{"id":13164,"date":"2026-09-16T06:46:49","date_gmt":"2026-09-16T06:46:49","guid":{"rendered":"https:\/\/www.examlabs.com\/certification\/?p=13164"},"modified":"2026-09-16T07:23:49","modified_gmt":"2026-09-16T07:23:49","slug":"google-professional-cloud-devops-engineer-practice-test-questions-and-exam-dumps-part-12-q221-q240","status":"publish","type":"post","link":"https:\/\/www.examlabs.com\/certification\/google-professional-cloud-devops-engineer-practice-test-questions-and-exam-dumps-part-12-q221-q240\/","title":{"rendered":"Google Professional Cloud DevOps Engineer Practice Test Questions and Exam Dumps Part 12 Q221 – Q240"},"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 221<\/b><\/h3>\n

Which deployment strategy supported by Cloud Deploy allows routing a small percentage of user traffic to a new version before full rollout?<\/b><\/p>\n

    \n
  1. Blue-green deployment<\/span><\/li>\n
  2. Rolling update replacement<\/span><\/li>\n
  3. Canary rollout strategy<\/span><\/li>\n
  4. In-place patching<\/span><\/li>\n<\/ol>\n

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

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

    Cloud Deploy supports canary rollout strategies, enabling engineering teams to shift a small percentage of production traffic to a newly deployed version to observe system behavior and telemetry metrics before promoting the release to all users. This approach minimizes blast radius and prevents widespread customer disruption if unforeseen bugs or performance regressions exist. Automated verification phases can evaluate error rates and latency metrics during the canary stage, triggering automatic rollbacks if performance thresholds are breached. Progressive delivery mechanisms give SREs confidence in release stability while accelerating overall software delivery velocity across enterprise cloud-native environments.<\/span><\/p>\n

    Question 222<\/b><\/h3>\n

    How can operations teams extract numerical metrics from unstructured log data in Cloud Logging?<\/b><\/p>\n

      \n
    1. By creating log-based metrics using regular expressions or filter queries<\/span><\/li>\n
    2. By writing manual Python scripts to parse text files locally<\/span><\/li>\n
    3. By routing all logs directly to Compute Engine serial ports<\/span><\/li>\n
    4. By disabling logging and relying solely on database counters<\/span><\/li>\n<\/ol>\n

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

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

      Log-based metrics in Cloud Logging allow teams to extract valuable numerical data from incoming log streams by defining specific filter expressions or regular expressions. These metrics can track occurrences of particular error codes, API latency values, or custom application events over time. Once created, log-based metrics function similarly to standard Cloud Monitoring metrics, enabling engineers to build custom dashboards and configure alerting policies when thresholds are crossed. This powerful capability bridges unstructured logging text with proactive operational monitoring, empowering SRE teams to detect anomalous system behavior quickly and maintain high observability standards across complex distributed enterprise application architectures seamlessly.<\/span><\/p>\n

      Question 223<\/b><\/h3>\n

      What is the primary function of GKE node auto-provisioning?<\/b><\/p>\n

        \n
      1. Automatically deleting old container images from Artifact Registry storage buckets<\/span><\/li>\n
      2. Rotating cluster administrator SSH keys every single night<\/span><\/li>\n
      3. Converting Google Kubernetes Engine clusters into serverless functions<\/span><\/li>\n
      4. Automatically creating and deleting node pools based on pending pod resource demands<\/span><\/li>\n<\/ol>\n

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

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

        GKE node auto-provisioning automatically manages the creation and deletion of node pools based on the resource requirements of pending pods that cannot fit onto existing cluster nodes. When developers deploy resource-intensive workloads, auto-provisioning dynamically provisions optimal instance types, matching hardware architectures and accelerators without manual intervention. Once workloads terminate, idle nodes are automatically drained and removed to optimize cloud expenditure. This feature eliminates manual cluster capacity planning overhead, ensures elastic scalability, and guarantees that containerized applications receive sufficient compute resources instantly during sudden traffic surges across enterprise Kubernetes environments.<\/span><\/p>\n

        Question 224<\/b><\/h3>\n

        How can Cloud Monitoring forward critical incident alerts to external third-party incident management tools like PagerDuty?<\/b><\/p>\n

          \n
        1. By printing alert text directly to local terminal console screens<\/span><\/li>\n
        2. By configuring notification channels such as Webhooks, PagerDuty, Slack, or SMS<\/span><\/li>\n
        3. By storing alert summaries in unencrypted CSV spreadsheet files<\/span><\/li>\n
        4. By sending monthly PDF invoices via postal mail services<\/span><\/li>\n<\/ol>\n

