Google Apigee-API-Engineer Exam Questions 2025

The security team's concern is about access control—specifically, that any internal service can call the backend APIs, not just the intended website. The current architecture bypasses any policy enforcement point. Recommending a design change to place an Apigee microgateway in front of the backend APIs directly solves this problem. The microgateway acts as a lightweight, containerized policy enforcement point for internal ("east-west") traffic. This allows the Apigee team to apply standard security policies like API key validation, OAuth, or IP-based access control, ensuring that only authorized clients (like the website) can access the backend services.

A. You should recommend an Apigee Edge Access Control policy: This policy would be ineffective because the question states the website calls the backend APIs directly, meaning traffic does not pass through the Apigee Edge gateway where policies are enforced.

B. You should recommend that the backend API's use TLS v12 to secure their APIs: TLS encrypts data in transit, protecting against eavesdropping. However, it does not solve the access control problem; an unauthorized internal client could still establish a valid TLS connection and call the API.

C. You should recommend the use of custom secure headers with time stamp verification: This creates a custom, non-standard security solution that is difficult to manage, scale, and audit. It is better to use a standard API management component like a microgateway for this purpose.

---

1. Google Cloud - Apigee Documentation

"About Apigee hybrid": This document explains the role of the hybrid runtime plane

which is based on a microgateway architecture. It states

"All API traffic passes through and is processed within the runtime plane... This allows you to leverage Apigee API management capabilities like security

traffic management

and analytics...". This supports using a microgateway as the policy enforcement point for API traffic.

Reference: Google Cloud Documentation > Apigee > Hybrid > gcp/apigee/hybrid/v1.8/about-hybrid

2. Google Cloud - Apigee Documentation

"Microgateway versus API proxy": This section clarifies the use case for a microgateway. It highlights that a key reason to use a microgateway is for "low latency for services that run in close proximity

" which is typical for internal traffic between a website's backend and other backend services within the same network or cloud environment.

Reference: Google Cloud Documentation > Apigee > Edge > private-cloud/v4.50.00/edge-microgateway-overview#microgatewayversusapiproxy

3. Google Cloud - Apigee Documentation

"Access Control policy": The documentation for this policy states

"The AccessControl policy lets you allow or deny access to your APIs by specific IP addresses." This confirms its function is access control

but its placement within an API proxy flow means it is only effective if traffic is routed through the Apigee gateway.

Reference: Google Cloud Documentation > Apigee > Edge > api-platform/reference/policies/access-control-policy

The Flow Callout policy is used to invoke a Shared Flow from within an API proxy or another Shared Flow. It can be attached to the PreFlow, PostFlow, or any conditional Flow within a ProxyEndpoint or TargetEndpoint. It can also be used inside one Shared Flow to call another, a practice known as "chaining." The only location where it cannot be used is the PostClientFlow, which executes after the response is sent to the client and has a restricted set of allowable policies that does not include Flow Callout.

C. Only in the Flow phase of ProxyEndpoint or TargetEndpoint: This is incorrect because a Flow Callout can also be used in the PreFlow and PostFlow phases, not just conditional Flows.

D. Anywhere except another Shared Flow: This is incorrect. The official documentation explicitly states that Shared Flows can be "chained" by using a Flow Callout policy within one Shared Flow to execute another.

E. Only in ProxyEndpoint PreFlow or TargetEndpoint PostFlow: This is too restrictive. A common use case is to place a Flow Callout within a conditional Flow to execute reusable logic for a specific API resource.

1. Google Cloud

Apigee Documentation

"Shared flows": "You can also chain shared flows together

that is

have a Flow Callout policy execute another shared flow." This supports answer B and refutes answer D.

2. Google Cloud

Apigee Documentation

"Flow Callout policy": "You can use a Flow Callout policy in a ProxyEndpoint or TargetEndpoint." This general statement supports its use in various flow locations.

3. Google Cloud

Apigee Documentation

"Configuring flows"

Section: PostClientFlow: This section lists the specific policies that can be attached to the PostClientFlow. The FlowCallout policy is not on this list

which includes AccessControl

KeyValueMapOperations

MessageLogging

ServiceCallout

and StatisticsCollector. This supports the exclusion mentioned in answer A.

In Apigee, to prevent sensitive data from being exposed in trace or debug sessions, you must assign it to a private variable. The private. prefix is a specific mechanism used to designate a variable as private. When a value is retrieved from an encrypted Key Value Map (KVM) using the KeyValueMapOperations policy and assigned to a variable with this prefix (e.g., private.mysecret), Apigee's trace tool will not capture or display its value. This is a critical security practice for handling credentials, tokens, or other confidential information.

