{"id":13166,"date":"2026-09-16T06:46:14","date_gmt":"2026-09-16T06:46:14","guid":{"rendered":"https:\/\/www.examlabs.com\/certification\/?p=13166"},"modified":"2026-09-16T07:23:17","modified_gmt":"2026-09-16T07:23:17","slug":"google-professional-cloud-devops-engineer-practice-test-questions-and-exam-dumps-part-14-q261-q280","status":"publish","type":"post","link":"https:\/\/www.examlabs.com\/certification\/google-professional-cloud-devops-engineer-practice-test-questions-and-exam-dumps-part-14-q261-q280\/","title":{"rendered":"Google Professional Cloud DevOps Engineer Practice Test Questions and Exam Dumps Part 14 Q261 – Q280"},"content":{"rendered":"

<\/h2>\n

View Full <\/b>Google Professional Cloud DevOps Engineer Exam Dumps<\/b><\/a> and Practice Test Dumps.<\/b><\/h2>\n

 <\/p>\n

Question 261<\/b><\/h3>\n

How can an organization route specific subset logs from Cloud Logging to external destinations like Pub\/Sub or BigQuery?<\/b><\/p>\n

    \n
  1. By reading compute instance serial port logs manually<\/span><\/li>\n
  2. By deleting log buckets every night<\/span><\/li>\n
  3. By configuring Cloud Logging log router sinks with inclusion filters<\/span><\/li>\n
  4. By storing plain text log summaries in local files<\/span><\/li>\n<\/ol>\n

    Correct Answer:<\/b> 3<\/b><\/p>\n

    Explanation:<\/b><\/p>\n

    Cloud Logging log router sinks allow administrators to filter and route log entries to various destinations, including BigQuery datasets, Cloud Storage buckets, and Pub\/Sub topics. By configuring targeted inclusion or exclusion filters, teams can export specific subsets of logs for long-term archiving, security analysis, or real-time event processing. Sinks enable decentralized log management and compliance auditing across multi-project cloud environments. Exporting operational telemetry to external analytical data warehouses transforms raw log streams into actionable intelligence, empowering security teams to detect anomalies and troubleshoot distributed system failures efficiently without overwhelming default logging storage quotas.<\/span><\/p>\n

    Question 262<\/b><\/h3>\n

    What is the primary function of the GKE Vertical Pod Autoscaler (VPA)?<\/b><\/p>\n

      \n
    1. Automatically recommending or adjusting CPU and memory resource requests for running containers based on usage history<\/span><\/li>\n
    2. Automatically creating new virtual machine nodes when pod counts increase<\/span><\/li>\n
    3. Deleting old container images from Artifact Registry storage repositories<\/span><\/li>\n
    4. Rotating database passwords automatically every weekend<\/span><\/li>\n<\/ol>\n

      Correct Answer:<\/b> 1<\/b><\/p>\n

      Explanation:<\/b><\/p>\n

      The GKE Vertical Pod Autoscaler analyzes CPU and memory utilization history of container workloads and automatically adjusts resource requests and limits to match actual operational demand. VPA prevents container out-of-memory crashes and optimizes cluster capacity by eliminating over-provisioned resource allocations. It can operate in recommendation mode or apply updates dynamically by restarting pods during maintenance windows. Proper vertical scaling ensures cost efficiency and stable application performance across dynamic microservice architectures running on Google Kubernetes Engine clusters, reducing the manual burden of cluster capacity planning for DevOps engineers.<\/span><\/p>\n

      Question 263<\/b><\/h3>\n

      How does Terraform ensure state file consistency when multiple engineers collaborate on infrastructure deployments?<\/b><\/p>\n

        \n
      1. By storing state files unencrypted in local laptop directories<\/span><\/li>\n
      2. By deleting historical state snapshots after every build run<\/span><\/li>\n
      3. By routing all state files through public HTTP proxies<\/span><\/li>\n
      4. By utilizing remote backend storage with state locking mechanisms like Cloud Storage<\/span><\/li>\n<\/ol>\n

