorrect Answers
B:
This choice addresses a different situation: An automation client needs a nested JSON object for interface configuration. JSON hierarchy represents structured configuration directly. It does not specifically correct the issue here: an API request uses single-quoted JSON object keys.
C:
This choice addresses a different situation: A JSON payload contains an unescaped newline inside an ordinary string. Control characters inside JSON strings require escape sequences. It does not specifically correct the issue here: an API request uses single-quoted JSON object keys.
D:
This choice addresses a different situation: A REST request is rejected because a JSON object has a trailing comma. Standard JSON does not allow trailing commas in objects or arrays. It does not specifically correct the issue here: an API request uses single-quoted JSON object keys.
Question 710
A post-change test follows this action: enclose JSON property names and strings in double quotes. Which result demonstrates success?
Decoded JSON retains the intended object and child properties.
The JSON decoder preserves the newline as string content.
A strict JSON parser accepts the corrected payload.
A strict decoder parses the object with the expected key/value pair.
Explanation
Correct Answer
D:
A strict decoder parses the object with the expected key/value pair. This is the targeted operational evidence for the change. JSON string syntax requires double quotation marks. Merely entering the configuration or seeing a management session is less conclusive than observing the resulting behavior.
Incorrect Answers
A:
This observation validates another operation: Build nested objects using braces and arrays using brackets as required. JSON hierarchy represents structured configuration directly. It is not decisive evidence that the change under examination works as required. A relevant verification must exercise its particular control or forwarding outcome.
B:
This observation validates another operation: Escape the newline as `\n` inside the JSON string. Control characters inside JSON strings require escape sequences. It is not decisive evidence that the change under examination works as required. A relevant verification must exercise its particular control or forwarding outcome.
C:
This observation validates another operation: Remove the trailing comma from the JSON object. Standard JSON does not allow trailing commas in objects or arrays. It is not decisive evidence that the change under examination works as required. A relevant verification must exercise its particular control or forwarding outcome.
Implementing Cisco Enterprise Network Core Technologies (ENCOR) (350-401) Practice Tests
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Cisco ENCOR 350-401 Practice Test Questions, Cisco ENCOR 350-401 Exam Practice Test Questions
Looking to pass your tests the first time. You can study with Cisco ENCOR 350-401 certification practice test questions and answers, study guide, training courses. With Exam-Labs VCE files you can prepare with Cisco 350-401 Implementing Cisco Enterprise Network Core Technologies (ENCOR) exam practice test questions and answers. The most complete solution for passing with Cisco certification ENCOR 350-401 exam practice test questions and answers, study guide, training course.
Cisco 350-401 ENCOR: Enterprise Core Architecture, Assurance, Security, and Automation
Cisco 350-401 ENCOR, Implementing Cisco Enterprise Network Core Technologies, is the current core exam for CCNP Enterprise and, under the current v1.2 path, a qualifying core for CCIE Enterprise Infrastructure. Cisco’s current ENCOR v1.2 blueprint lists a 120-minute exam covering dual-stack architecture, virtualization, infrastructure, network assurance, security, and automation.
ENCOR is broad by design. It tests whether an engineer can reason across campus switching, routing, overlays, security, monitoring, and programmability. The challenge is not that every topic is equally deep; it is that enterprise incidents often cross those boundaries. A routing change can affect assurance data, a virtualization choice can alter troubleshooting visibility, and an automation error can reproduce a bad configuration across many devices.
A strong preparation strategy therefore builds one coherent enterprise model rather than ten disconnected topic lists. Understand how packets move, how control planes select paths, how policy is applied, how failures are observed, and how configuration is delivered safely.
Enterprise architecture starts with understanding where control, forwarding, and policy live
Modern enterprise networks can include campus fabrics, traditional routing and switching, WAN overlays, wireless controllers, cloud connectivity, and centralized management. The engineer needs to know which component owns a decision. Is routing distributed on devices? Is segmentation expressed through VRFs or an overlay? Is policy local, centralized, or identity driven?
Architectural reasoning reduces troubleshooting time because it narrows the possible fault domain. If a packet is dropped before entering an overlay, debugging the overlay control plane is wasted effort. If the underlay cannot reach a tunnel endpoint, changing an application policy will not help.
The Cisco ecosystem uses multiple implementation models, but ENCOR rewards candidates who can identify common functions beneath product names.
Virtualization separates logical networks from the physical infrastructure carrying them
VRFs, tunnels, virtual switching, and overlays let enterprises create independent logical paths over shared hardware. These technologies improve segmentation and flexibility, but they add context that must be preserved during troubleshooting. A route can exist in one VRF and be absent in another even though both use the same physical interface.
Cisco VRF separates routing tables on a shared device, while VXLAN carries Layer 2 segments across an IP underlay. Both technologies illustrate how logical network boundaries can be decoupled from a single physical topology.
Candidates should practice asking “which table, which tunnel, which endpoint, and which encapsulation?” before running commands. Virtualization failures often look mysterious only because the engineer is inspecting the wrong logical context.
Layer 2 reliability depends on predictable trunks, EtherChannels, and spanning-tree behavior
Campus networks still rely on VLANs, 802.1Q trunks, link aggregation, and loop prevention even as overlays become more common. A small mismatch can remove reachability for one VLAN while every physical link remains up. ENCOR expects candidates to verify configuration and infer forwarding behavior rather than merely recognize protocol names.
Port-channel troubleshooting is a good example. Member links need compatible settings, and the logical bundle affects spanning tree and forwarding as one interface. If traffic is unexpectedly distributed or a member refuses to join, candidates should compare negotiation mode, VLAN configuration, speed, and other consistency parameters.