A. encrypted: This term describes the state of the KVM itself, not a variable prefix used to hide data in a trace session.

B. mask: While related to the concept of data masking, private. is the specific, required prefix for the variable name to prevent its capture.

C. kvm: This is a common, conventional prefix for KVM-related variables but provides no inherent security or masking functionality in trace.

E. hidden: This is not a recognized or functional variable prefix within Apigee for masking data in trace sessions.

1. Google Cloud

Apigee Documentation

"KeyValueMapOperations policy": Under the section for the element

the documentation explicitly states: "To retrieve the value into a private variable that will not be visible in a Trace session

use the private. prefix on the variable name in the assignTo attribute."

2. Google Cloud

Apigee Documentation

"Working with key value maps": In the section "Retrieving values from a KVM

" the documentation notes the use of the private. prefix for sensitive data: "If the data is sensitive

use the private. prefix in the variable name... The private. prefix masks the variable in Trace and debug sessions."

Edge Microgateway-aware proxies are standard Apigee proxies that serve as a configuration source for a Microgateway instance. A key feature of Apigee proxies is the ability to use conditional flows to apply logic and policies to specific request paths, verbs, or other conditions. This feature is fully supported for microgateway-aware proxies. It allows developers to define granular enforcement rules, such as applying a stricter quota policy to a write operation (POST /resource) and a more lenient one to a read operation (GET /resource) within the same proxy, which Microgateway will then download and enforce locally.

A. Edge Microgateway-aware proxies must point to a Node js ScnptTarget

This is incorrect. Microgateway-aware proxies often have no target at all (a "no target" proxy) because their primary purpose is to bundle policies for Microgateway, not to route traffic.

B. Edge Microgateway-aware proxies should at least contain a quota or OAuth2 policy

This is not a requirement. A microgateway-aware proxy could validly contain only a Spike Arrest policy or just be used for API key validation without other specific policies.

D. Edge Microgateway-aware proxies must use HTTPTargetConnection in the TargetEndpoint

This is incorrect. As these proxies are not primarily for routing traffic to a backend, they typically do not use an HTTPTargetConnection. A "no target" configuration is common.

---

1. Google Cloud

Apigee Documentation

"Operations and flows": This document explicitly states

"You can attach policies to flows in the microgateway-aware proxy

giving you the ability to apply fine-grained policy enforcement on a per-resource basis." It provides a clear XML example of a conditional flow () being used in a microgateway-aware proxy. This directly supports option C.

2. Google Cloud

Apigee Documentation

"Set up and configure Edge Microgateway"

Step 3: Create a microgateway-aware proxy: This tutorial section notes

"The proxy can be a simple 'no target' proxy... The proxy's TargetEndpoint must be configured with a element

but it does not have to resolve to a real target..." This confirms that a specific

functional HTTPTargetConnection or ScriptTarget is not required

invalidating options A and D.

3. Google Cloud

Apigee Documentation

"What is Edge Microgateway?": Under the section "What policies are enforced by Edge Microgateway?"

the documentation lists Spike Arrest

Quota

OAuth v2

and Verify API Key. It does not state that a proxy must contain a Quota or OAuth2 policy

invalidating the strict requirement implied in option B.

Apigee provides two primary techniques for dynamically selecting a target endpoint at runtime. The first is a declarative approach using conditional RouteRules within the ProxyEndpoint. Apigee evaluates these rules sequentially, and the first rule whose condition evaluates to true directs the flow to the specified TargetEndpoint. The second is a programmatic approach, typically using a JavaScript policy. This policy can execute code to determine the appropriate target URL and then dynamically set the target.url flow variable, which overrides the statically configured URL in the TargetEndpoint definition.

A: "Routing tables" is not a standard Apigee configuration object. While you use the Management API to configure RouteRules, the API itself is a configuration tool, not the runtime mechanism that makes the dynamic choice.

D: By default, an API proxy has a static route to a single, pre-configured target endpoint. Dynamic routing requires explicit configuration and is not a default behavior.

1. Google Cloud Apigee Documentation

"Conditional routing": This document explicitly describes the use of RouteRule elements with conditions to achieve dynamic routing. It states

"You can add routing logic to your API proxy flow by adding conditional routes to your TargetEndpoint configuration... A RouteRule forwards a request to a particular TargetEndpoint if the condition in the route rule evaluates to true." (See the section on "Conditional routes").

2. Google Cloud Apigee Documentation

"Flow variables reference": The documentation for the target.url variable states

"In a JavaScript policy

you can read and set this variable." This confirms that scripts can programmatically alter the target URL at runtime.

