JNCIA-DevOps Practice Test 20 — 15 Questions

Question 1

Which Python function deserializes a JSON-formatted string into a native Python dictionary?

Accepted Answer

json.loads(). The json.loads() function in Python's json module deserializes a JSON-formatted string into a native Python dictionary (or list, depending on the JSON structure). It is the standard method for parsing JSON strings. The 's' in loads stands for 'string', distinguishing it from json.load(), which reads from a file-like object.

Answer

json.load()

Answer

json.read()

Answer

json.parse()

Question 2

An automation script performs a NETCONF transaction that triggers an alarm. You want to retrieve current system alarms using the Junos XML API. Which RPC tag represents this request?

Accepted Answer

. The RPC retrieves active system alarms from the Junos device.

Answer

<retrieve-alarms>

Answer

<get-system-alarms>

Answer

<get-chassis-alarms>

Question 3

An engineer is building a Python application to manage Junos devices. They need to open a NETCONF session, retrieve the device's hostname and model, and handle exceptions if the device is unreachable. Which Junos PyEZ component is designed specifically for establishing the NETCONF session and executing RPCs?

Accepted Answer

The Device class, which handles connection, authentication, and RPC execution over NETCONF.. The Device class is the PyEZ component that establishes and manages the NETCONF session, handles authentication, and executes RPCs or CLI commands. It is the correct choice for connecting to a device, retrieving operational facts like hostname and model, and handling connection exceptions. The Config, Table, and Meta classes serve configuration management, data transformation, and internal class generation, respectively, not session establishment.

Answer

The Config class, which locks the candidate configuration and commits changes.

Answer

The Table class, which maps Junos XML output to Python dictionaries for operational commands.

Answer

The Meta class, which dynamically generates Python methods for YANG models on the device.

Question 4

When serializing complex nested Python dictionaries to JSON, which THREE data types will cause a TypeError unless handled by a custom default encoder function? (Choose three)

Accepted Answer

Python set objects. Option B (Python set objects) is correct because the json module has no native representation for sets, so json.dumps() raises TypeError: Object of type set is not JSON serializable unless a custom default function converts it (e.g., to a list). Option C (Custom class instances) is correct because arbitrary user-defined objects are not JSON-serializable by default; json.dumps() only knows how to encode dict, list, tuple, str, int, float, bool, and None, so a custom default handler must return a serializable representation such as obj.__dict__. Option E (Complex numbers) is correct because Python's complex type is not among the supported JSON types and json.dumps(1+2j) raises TypeError, requiring a custom encoder to convert it (e.g., to a string or a [real, imag] list). Option A (Standard string objects) is not correct because str is natively supported and serializes directly to a JSON string. Option D (Boolean values) is not correct because bool is natively supported and serializes to JSON true/false.

Answer

Standard string objects

Answer

Boolean values

Question 5

During a NETCONF session with a Junos device, an automation script issues an RPC to load a configuration. The device returns a response containing an <rpc-error> tag. What does this indicate?

Accepted Answer

The configuration or RPC request failed validation, syntax checking, or execution constraints on the device.. In NETCONF (RFC 6241), the element is returned inside the when the server cannot successfully process the RPC. It signals that the request failed validation, hit a syntax error, violated a data-model constraint, or was rejected by the device's configuration engine — not that the session or hardware failed. The error contains sub-elements like , , , and that describe the exact failure.

Answer

The Junos routing engine is operating at 100% CPU capacity.

Answer

The NETCONF session has successfully terminated with a normal exit code.

Answer

The physical optical link on the management port has failed.

Question 6

Which TWO actions occur during the initial NETCONF session establishment phase between a client and a Junos device? (Choose two)

Accepted Answer

The client and server exchange messages to negotiate supported capabilities.. Option A is correct because NETCONF session establishment begins with both peers exchanging messages that advertise their capabilities and, in the server's case, the session-id, allowing the client and Junos device to negotiate supported features such as candidate configuration or confirmed commit. Option D is correct because NETCONF runs over SSH on Junos (typically TCP port 830), so the client must complete SSH authentication before the NETCONF subsystem is started and the exchange can occur. Option B is wrong because a RPC is a configuration operation performed after the session is established, not part of session initialization. Option C is wrong because NETCONF session setup does not reload or restart routing engine control-plane daemons. Option E is wrong because the running configuration datastore is not automatically locked during session establishment; locking is an explicit client action via the RPC.