        Correct Answer:<\/b> 4<\/b><\/p>\n

        Explanation:<\/b><\/p>\n

        Terraform supports remote backends, such as Google Cloud Storage, which securely store infrastructure state files and support state locking mechanisms. State locking prevents concurrent modifications by multiple engineers or CI\/CD pipelines, avoiding race conditions, state file corruption, and conflicting resource provisioning operations. Remote state management ensures a single source of truth for infrastructure metadata across distributed development teams. Encrypting state files in managed cloud storage protects sensitive infrastructure secrets and resource identifiers, reinforcing compliance and security baselines for enterprise infrastructure-as-code deployment workflows.<\/span><\/p>\n

        Question 264<\/b><\/h3>\n

        How can developers pass dynamic parameters into Cloud Build configuration files during pipeline execution?<\/b><\/p>\n

          \n
        1. By hardcoding static strings inside Dockerfile build layers<\/span><\/li>\n
        2. By utilizing user-defined substitution variables passed via command-line flags or trigger payloads<\/span><\/li>\n
        3. By printing environment variables to unencrypted public log files<\/span><\/li>\n
        4. By deleting build configurations after every run<\/span><\/li>\n<\/ol>\n

          Correct Answer:<\/b> 2<\/b><\/p>\n

          Explanation:<\/b><\/p>\n

          Cloud Build substitution variables allow developers to inject dynamic parameters\u2014such as branch names, commit hashes, or environment-specific tags\u2014into build configuration files at runtime. Substitutions make build scripts reusable across multiple environments like staging and production without requiring hardcoded configuration changes. Triggers can automatically populate default substitution values based on Git repository webhook events. Utilizing dynamic variables simplifies CI\/CD pipeline maintenance, ensures consistent build artifacts, and enhances overall automation flexibility across complex software delivery workflows and multi-project cloud environments.<\/span><\/p>\n

          Question 265<\/b><\/h3>\n

          What is the primary function of Packet Mirroring in Google Cloud VPC networks?<\/b><\/p>\n

            \n
          1. Compiling Java source code into container images<\/span><\/li>\n
          2. Calculating monthly cloud billing invoice discounts<\/span><\/li>\n
          3. Cloning and forwarding designated network traffic packets to security inspection tools<\/span><\/li>\n
          4. Deleting firewall rules automatically when traffic drops<\/span><\/li>\n<\/ol>\n

            Correct Answer:<\/b> 3<\/b><\/p>\n

            Explanation:<\/b><\/p>\n

            Packet Mirroring clones and forwards network traffic flowing across virtual machine instances to designated collector or security analysis tools for deep inspection, threat detection, and forensic investigation. It operates transparently without interrupting normal packet routing or application performance. Security operations teams rely on packet mirroring to monitor suspicious network behavior, detect intrusions, and satisfy rigorous compliance mandates. Capturing granular network telemetry aids in troubleshooting complex connectivity issues and auditing network perimeters across multi-project cloud deployments and sensitive enterprise architectures.<\/span><\/p>\n

            Question 266<\/b><\/h3>\n

            How do Cloud SQL maintenance windows minimize operational disruption during database updates?<\/b><\/p>\n

              \n
            1. By scheduling automated database patches during predefined low-traffic time intervals<\/span><\/li>\n
            2. By deleting database tables automatically when error rates spike<\/span><\/li>\n
            3. By routing public traffic through unencrypted proxy servers<\/span><\/li>\n
            4. By stopping all virtual machine instances indefinitely<\/span><\/li>\n<\/ol>\n

              Correct Answer:<\/b> 1<\/b><\/p>\n

              Explanation:<\/b><\/p>\n

              Cloud SQL maintenance windows allow administrators to specify preferred days and times for automated database software updates and patch applications, ensuring updates occur during anticipated low-traffic periods to minimize user disruption. Automated maintenance keeps databases secure and compliant without requiring manual administrative intervention. High-availability configurations ensure that failover mechanisms handle brief maintenance restarts gracefully. Defining predictable maintenance schedules empowers operations teams to balance security patching requirements with high application availability standards across mission-critical enterprise database workloads.<\/span><\/p>\n

              Question 267<\/b><\/h3>\n

              How does Secret Manager IAM access control protect sensitive credentials from unauthorized exposure?<\/b><\/p>\n