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

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

          Cloud Monitoring notification channels allow operations teams to route critical alert notifications to various external platforms, including PagerDuty, Slack, Webhooks, Pub\/Sub, and SMS or email endpoints. Integrating alerting policies with external incident management tools ensures that on-call engineers are notified immediately when service indicators breach established thresholds. Multi-channel notifications reduce mean time to acknowledgement and resolution during production outages. Configuring robust notification workflows prevents alert fatigue and ensures accountability during incident response operations across distributed engineering teams managing complex mission-critical cloud applications and microservices.<\/span><\/p>\n

          Question 225<\/b><\/h3>\n

          Which Artifact Registry feature allows organizations to automatically delete old or untagged container images to reduce storage costs?<\/b><\/p>\n

            \n
          1. VPC Service Controls perimeters<\/span><\/li>\n
          2. Cloud Monitoring uptime checks<\/span><\/li>\n
          3. Cleanup policies for repositories<\/span><\/li>\n
          4. Cloud Deploy manual approval gates<\/span><\/li>\n<\/ol>\n

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

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

            Artifact Registry cleanup policies allow administrators to define automated rules that delete old, unused, or untagged container images and language packages based on age, tag patterns, or version counts. Automated cleanup optimizes storage expenditures and prevents repositories from accumulating obsolete build artifacts. Establishing retention policies ensures compliance with organizational data governance requirements while maintaining clean repository workspaces. Automated artifact lifecycle management reduces administrative overhead for development teams, ensuring that only valid, secure, and production-ready images remain stored within centralized registries across enterprise multi-project cloud environments.<\/span><\/p>\n

            Question 226<\/b><\/h3>\n

            Which Google Cloud service acts as a managed service registry for discovering microservices across hybrid and multi-cloud environments?<\/b><\/p>\n

              \n
            1. Service Directory<\/span><\/li>\n
            2. Cloud DNS local host files<\/span><\/li>\n
            3. Cloud Storage bucket lists<\/span><\/li>\n
            4. Compute Engine metadata servers<\/span><\/li>\n<\/ol>\n

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

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

              Service Directory is a managed service registry that provides a unified, highly available catalog for discovering and managing the endpoints of all backend services, regardless of where they are hosted across Google Cloud, hybrid on-premises, or 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 227<\/b><\/h3>\n

              What is the primary benefit of utilizing Cloud Build private worker pools?<\/b><\/p>\n

                \n
              1. They make all build artifacts publicly accessible on the internet<\/span><\/li>\n
              2. They compile Java source code using local virtual machine hard drives<\/span><\/li>\n
              3. They delete log files automatically to save storage quotas<\/span><\/li>\n
              4. They allow builds to run securely within private customer VPC networks with access to internal resources<\/span><\/li>\n<\/ol>\n

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

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

                Cloud Build private worker pools allow organizations to execute build pipelines within their own private VPC networks, enabling secure access to internal resources such as private database instances, artifact repositories, or internal APIs that are not exposed to the public internet. Private workers ensure strict network isolation and compliance with corporate security perimeters. Managed worker pools scale automatically to handle concurrent build demands without requiring manual infrastructure provisioning. Utilizing private workers safeguards sensitive source code and proprietary build environments from external exposure during continuous integration and deployment workflows.<\/span><\/p>\n

                Question 228<\/b><\/h3>\n

                How can an SRE team automate the rotation of database passwords stored in Secret Manager?<\/b><\/p>\n

                  \n
                1. By resetting passwords manually via console clicks every weekend<\/span><\/li>\n
                2. By configuring Secret Manager rotation with a Cloud Functions trigger and target database updates<\/span><\/li>\n
                3. By writing plaintext passwords inside container image Dockerfiles<\/span><\/li>\n
                4. By disabling authentication entirely to eliminate password maintenance<\/span><\/li>\n<\/ol>\n

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

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

                  Secret Manager supports automated secret rotation by integrating with Cloud Functions or Cloud Run services triggered via Pub\/Sub and Eventarc. When a rotation schedule is initiated, the automated function generates a new secure credential, updates the backend database instance, and creates a new version in Secret Manager. Automated credential rotation enhances security posture and satisfies rigorous compliance mandates without human intervention. Eliminating manual password updates reduces operational friction and minimizes the risk of credential leakage, ensuring robust security hygiene across sensitive enterprise data layers and microservice architectures.<\/span><\/p>\n

                  Question 229<\/b><\/h3>\n

                  What is a primary architectural difference between VPC Network Peering and Shared VPC for multi-project management?<\/b><\/p>\n