Answer

The client sends an immediate <commit> RPC to initialize the session.

Answer

The routing engine reloads its control plane daemons.

Answer

The Junos device automatically locks the running configuration datastore.

Question 7

An automation engineer needs to include comments explaining complex network parameters inside a Junos automation data file. Which serialization format should the engineer select?

Accepted Answer

YAML. YAML natively supports comments using the hash (#) symbol, whereas standard JSON does not support comments.

Answer

CSV

Answer

JSON

Answer

Pickle

Question 8

Which THREE attributes are available within the <edit-config> operation element in NETCONF to specify the modification action on a target node? (Choose three)

Accepted Answer

delete. The NETCONF <edit-config> operation supports the operation attribute, whose valid values are merge, replace, create, delete, and remove. Option A (delete) is correct because the delete operation attribute removes a node that exists in the target datastore, and it is one of the standard values defined in RFC 6241. Option B (replace) is correct because replace overwrites the target node's value or configuration with the supplied content, creating it if it does not exist. Option E (merge) is correct because merge is the default operation attribute value, combining the supplied configuration with the existing target datastore content. Option C (append) is not a valid NETCONF operation attribute value; list/leaf-list additions are handled via merge or the insert/key attributes. Option D (modify) is not a defined operation attribute value in NETCONF; modification is achieved through merge, replace, create, delete, or remove.

Answer

append

Answer

modify

Question 9

A DevOps engineer is designing a CI/CD pipeline for validating Junos configuration changes prior to deployment. Which THREE actions are typically performed during the automated CI pipeline 'test' or 'validate' stage? (Choose THREE)

Accepted Answer

Performing dry-run validation checks against staging or virtual Junos instances (vSRX). Option A is correct because the validate/test stage of a CI pipeline should exercise candidate configurations against non-production targets such as staging devices or virtual Junos instances (vSRX/vMX), often using 'commit check' or 'commit dry-run' to confirm the config loads and behaves as expected without impacting live traffic. Option C is correct because automated linters and style checks (for example flake8, pylint, yamllint, or ansible-lint) catch syntax errors, formatting issues, and common bugs in Python automation scripts and Jinja2 templates before they are rendered and pushed to devices. Option D is correct because static syntax and semantic validation against Junos schemas (for example 'commit check' or Junos PyEZ/YANG-based validation) verifies that the candidate configuration is syntactically valid and semantically consistent with the device's data model before deployment. Option B is not part of a test/validate stage because rebooting a production core routing engine is a disruptive deployment/remediation action, not a validation step, and would cause an outage. Option E is not part of an automated CI test stage because manually logging into physical CLI consoles is a manual troubleshooting activity that contradicts the goal of automated, repeatable validation.

Answer

Immediately rebooting the production core routing engine to apply all updates

Answer

Manually logging into physical CLI consoles to troubleshoot cabling

Question 10

Which statement correctly identifies the relationship between Junos REST API and NETCONF data models?

Accepted Answer

Both protocols leverage the same underlying Junos data models and management infrastructure.. Both Junos REST API and NETCONF leverage the same underlying Junos data models and management infrastructure. The Junos REST API is essentially a RESTful interface to the Junos configuration and operational data, which is modeled using YANG and accessed via NETCONF. Therefore, they share the same data models and management framework.

Answer

REST API bypasses all Junos data models and writes directly to kernel memory.

Answer

NETCONF uses YANG models, whereas REST API uses proprietary relational databases.

Answer

NETCONF is deprecated in favor of REST API for all Junos configuration tasks.