3. Google Cloud Apigee Documentation

"Route requests to the proper backend server": This guide provides a clear example of dynamic routing. Under the section "Dynamically routing to a target with a script

" it demonstrates using a JavaScript policy to set the target.url variable. It states

"You can dynamically set a target URL with code... the script overrides the static URL... configured in the TargetEndpoint XML block."

The most appropriate and standard method in Apigee to implement a hot-warm (active-passive) failover is by using the built-in load balancing capabilities of the TargetEndpoint. This involves defining each datacenter endpoint as a TargetServer. Within the TargetEndpoint's LoadBalancer configuration, the warm datacenter's TargetServer is marked with the true property. Apigee will then direct all traffic to the primary (hot) server(s). If the health monitor detects that all primary servers are unavailable, Apigee automatically fails over and routes traffic to the designated fallback (warm) server. This declarative approach is the intended design pattern for this scenario.

A. Using a Java Callout is an overly complex, imperative approach that bypasses Apigee's built-in, optimized routing features, making the proxy harder to maintain and less performant.

B. A FaultRule's primary purpose is to catch errors and return a customized error response to the client, not to re-route the original request to a different backend.

C. Service Callouts are designed for invoking external services from within a proxy flow (e.g., for enrichment), not for handling the primary target request and its failover logic.

1. Google Cloud

Apigee Documentation

"Load balancing across backend servers": This official documentation explicitly describes the use of fallback servers for failover scenarios. In the section "Configuring fallback servers

" it states

"When Apigee determines that all your primary servers are unavailable

it automatically routes all traffic to your fallback servers...". The provided XML configuration example clearly shows the use of the true element within a definition to designate a server for failover.

Reference Location: Google Cloud > Apigee > Documentation > Reference > API proxy configuration reference > Endpoint properties reference > Load balancing across backend servers.

2. Google Cloud

Apigee Documentation

"TargetEndpoint configuration": This document details the structure of a TargetEndpoint. The element is shown as a child of

and it supports one or more elements. This confirms that load balancing and server definition are integral parts of the TargetEndpoint configuration

which is the correct place to manage backend routing and failover.

Reference Location: Google Cloud > Apigee > Documentation > Reference > API proxy configuration reference > Endpoint properties reference > TargetEndpoint configuration.

The Apigee ExtractVariables policy uses JSONPath to extract data from a message payload that is in JSON format. For Apigee's parser to correctly interpret the message body as JSON, the Content-Type header of that message (either the request or response) must be explicitly set to application/json. If the header is missing, incorrect, or set to another value (e.g., text/plain), the policy will not treat the payload as a JSON object. Consequently, the JSONPath expression will fail to find any matching paths, resulting in the query not returning the expected value.

A. The Accept header indicates the media types the client can process in a response; it does not describe the format of the current payload being parsed.

B. The Accept header is irrelevant for parsing the current message's payload. It is a client-side header used for content negotiation for the response.

C. While Content-Type is the correct header, text/json is an obsolete and non-standard media type. The official standard specified by IETF RFC 8259 is application/json.

1. Google Cloud Apigee Documentation

"Extract Variables policy": Under the element description

the documentation states: "The message must be parsed as JSON by Apigee. If the message is not valid JSON

or if the message is not parsed as JSON for other reasons (such as the Content-type header not being application/json)

the policy will not be able to extract any variables." This directly confirms that the Content-Type header must be application/json.

Source: Google Cloud Documentation > Apigee > Reference > Policies > Extract Variables policy reference.

2. IETF RFC 8259

"The JavaScript Object Notation (JSON) Data Interchange Format": This official standard defines the media type for JSON.

Section 11

"IANA Considerations": "The MIME media type for JSON text is application/json." This establishes application/json as the correct and standard value.

A data dictionary serves as a centralized, authoritative source of truth for data definitions, including field names, data types, and business rules. Creating a data dictionary directly addresses the root cause of confusion by establishing a clear, consistent, and shared understanding of data elements across the project. This is a foundational practice in data governance and API design that scales effectively as the project grows. It provides the standard against which developers can code and reviewers can validate, ensuring clarity and consistency in the API contract and its implementation.

A. A static code analysis tool is for enforcing a convention, not for creating it. The rules and definitions must be established first, which is the purpose of a data dictionary.

B. Relying solely on code reviews is inefficient and subjective without a documented standard. Reviewers may have different interpretations, failing to solve the core consistency problem.

D. Creating a unified data model for all possible use cases is often an overly complex and rigid approach that can lead to "analysis paralysis" and hinder agile development.

1. Google Cloud - API design guide (AIP-140): This guide emphasizes the critical importance of consistent and predictable naming conventions for API fields. It states

"Field names should be snakecase... By using consistent field names

users who are familiar with one part of the API can more easily understand other parts of the API." A data dictionary is the formal mechanism for defining and documenting these conventions.