                \n
              1. By printing secrets to container standard output logs<\/span><\/li>\n
              2. By storing API keys in public Git repositories<\/span><\/li>\n
              3. By sharing administrator passwords openly via email<\/span><\/li>\n
              4. By enforcing the principle of least privilege through fine-grained IAM roles applied to specific secret resources<\/span><\/li>\n<\/ol>\n

                Correct Answer:<\/b> 4<\/b><\/p>\n

                Explanation:<\/b><\/p>\n

                Secret Manager uses fine-grained Identity and Access Management roles to control exactly which users, service accounts, or applications can access, view, or manage specific secret versions. Enforcing the principle of least privilege ensures that workloads only retrieve the credentials they strictly require, minimizing security blast radii if accounts are compromised. Centralized permission management prevents unauthorized access to sensitive API keys, database passwords, and cryptographic certificates. Robust access control policies maintain rigorous compliance standards and protect vital organizational data assets across multi-project enterprise cloud deployments.<\/span><\/p>\n

                Question 268<\/b><\/h3>\n

                What is the role of Cloud Deploy target configurations in multi-stage continuous delivery pipelines?<\/b><\/p>\n

                  \n
                1. To calculate monthly billing expenditures for finance stakeholders<\/span><\/li>\n
                2. To define the specific execution environments and runtime destinations where releases are promoted<\/span><\/li>\n
                3. To delete stale container images from registry storage buckets<\/span><\/li>\n
                4. To compile application source code binaries into Java archives<\/span><\/li>\n<\/ol>\n

                  Correct Answer:<\/b> 2<\/b><\/p>\n

                  Explanation:<\/b><\/p>\n

                  Cloud Deploy target configurations define the specific runtime destinations\u2014such as GKE clusters, Cloud Run services, or staging and production environments\u2014where software releases are deployed and tested. Targets specify execution parameters, verification requirements, and approval gate criteria needed before promoting artifacts through delivery pipelines. Clear target definitions standardize release management across diverse environments, ensuring consistent governance and deployment safety. Structured target promotion prevents unverified code from reaching production, streamlining continuous delivery workflows for enterprise engineering teams.<\/span><\/p>\n

                  Question 269<\/b><\/h3>\n

                  How does Service Directory help microservices discover backend endpoints across hybrid architectures?<\/b><\/p>\n

                    \n
                  1. By deleting log files automatically from storage buckets<\/span><\/li>\n
                  2. By encrypting virtual machine persistent disks with customer keys<\/span><\/li>\n
                  3. By providing a unified, managed service registry catalog for querying endpoint metadata securely<\/span><\/li>\n
                  4. By routing all traffic through public HTTP proxy servers<\/span><\/li>\n<\/ol>\n

                    Correct Answer:<\/b> 3<\/b><\/p>\n

                    Explanation:<\/b><\/p>\n

                    Service Directory acts as a managed service registry that provides a unified, highly available catalog for discovering and managing backend service endpoints across Google Cloud, hybrid on-premises, and multi-cloud environments. It enables microservices to locate and communicate with each other securely using up-to-date endpoint metadata. Centralized service discovery simplifies network configuration and improves application resiliency in complex distributed systems. Integrating service directory endpoints with traffic management tools ensures reliable routing and seamless integration across enterprise application portfolios without manual IP address maintenance.<\/span><\/p>\n

                    Question 270<\/b><\/h3>\n

                    How do Anthos Service Mesh telemetry features assist SRE teams in diagnosing performance bottlenecks?<\/b><\/p>\n

                      \n
                    1. By collecting and reporting standardized request metrics, access logs, and distributed traces automatically<\/span><\/li>\n
                    2. By deleting database records when memory limits are reached<\/span><\/li>\n
                    3. By calculating monthly billing invoice discounts for engineering teams<\/span><\/li>\n
                    4. By routing network packets through local terminal consoles<\/span><\/li>\n<\/ol>\n

                      Correct Answer:<\/b> 1<\/b><\/p>\n

                      Explanation:<\/b><\/p>\n

                      Anthos Service Mesh automatically collects and reports comprehensive telemetry data, including request volume, latency distributions, error rates, and distributed traces, without requiring application code modifications. SRE teams use this telemetry to visualize service dependencies, identify latency bottlenecks, and configure alerting policies easily. Centralized observability accelerates root-cause analysis during outages and provides deep visibility into microservice interactions. Leveraging managed service mesh telemetry eliminates complex third-party instrumentation setups while ensuring reliable performance tracking across large-scale containerized Kubernetes fleets.<\/span><\/p>\n