Question 11

You are writing a Python script to retrieve the operational state of interfaces from a Junos device using NETCONF. Which XML RPC element must be enclosed within the <rpc> tag to request operational data?

Accepted Answer

. The rpc tag is used to retrieve both configuration and operational data, whereas is restricted to configuration data.

Answer

<pull-operational>

Answer

<get-rpc-reply>

Answer

<get-config>

Question 12

You are writing a Python script using the PyEZ library to retrieve interface facts from a Juniper EX Series switch. The resulting data structure is stored in a Python dictionary. You need to dump this dictionary into a YAML file so it can be read by an Ansible playbook later. Which PyYAML function should you use to convert the Python dictionary into a YAML-formatted string or file stream?

Accepted Answer

yaml.dump(). yaml.dump() is the standard PyYAML function used to serialize Python objects (such as dictionaries) into a YAML-formatted stream or string.

Answer

yaml.load()

Answer

yaml.serialize()

Answer

yaml.safe_load()

Question 13

Which THREE actions can be performed using the Junos REST API operational endpoints? (Choose three)

Accepted Answer

Fetch interface packet counters and operational states.. Option B is correct because Junos REST API operational endpoints expose RPCs such as get-interface-information, which return live interface packet counters and operational states (up/down, errors, etc.) in JSON or XML. Option C is correct because operational endpoints include RPCs like get-system-information and get-chassis-inventory, which retrieve hardware and software inventory details from the device. Option E is correct because the REST API operational endpoint accepts arbitrary operational RPCs, including get-route-information, invoked via HTTP GET/POST to /rpc/get-route-information. Option A is not correct because modifying the startup configuration file on disk is a configuration-management task handled through configuration endpoints or CLI, not operational RPC endpoints. Option D is not correct because formatting and partitioning local SSDs is a low-level maintenance action not exposed through Junos REST operational RPCs.

Answer

Directly modify the startup configuration file on the hard disk.

Answer

Format and partition local storage solid-state drives.

Question 14

Which THREE principles are foundational to the DevOps movement when applied to network engineering? (Choose three)

Accepted Answer

Continuous monitoring and feedback loops for network telemetry. Option A is correct because DevOps network engineering depends on continuous monitoring and feedback loops—streaming telemetry via SNMP, gNMI, syslog, or NetFlow into observability platforms—so that changes are validated and issues detected immediately rather than discovered later. Option D is correct because the DevOps culture emphasizes shared responsibility between network, development, and operations teams, plus blameless post-mortems and rapid learning from failures, which is essential for safely iterating on network changes. Option E is correct because automating repetitive provisioning and configuration tasks—using tools such as Ansible, Terraform, or Python scripts against APIs—is a core DevOps practice that removes manual drift and enables consistent, repeatable network deployments. Option B does not belong because strict siloing directly contradicts DevOps's cross-functional collaboration and shared ownership model. Option C does not belong because relying solely on annual manual audits is a slow, reactive practice that DevOps replaces with continuous automated validation and monitoring.

Answer

Strict siloing of operational teams from software developers

Answer

Relying solely on annual manual network audits

Question 15

An automation engineer is building a Python script that generates Junos configuration snippets from a JSON payload. The payload contains nested objects representing interfaces, units, and addresses. The engineer uses json.loads and then accesses data['interfaces']['ge-0/0/0']['unit'][0]['family']['inet']['address'][0]['name']. Which JSON structural feature makes this nested access pattern possible?

Accepted Answer

JSON objects map to Python dictionaries, and JSON arrays map to Python lists, allowing mixed nesting.. The json module maps JSON objects to Python dict and JSON arrays to list. Since dicts and lists can contain each other to arbitrary depth, complex Junos configuration hierarchies can be represented and traversed with chained key lookups and integer indices. This direct structural correspondence is what makes the long access expression valid without any additional query language.

Answer

JSON supports XPath expressions natively for navigating nested structures.

Answer

JSON arrays map to Python sets, enabling fast membership tests during traversal.

Answer

JSON objects map to Python tuples, which preserve order and allow positional access.