VLAN architecture connects segmentation design with the switching behaviors ENCOR candidates need to master, including trunking, Layer 2 boundaries, and the operational consequences of incorrect membership or propagation.
OSPF and BGP require candidates to distinguish adjacency problems from path-selection problems
Routing troubleshooting has at least two stages: first establish whether peers or neighbors form correctly, then determine why a particular route is or is not preferred. Mixing these stages leads to wasted effort. If OSPF neighbors never reach the expected state, route filtering is not yet the primary problem. If BGP peering is established, then attributes and policy become relevant.
OSPF and BGP fundamentals differ because the protocols solve different routing problems and use different decision models. ENCOR candidates should be comfortable with OSPF area behavior and with basic eBGP establishment and path selection.
Route tables, protocol databases, neighbor state, and packet captures should tell a consistent story. When they do not, that inconsistency is often the clue that reveals redistribution, filtering, stale state, or an unexpected next hop.
Current ENCOR preparation no longer includes the former wireless objectives
Wireless is an important current-versus-legacy distinction for ENCOR. Cisco announced that the dedicated Wireless certification track would launch on March 19, 2026 and that ENCOR would no longer cover wireless concepts. Candidates using older ENCOR study plans can therefore spend substantial time on RF, controllers, roaming, and wireless-client topics that are no longer part of the live ENCOR scope.
Those skills did not disappear from Cisco certification. They moved into the dedicated wireless path built around 350-101 WLCOR. Enterprise engineers may still need wireless knowledge on the job, but current ENCOR preparation should follow Cisco’s live objective boundary rather than preserving an outdated topic list.
The change makes version control part of exam preparation itself: verify that books, courses, lab checklists, and practice material reflect the post-March-2026 ENCOR scope before using their topic coverage as a study plan.
SD-WAN separates transport choice from application-aware policy.
Enterprise WAN design increasingly uses overlays so applications can be steered according to policy rather than simply following the route with the lowest traditional metric. SD-WAN controllers distribute policy and build secure overlay relationships across multiple transports, allowing organizations to use Internet, private circuits, and other connectivity according to application needs.
SD-WAN architecture separates underlay reachability from overlay policy. A tunnel can be healthy while an application takes an unexpected path because policy selected it; conversely, perfect policy cannot compensate for a broken underlay.
Network assurance turns device data into evidence about service health
Ping and traceroute remain useful, but enterprise assurance also involves syslog, SNMP, telemetry, flow data, debugs, packet captures, IP SLA, and centralized analytics. Each tool answers a different question. Good troubleshooting begins by choosing the evidence that can confirm or reject a hypothesis.
Remote logging is valuable only when timestamps, severity, source identity, and retention are trustworthy. SNMP can provide counters and status, while streaming telemetry can expose higher-frequency state. Central platforms can correlate these signals, but candidates should still understand what the underlying measurement represents.
SNMPv3 adds authentication and privacy controls to a familiar monitoring model. Assurance is not just visibility; it is the ability to trust telemetry and use it to make a confident operational decision.
Security is embedded in routing, segmentation, access, and device management
Enterprise security is not confined to a firewall. Infrastructure devices have management planes that need protection, segments need policy boundaries, control-plane protocols need trust, and users or devices need appropriate access. A routing or switching feature can have security consequences even when it was deployed for availability or performance.
ENCOR candidates should understand secure management, access control, segmentation, infrastructure protection, and the principle of limiting unnecessary reachability. VRFs and VLANs create separation, but separation is not automatically security unless traffic between zones is deliberately controlled.
Operational practice matters as much as configuration. Backups, version control, authentication, logging, and change review reduce the chance that an infrastructure compromise or accidental change remains invisible.
Automation uses data models and APIs to make enterprise changes repeatable
Modern Cisco enterprise platforms expose APIs and model-driven interfaces that allow software to retrieve state and make changes consistently. Candidates should understand structured data, common API concepts, and the role of YANG models, NETCONF, and RESTCONF in model-driven management.
YANG, NETCONF, and RESTCONF connect structured data models with programmable configuration and state retrieval. A data model describes structure, while a protocol provides a way to retrieve or modify data according to that structure.
Automation should be treated as controlled change engineering. Scripts and workflows need source control, validation, error handling, and post-change verification. Repeating a manual mistake one hundred times is not progress.
Desired-state comparisons are particularly useful in large enterprises. Rather than asking only whether a command succeeded, an automation workflow can retrieve the resulting state and compare it with policy. That approach catches partial changes, unexpected defaults, and configuration drift. It also makes rollback decisions more defensible because operators can see exactly which intended conditions were not achieved.
Prepare for ENCOR by connecting technologies in failure scenarios
A useful lab should create dependencies between technologies. Put an OSPF-routed campus behind a VRF, carry selected VLANs over trunks, monitor devices with secure telemetry, and automate a small configuration change. Then break one dependency at a time and determine which evidence reveals the cause fastest.
Concentration topics can deepen the core. ENARSI adds advanced routing and services, ENSDWI develops SD-WAN, ENSLD focuses design, and ENAUTO expands programmable operations. Core preparation should make those specialties easier because the candidate already understands the architecture they modify.
Current candidates should study the current ENCOR v1.2 exam and verify exam-specific details against Cisco’s live objectives, especially where older material still includes wireless topics. The exam remains the central enterprise core, and success depends on being able to reason across technologies rather than treating each blueprint heading as a separate memorization exercise.
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