                    \n
                  1. VPC Network Peering allows administrative control from both sides, whereas Shared VPC centralizes network administration in a host project<\/span><\/li>\n
                  2. Shared VPC only connects virtual machines to external storage buckets<\/span><\/li>\n
                  3. VPC Network Peering requires physical cables between data centers<\/span><\/li>\n
                  4. Shared VPC encrypts all inter-instance traffic using physical hardware tokens<\/span><\/li>\n<\/ol>\n

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

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

                    VPC Network Peering connects two distinct VPC networks privately where each network is administered independently by its respective project owners. In contrast, Shared VPC allows an organization to connect resources from multiple service projects to a single common VPC network hosted in a central project, enabling centralized administrative control over subnets, firewall rules, and routing. Shared VPC facilitates strict network governance and security standardization across enterprise teams. Choosing between peering and shared VPC depends on organizational autonomy requirements and centralized network administration mandates for multi-project cloud environments.<\/span><\/p>\n

                    Question 230<\/b><\/h3>\n

                    Which pricing model offers deep discounts on Google Cloud compute resources in exchange for a commitment to a consistent usage level over a 1-year or 3-year term?<\/b><\/p>\n

                      \n
                    1. Committed Use Discounts (CUDs)<\/span><\/li>\n
                    2. Ephemeral preemptible spot instances<\/span><\/li>\n
                    3. Pay-as-you-go standard hourly billing<\/span><\/li>\n
                    4. Free tier trial allowances<\/span><\/li>\n<\/ol>\n

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

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

                      Committed Use Discounts provide significant cost reductions on Google Cloud services like Compute Engine, Cloud SQL, and BigQuery in exchange for a customer committing to pay for a specified minimum resource level over a 1-year or 3-year period. CUDs help organizations optimize predictable cloud expenditures for steady-state production workloads. Unlike spot instances, committed resources guarantee high availability and stability without risk of unexpected preemption. Strategic use of commitments combined with autoscaling allows finance and DevOps teams to balance cost efficiency with operational resilience across large enterprise multi-project cloud deployments effectively.<\/span><\/p>\n

                      Question 231<\/b><\/h3>\n

                      How does Managed Service for Prometheus evaluate alerting rules for container workloads?<\/b><\/p>\n

                        \n
                      1. By reading local text files stored on container boot disks<\/span><\/li>\n
                      2. By executing manual shell scripts during nightly batch windows<\/span><\/li>\n
                      3. By checking monthly cloud infrastructure billing invoices<\/span><\/li>\n
                      4. By using global rule evaluation engines that query collected Prometheus metrics continuously<\/span><\/li>\n<\/ol>\n

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

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

                        Managed Service for Prometheus enables global rule evaluation, allowing operators to run Prometheus alerting and recording rules centrally against metrics scraped from multiple GKE clusters. This capability ensures consistent alert evaluation without requiring standalone Prometheus server infrastructure inside every individual cluster. Centralized evaluation reduces operational overhead and simplifies multi-cluster observability. Seamless integration with Cloud Monitoring notification channels ensures that alert firings trigger immediate incident response workflows, maintaining high availability and rapid detection of performance anomalies across distributed containerized microservice architectures.<\/span><\/p>\n

                        Question 232<\/b><\/h3>\n

                        What is the purpose of configuring multi-window burn rate alerts for Service Level Objectives in Cloud Monitoring?<\/b><\/p>\n

                          \n
                        1. To calculate employee payroll bonuses based on uptime percentages<\/span><\/li>\n
                        2. To detect fast and slow error budget consumption accurately while minimizing false positives<\/span><\/li>\n
                        3. To delete historical log files when storage quotas reach capacity limits<\/span><\/li>\n
                        4. To automatically upgrade virtual machine instance CPU core counts<\/span><\/li>\n<\/ol>\n

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

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

                          Multi-window burn rate alerts evaluate the rate at which an application’s error budget is being consumed over different time windows. By analyzing both rapid error spikes and slow, persistent degradation, these alerts provide high fidelity for incident detection while minimizing false positive notifications. SRE teams rely on burn rate alerts to prioritize genuine user-impacting issues over minor transient fluctuations. Implementing advanced SLO alerting strategies ensures timely incident response, preserves developer trust in monitoring systems, and maintains high reliability standards across mission-critical enterprise applications.<\/span><\/p>\n

                          Question 233<\/b><\/h3>\n

                          How can developers extend the default behavior of Cloud Deploy delivery pipelines to execute custom validation or testing tasks?<\/b><\/p>\n