Source: Google Cloud

API design guide

AIP-140 Field names.

2. Apigee Documentation - API-first approach: The API-first philosophy

central to Apigee's methodology

prioritizes designing a clear and stable API contract before writing code. A data dictionary is a key artifact in this design phase

ensuring all stakeholders agree on the data model and its naming.

Source: Apigee Docs

"Develop an API-first strategy".

3. University Courseware - Database Design: Foundational computer science and database design principles teach that a data dictionary is the central repository of metadata about the database. It contains the "data about the data

" including names

definitions

and data types

to prevent ambiguity and ensure consistency.

Source: Stanford University

CS 145: Introduction to Databases

Course Notes on Data Dictionaries.

The recommended solution is to use a TargetServer configuration. TargetServers are environment-scoped objects in Apigee that decouple the concrete backend endpoint URLs from the API proxy's TargetEndpoint definition. You can define a TargetServer with the same name (e.g., 'backend-service') in each environment (dev, test, prod), but with a different host/IP address for each. The API proxy then references this named TargetServer. When the proxy is deployed to an environment, it resolves to the backend configured for that specific environment, allowing the same proxy bundle to be promoted without modification.

A. Java/JavaScript/Python callout: This is not recommended as it adds unnecessary code complexity and mixes configuration with runtime logic, making the proxy harder to maintain.

B. TargetEndpoint configuration: Hardcoding a URL directly in the TargetEndpoint is bad practice because it requires changing the proxy bundle for each environment.

C. RouteRules: RouteRules are used for conditional routing based on request characteristics (e.g., path, headers), not for managing environment-specific backend endpoints.

1. Google Cloud Apigee Documentation

"Load balancing across backend servers": This document explicitly states

"A TargetServer decouples concrete endpoint URLs from TargetEndpoint configurations. Instead of defining a concrete URL in your configuration

you can configure one or more named TargetServers... The TargetServer definition itself is stored in the environment..." This directly supports using TargetServer for environment-specific backends.

2. Google Cloud Apigee Documentation

"TargetEndpoint configuration reference": Under the element section

the documentation shows how to use to reference a TargetServer by name ()

which is the mechanism for implementing this pattern. It contrasts this with using a direct .

3. Google Cloud Apigee Documentation

"About environments and environment groups": This document clarifies that an environment is a "runtime execution context for the API proxies" and that certain configurations

like TargetServers and Key Value Maps (KVMs)

are scoped to these environments. This reinforces that TargetServer is the correct construct for environment-specific configurations.

The XMLToJSON policy is the most appropriate choice for converting a SOAP response to a JSON response. SOAP (Simple Object Access Protocol) messages are fundamentally structured in XML format. The XMLToJSON policy is specifically designed to parse an XML payload, such as a SOAP message body, and transform it into a corresponding JSON structure. This policy provides various options to control the conversion process, handling XML elements, attributes, and text content to produce a well-formed JSON output, making it the best tool for this specific task.

A. AssignMessage: This policy creates or modifies messages but does not have built-in logic for format transformation between XML and JSON.

B. Message Validation: This policy is used to validate message formats against a schema (e.g., XSD or JSON Schema), not to convert them.

C. SOAPToJSON: This is not a standard, existing policy type within the Google Apigee platform; it is a plausible but incorrect distractor.

1. Google Cloud Apigee Documentation

"XML to JSON policy": "The XMLtoJSON policy lets you convert messages from the Extensible Markup Language (XML) format to JavaScript Object Notation (JSON)." This directly confirms that XMLToJSON is the correct policy for converting XML-based messages like SOAP into JSON.

Source: Google Cloud

Apigee Documentation

Policy reference

XML to JSON policy.

2. Google Cloud Apigee Documentation

"Assign Message policy": "The AssignMessage policy changes or creates new request and response messages during an API proxy flow. It lets you perform...Set the payload of a message." While it can set a payload

it does not perform the complex logic of format conversion itself.

Source: Google Cloud

Apigee Documentation

Policy reference

Assign Message policy.

3. Google Cloud Apigee Documentation

"Message Validation policy": "The MessageValidation policy validates a request or response message against a defined schema...For XML messages

Apigee uses the XML Schema Definition (XSD)." This clearly defines its purpose as validation

not transformation.

Source: Google Cloud

Apigee Documentation

Policy reference

Message Validation policy.

4. Google Cloud Apigee Documentation

"Policy reference overview": A review of the complete list of available policies in the official Apigee documentation confirms that a policy named SOAPToJSON does not exist.

Source: Google Cloud

Apigee Documentation

Policy reference overview.