                      Question 271<\/b><\/h3>\n

                      What is the primary purpose of configuring custom rate-limiting rules in Cloud Armor security policies?<\/b><\/p>\n

                        \n
                      1. To compile Java source code binaries into container images<\/span><\/li>\n
                      2. To delete virtual machine instances when CPU utilization increases<\/span><\/li>\n
                      3. To encrypt database storage volumes using customer-managed keys<\/span><\/li>\n
                      4. To throttle or block clients exceeding specific request frequency thresholds to mitigate abuse<\/span><\/li>\n<\/ol>\n

                        Correct Answer:<\/b> 4<\/b><\/p>\n

                        Explanation:<\/b><\/p>\n

                        Cloud Armor custom rate-limiting rules monitor incoming request frequencies from specific client IP addresses or geographic regions and throttle or block requests that exceed defined thresholds. This capability mitigates brute-force login attacks, web scraping, and application-layer denial-of-service attempts at the network edge before traffic reaches backend workloads. Enforcing edge rate limits preserves application performance and availability during abusive traffic spikes. Configurable enforcement rules allow engineering teams to tailor defenses to specific application requirements while ensuring legitimate users experience uninterrupted service access.<\/span><\/p>\n

                        Question 272<\/b><\/h3>\n

                        How does Binary Authorization use attestations to enforce deployment security on GKE clusters?<\/b><\/p>\n

                          \n
                        1. By scanning IAM user accounts for administrative privileges<\/span><\/li>\n
                        2. By requiring signed cryptographic approvals from trusted authorities verifying build integrity before pod startup<\/span><\/li>\n
                        3. By deleting old log files automatically from Cloud Storage buckets<\/span><\/li>\n
                        4. By encrypting all inter-node network packets using IPsec tunnels<\/span><\/li>\n<\/ol>\n

                          Correct Answer:<\/b> 2<\/b><\/p>\n

                          Explanation:<\/b><\/p>\n

                          Binary Authorization uses attestations as a deployment-time security control where trusted build pipelines or security scanners cryptographically sign container images after successful vulnerability verification. GKE admission controllers check these attestations against security policies before allowing pods to execute, ensuring unverified or tampered code never reaches production. Attestation enforcement secures the software supply chain, stopping unauthorized deployments instantly. Centralized policy management maintains strict compliance across multi-project cloud deployments and protects critical workloads from malicious tampering.<\/span><\/p>\n

                          Question 273<\/b><\/h3>\n

                          How does Error Reporting group incoming exception logs from multiple microservices?<\/b><\/p>\n

                            \n
                          1. By deleting log files when storage quotas reach capacity limits<\/span><\/li>\n
                          2. By calculating monthly cloud billing invoice totals for finance teams<\/span><\/li>\n
                          3. By analyzing stack traces and automatically clustering identical error occurrences into single issues<\/span><\/li>\n
                          4. By routing network packet captures through virtual routers<\/span><\/li>\n<\/ol>\n

                            Correct Answer:<\/b> 3<\/b><\/p>\n

                            Explanation:<\/b><\/p>\n

                            Error Reporting analyzes incoming log streams in Cloud Logging, automatically parsing stack traces and clustering identical exception occurrences into unified issue groups. This intelligent grouping prevents alert fatigue and provides a clean dashboard tracking error frequencies, affected service versions, and first-seen timestamps. Developers receive instant notifications when critical errors occur, accelerating triage and remediation workflows. Centralized error tracking eliminates manual log searching, providing clear visibility into application health and improving overall system reliability across production microservice architectures.<\/span><\/p>\n

                            Question 274<\/b><\/h3>\n

                            What is the primary function of recording rules in Managed Service for Prometheus?<\/b><\/p>\n

                              \n
                            1. Precomputing frequently used or expensive queries and storing results as new time-series metrics<\/span><\/li>\n
                            2. Deleting historical log entries to save storage quotas<\/span><\/li>\n
                            3. Executing local shell scripts for database backups<\/span><\/li>\n
                            4. Compiling application source code binaries into container images<\/span><\/li>\n<\/ol>\n