                            \n
                          1. By utilizing custom target actions and Skaffold hooks<\/span><\/li>\n
                          2. By editing Compute Engine serial port files manually<\/span><\/li>\n
                          3. By storing unencrypted credentials in public Git repositories<\/span><\/li>\n
                          4. By disabling automated pipeline verification checks entirely<\/span><\/li>\n<\/ol>\n

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

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

                            Cloud Deploy supports custom target actions and Skaffold hooks, enabling teams to inject custom tasks\u2014such as automated security scans, database schema migrations, or integration tests\u2014into deployment pipelines between rollout stages. Custom actions allow organizations to tailor delivery workflows to meet specific compliance and quality assurance requirements without abandoning managed release infrastructure. Integrating custom validation steps ensures that faulty or insecure releases are caught and blocked automatically before reaching production environments. Extensible pipelines enhance governance and accelerate software delivery velocity across complex enterprise software architectures.<\/span><\/p>\n

                            Question 234<\/b><\/h3>\n

                            What is the function of virtual services and destination rules in Anthos Service Mesh traffic management?<\/b><\/p>\n

                              \n
                            1. To define advanced traffic routing, splitting, fault injection, and load balancing policies for microservices<\/span><\/li>\n
                            2. To compile Java source code binaries into container images<\/span><\/li>\n
                            3. To automate the creation of database backups and transaction logs<\/span><\/li>\n
                            4. To scan container images for security vulnerabilities<\/span><\/li>\n<\/ol>\n

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

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

                              Anthos Service Mesh uses virtual services and destination rules to decouple service traffic routing from pod infrastructure. Virtual services define how requests are routed to specific services, supporting canary routing, header-based matching, and fault injection testing. Destination rules configure traffic policies applied after routing occurs, such as load balancing algorithms, TLS settings, and circuit breaking thresholds. This declarative traffic control allows platform engineers to manage service-to-service communication securely and reliably across multi-cluster environments without modifying application source code or deployment manifests.<\/span><\/p>\n

                              Question 235<\/b><\/h3>\n

                              Which Cloud Storage feature prevents objects from being deleted or modified until a specified retention period expires?<\/b><\/p>\n

                                \n
                              1. Ephemeral instance disk snapshots<\/span><\/li>\n
                              2. VPC flow log filters<\/span><\/li>\n
                              3. Compute Engine sole-tenant reservations<\/span><\/li>\n
                              4. Cloud Storage bucket retention policies and object holds<\/span><\/li>\n<\/ol>\n

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

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

                                Cloud Storage bucket retention policies and object holds enforce Write Once, Read Many (WORM) data states, preventing objects from being deleted, overwritten, or modified until a mandatory retention period elapses or holds are removed. Bucket retention policies help organizations comply with strict regulatory mandates requiring immutable data storage for financial, legal, or medical records. Setting up retention safeguards protects critical organizational data against ransomware attacks, accidental deletion, or unauthorized tampering by internal users. Robust data immutability guarantees long-term data integrity and audit readiness across enterprise cloud repositories.<\/span><\/p>\n

                                Question 236<\/b><\/h3>\n

                                What is the relationship between Compute Engine instance templates and managed instance groups?<\/b><\/p>\n

                                  \n
                                1. Managed instance groups generate billing invoices, while instance templates store database records<\/span><\/li>\n
                                2. Instance templates define the configuration blueprint, while managed instance groups use that blueprint to create and manage virtual machine fleets<\/span><\/li>\n
                                3. Instance templates execute cron jobs, while managed instance groups route HTTP traffic<\/span><\/li>\n
                                4. Instance templates are used exclusively for storage, while managed instance groups handle networking<\/span><\/li>\n<\/ol>\n

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

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

                                  Compute Engine instance templates serve as global configuration blueprints defining machine types, boot images, disk sizes, network tags, and startup scripts. Managed instance groups utilize these instance templates to deploy, scale, and heal fleets of identical virtual machine instances automatically. Decoupling configuration definition from fleet management simplifies infrastructure provisioning and ensures consistent deployments across staging and production environments. Utilizing templates and managed instance groups together enables elastic autoscaling and robust fault tolerance for scalable workloads running on Google Cloud virtual machines.<\/span><\/p>\n

                                  Question 237<\/b><\/h3>\n

                                  How does Identity-Aware Proxy (IAP) provide secure administrative access to Compute Engine instances without exposing management ports to the public internet?<\/b><\/p>\n