                              Correct Answer:<\/b> 1<\/b><\/p>\n

                              Explanation:<\/b><\/p>\n

                              Recording rules in Managed Service for Prometheus allow operators to precompute frequently needed or computationally expensive expressions and save the results as new time-series metrics. Precomputing metrics accelerates dashboard loading times and simplifies complex alerting rule evaluations across large-scale GKE clusters. By reducing real-time query overhead, recording rules optimize monitoring performance and resource consumption. Integrating Prometheus recording rules with Cloud Monitoring ensures unified observability, enabling rapid anomaly detection and reliable performance tracking across container fleets without managing standalone server infrastructure.<\/span><\/p>\n

                              Question 275<\/b><\/h3>\n

                              How does the Network Intelligence Center Topology view assist operations teams in understanding cloud networks?<\/b><\/p>\n

                                \n
                              1. By deleting unused firewall rules automatically<\/span><\/li>\n
                              2. By calculating monthly billing invoice discounts for network usage<\/span><\/li>\n
                              3. By compiling Java source code into container images<\/span><\/li>\n
                              4. By providing an interactive graphical map of VPC networks, traffic flows, and resource relationships<\/span><\/li>\n<\/ol>\n

                                Correct Answer:<\/b> 4<\/b><\/p>\n

                                Explanation:<\/b><\/p>\n

                                Network Intelligence Center Topology view provides an interactive graphical map visualizing VPC networks, subnets, virtual machine instances, hybrid interconnects, and traffic flow relationships across Google Cloud environments. This visualization helps operations teams understand complex network architectures, inspect traffic paths, and troubleshoot connectivity bottlenecks quickly. Centralized topology mapping enhances network visibility and simplifies security auditing. Utilizing topology dashboards allows SREs to verify network segmentation and maintain resilient communication pathways across multi-project enterprise cloud deployments.<\/span><\/p>\n

                                Question 276<\/b><\/h3>\n

                                How do Artifact Registry remote repositories help engineering teams manage third-party dependencies?<\/b><\/p>\n

                                  \n
                                1. By deleting old container images automatically every night<\/span><\/li>\n
                                2. By caching external open-source packages locally to improve build reliability and speed<\/span><\/li>\n
                                3. By converting application code into serverless functions<\/span><\/li>\n
                                4. By publishing internal source code publicly on the internet<\/span><\/li>\n<\/ol>\n

                                  Correct Answer:<\/b> 2<\/b><\/p>\n

                                  Explanation:<\/b><\/p>\n

                                  Artifact Registry remote repositories act as transparent caching proxies for external public registries, storing third-party open-source packages locally within the organization’s cloud environment. Caching external dependencies protects build pipelines from upstream internet outages, rate limits, or unexpected package deletions, ensuring consistent and reliable build times. Local caching also accelerates dependency download speeds during continuous integration builds. Utilizing remote repositories streamlines software supply chain management, enhances security governance, and ensures robust artifact availability across enterprise software development workflows.<\/span><\/p>\n

                                  Question 277<\/b><\/h3>\n

                                  What is the function of concurrency settings in Cloud Run serverless container services?<\/b><\/p>\n

                                    \n
                                  1. Deleting container instances when memory limits are reached<\/span><\/li>\n
                                  2. Compiling source code binaries into executable packages<\/span><\/li>\n
                                  3. Controlling how many concurrent requests a single container instance can handle simultaneously<\/span><\/li>\n
                                  4. Routing network traffic through unencrypted public proxies<\/span><\/li>\n<\/ol>\n

                                    Correct Answer:<\/b> 3<\/b><\/p>\n

                                    Explanation:<\/b><\/p>\n

                                    Cloud Run concurrency settings define the maximum number of simultaneous requests that a single container instance can process at one time. Adjusting concurrency allows developers to optimize resource utilization and performance based on application threading models and workload characteristics. Higher concurrency maximizes resource efficiency for lightweight stateless applications, while lower concurrency ensures isolation for CPU-intensive tasks. Proper configuration balances compute resource scaling behavior, optimizes execution costs, and ensures stable application performance under varying traffic volumes across serverless architectures.<\/span><\/p>\n

                                    Question 278<\/b><\/h3>\n

                                    How do Cloud Monitoring uptime checks verify the availability of web applications globally?<\/b><\/p>\n

                                      \n
                                    1. By sending synthetic HTTP, HTTPS, or TCP requests from multiple geographic locations at regular intervals<\/span><\/li>\n
                                    2. By executing local shell scripts on virtual machine boot disks<\/span><\/li>\n
                                    3. By scanning container images for security vulnerabilities<\/span><\/li>\n
                                    4. By compiling monthly financial invoices for stakeholders<\/span><\/li>\n<\/ol>\n

                                      Correct Answer:<\/b> 1<\/b><\/p>\n

                                      Explanation:<\/b><\/p>\n

                                      Cloud Monitoring uptime checks provide continuous black-box monitoring by sending synthetic requests from various global geographical locations to verify web application availability and responsiveness. These checks ensure services remain accessible for external users regardless of internal infrastructure health metrics. Configuring uptime checks allows engineering teams to detect regional network outages or application crashes instantly before customers report disruptions. Automated alerts tied to these checks trigger immediate incident response workflows, minimizing total downtime and maintaining high availability standards across enterprise web applications.<\/span><\/p>\n

                                      Question 279<\/b><\/h3>\n

                                      Which DORA metric measures the speed of restoring service after a production outage occurs?<\/b><\/p>\n

                                        \n
                                      1. Deployment Frequency<\/span><\/li>\n
                                      2. Change Lead Time<\/span><\/li>\n
                                      3. Change Failure Rate<\/span><\/li>\n
                                      4. Mean Time to Recovery (MTTR)<\/span><\/li>\n<\/ol>\n

                                        Correct Answer:<\/b> 4<\/b><\/p>\n

                                        Explanation:<\/b><\/p>\n

                                        Mean Time to Recovery measures how quickly an organization recovers from a production failure or service outage, serving as a core DORA metric for operational resilience and incident response efficiency. Shortening MTTR indicates mature observability tools, effective runbooks, and streamlined automated remediation workflows. High-performing engineering teams optimize MTTR alongside deployment frequency and failure rates to maintain high reliability standards. Tracking recovery times over time helps leadership identify operational bottlenecks and implement effective automation safeguards to minimize user-impact duration during critical incidents across enterprise cloud projects.<\/span><\/p>\n

                                        Question 280<\/b><\/h3>\n

                                        What is the primary objective of tracking action items generated from blameless postmortems?<\/b><\/p>\n

                                          \n
                                        1. To assign personal blame and terminate employee contracts after typing errors<\/span><\/li>\n
                                        2. To implement concrete preventive safeguards and architectural fixes ensuring the same failure never recurs<\/span><\/li>\n
                                        3. To hide failure metrics from executive stakeholders and customers permanently<\/span><\/li>\n
                                        4. To disable monitoring alerts so future outages go unnoticed<\/span><\/li>\n<\/ol>\n

                                          Correct Answer:<\/b> 2<\/b><\/p>\n

                                          Explanation:<\/b><\/p>\n

                                          The primary objective of tracking action items generated from blameless postmortems is to implement concrete preventive safeguards, code refactoring, or architectural fixes ensuring that identified system failures never recur. Documenting and resolving these action items transforms operational failures into valuable engineering investments, steadily improving system resilience. Fostering a blameless culture encourages transparent incident reporting, ensuring teams focus on fixing systemic weaknesses rather than individuals, leading to stronger long-term reliability and reduced mean time to recovery across enterprise deployments.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

                                          View Full Google Professional Cloud DevOps Engineer Exam Dumps and Practice Test Dumps.   Question 261 How can an organization route specific subset logs from Cloud Logging to external destinations like Pub\/Sub or BigQuery? By reading compute instance serial port logs manually By deleting log buckets every night By configuring Cloud Logging log router sinks […]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":[],"categories":[1648,1647],"tags":[],"_links":{"self":[{"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts\/13166"}],"collection":[{"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/comments?post=13166"}],"version-history":[{"count":2,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts\/13166\/revisions"}],"predecessor-version":[{"id":13267,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts\/13166\/revisions\/13267"}],"wp:attachment":[{"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/media?parent=13166"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/categories?post=13166"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/tags?post=13166"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}