                                    \n
                                  1. By opening SSH port 22 directly on all public firewall rules<\/span><\/li>\n
                                  2. By requiring users to type plaintext passwords into terminal windows<\/span><\/li>\n
                                  3. By authenticating and authorizing users centrally via IAM before tunneling traffic over HTTPS<\/span><\/li>\n
                                  4. By routing all administrative traffic through unencrypted FTP servers<\/span><\/li>\n<\/ol>\n

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

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

                                    Identity-Aware Proxy secures administrative access to virtual machine instances by verifying user identity and authorization via Google Cloud IAM before permitting connection tunneling over HTTPS. IAP eliminates the need to expose management ports like SSH (port 22) or RDP (port 3389) to the public internet, significantly reducing the attack surface. Centralized access control ensures that only authorized personnel can connect to backend workloads. Implementing IAP strengthens remote access security, simplifies audit compliance, and protects internal virtual machine instances from unauthorized reconnaissance and brute-force attacks across enterprise cloud deployments.<\/span><\/p>\n

                                    Question 238<\/b><\/h3>\n

                                    How does Error Reporting integrate with Cloud Logging to help developers triage application bugs?<\/b><\/p>\n

                                      \n
                                    1. By automatically grouping and tracking application stack traces and exception errors from log entries<\/span><\/li>\n
                                    2. By deleting database records when memory utilization spikes<\/span><\/li>\n
                                    3. By calculating monthly billing discounts for engineering teams<\/span><\/li>\n
                                    4. By routing network packet captures through Virtual Private Cloud routers<\/span><\/li>\n<\/ol>\n

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

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

                                      Error Reporting analyzes incoming log streams in Cloud Logging, automatically detecting, grouping, and tracking application exceptions and stack traces in real time. It provides a centralized dashboard that highlights new error types, occurrence frequencies, and affected service versions. Developers receive instant notifications when critical errors occur, accelerating triage and remediation workflows. Integrating error tracking with logging infrastructure eliminates manual log searching, providing clear visibility into application health. Robust error monitoring improves software quality, reduces mean time to resolution, and enhances overall system reliability across production microservice architectures.<\/span><\/p>\n

                                      Question 239<\/b><\/h3>\n

                                      What is the primary function of synthetic monitors in Cloud Monitoring?<\/b><\/p>\n

                                        \n
                                      1. To execute local shell scripts for database backups<\/span><\/li>\n
                                      2. To scan container images for known vulnerabilities<\/span><\/li>\n
                                      3. To compile Java application source code files<\/span><\/li>\n
                                      4. To execute periodic script-based tests simulating user workflows and validating web application health<\/span><\/li>\n<\/ol>\n

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

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

                                        Synthetic monitors execute periodic, scripted test interactions\u2014such as logging into a web application, clicking buttons, and checking checkout workflows\u2014from various global locations. These tests validate end-to-end user journeys and detect application degradation before real users experience disruptions. Automated synthetic monitoring provides proactive black-box visibility into complex web services, going beyond simple server ping checks. Integrating synthetic tests with alerting policies ensures operations teams receive immediate notification of functional failures, safeguarding user experience and maintaining high availability standards across enterprise web applications.<\/span><\/p>\n

                                        Question 240<\/b><\/h3>\n

                                        Which DORA metric measures how often an organization successfully releases software to production environments?<\/b><\/p>\n

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

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

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

                                          Deployment Frequency measures how frequently an organization successfully releases code updates to production environments, serving as a primary DORA metric for software delivery velocity and organizational agility. High deployment frequency indicates a mature, highly automated CI\/CD pipeline capable of delivering rapid value to customers with minimal friction. High-performing engineering teams optimize this metric alongside lead time and failure rates to maintain a competitive market advantage. Streamlining release processes through automated testing and progressive delivery enables continuous integration and deployment without sacrificing stability or operational security standards across enterprise cloud projects.<\/span><\/p>\n","protected":false},"excerpt":{"rendered":"

                                          View Full Google Professional Cloud DevOps Engineer Exam Dumps and Practice Test Dumps.   Question 221 Which deployment strategy supported by Cloud Deploy allows routing a small percentage of user traffic to a new version before full rollout? Blue-green deployment Rolling update replacement Canary rollout strategy In-place patching Correct Answer: 3 Explanation: Cloud Deploy supports […]<\/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\/13164"}],"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=13164"}],"version-history":[{"count":2,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts\/13164\/revisions"}],"predecessor-version":[{"id":13270,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/posts\/13164\/revisions\/13270"}],"wp:attachment":[{"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/media?parent=13164"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/categories?post=13164"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.examlabs.com\/certification\/wp-json\/wp\/v2\/tags?post=13164"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}