1. What is Google Cloud Platform (GCP)?
GCP is a suite of cloud computing services provided by Google. It offers various services, including computing power, storage, and databases, as well as machine learning, data analytics, and networking services. GCP enables organizations to build, deploy, and scale applications efficiently in the cloud.
2. Explain the key components of GCP.
Compute Engine: Provides virtual machines (VMs) for running applications.
App Engine: A platform-as-a-service (PaaS) offering for building and deploying applications without managing the underlying infrastructure.
Kubernetes Engine: A managed Kubernetes service for container orchestration.
Cloud Storage: Object storage service for storing and retrieving data.
BigQuery: Serverless data warehouse for analytics.
Cloud SQL: Managed relational database service.
Cloud Pub/Sub: Messaging service for building event-driven systems.
Cloud Spanner: Globally distributed, horizontally scalable database.
3. Explain the difference between Compute Engine and App Engine.
Compute Engine: Infrastructure as a Service (IaaS) offering that provides virtual machines. Users have full control over the VMs, including the operating system and software configurations.
App Engine: Platform as a Service (PaaS) offering that abstracts away the infrastructure details. Developers focus on writing code, and Google manages the underlying infrastructure, automatically scaling as needed.
4. What is Kubernetes, and how does GCP support it?
Kubernetes: An open-source container orchestration platform for automating the deployment, scaling, and management of containerized applications.
GCP Kubernetes Engine: A managed Kubernetes service that simplifies the deployment and operation of Kubernetes clusters. It automates tasks like cluster provisioning, scaling, and upgrades.
5. Explain Cloud Storage Classes in GCP.
Standard: General-purpose storage with high performance and low latency.
Nearline: Designed for data accessed less frequently but requires low latency when accessed.
Coldline: Suited for archival data with infrequent access.
Archive: Lowest-cost option for long-term storage with rare access.
6. How does Cloud Identity and Access Management (IAM) work in GCP?
IAM: Manages access control by defining roles and assigning them to users or groups.
Roles: Define permissions, and users are granted those roles.
Principals: Entities that can request access, such as users, groups, or service accounts.
7. Explain Google Cloud Pub/Sub.
Pub/Sub: A messaging service for building event-driven systems. Publishers send messages to topics, and subscribers receive messages from subscriptions to those topics.
Topics: Channels for publishing messages.
Subscriptions: Named resources representing the stream of messages from a single, specific topic.
8. What is Google Cloud BigQuery, and how is it different from traditional databases?
BigQuery: A fully managed, serverless data warehouse for analytics. It enables super-fast SQL queries using the processing power of Google's infrastructure.
Differences: BigQuery is designed for analytical workloads and can handle massive datasets with high concurrency, while traditional databases are often optimized for transactional workloads.
9. Explain the concept of Virtual Private Cloud (VPC) in GCP.
VPC: A private network for GCP resources. It provides isolation, segmentation, and control over the network environment.
Subnets: Segments of the IP space within a VPC, allowing for further network isolation.
Firewall Rules: Control traffic to and from instances.
10. What are Cloud Functions in GCP?
Cloud Functions: Serverless compute service that allows you to run event-triggered functions without provisioning or managing servers.
Event Sources: Triggers for Cloud Functions, such as changes in Cloud Storage, Pub/Sub messages, or HTTP requests.
11. What is Stackdriver in GCP?
Stackdriver: Stackdriver is a comprehensive observability suite in GCP that includes logging, monitoring, trace analysis, and error reporting. It provides tools for developers and operators to gain insights into the performance, availability, and overall health of their applications.
12. Explain Stackdriver Logging.
Stackdriver Logging: A fully-managed logging service that allows you to store, search, analyze, and alert on log data. It collects log entries from applications and infrastructure and provides a centralized location for log management.
13. What are log entries in Stackdriver Logging?
Log Entries: Records of events generated by GCP resources. Each log entry has a timestamp, severity level, log name, and payload containing specific information about the event.
14. How can you view logs in Stackdriver Logging?
Stackdriver Console: You can view logs interactively in the Stackdriver Logging console. It provides a user-friendly interface to search, filter, and analyze logs.
15. Explain the concept of Log Severity Levels in Stackdriver Logging.
Severity Levels: Indicate the importance of a log entry. Levels include DEBUG, INFO, NOTICE, WARNING, ERROR, and CRITICAL. Setting and using severity levels helps in identifying and addressing issues effectively.
16. What is Stackdriver Monitoring?
Stackdriver Monitoring: A service that provides visibility into the performance, uptime, and overall health of applications and services. It includes dashboards, alerting policies, and metrics collection.
17. Explain Stackdriver Dashboards.
Dashboards: Customizable visual displays that allow users to aggregate and display metrics and charts for monitoring purposes. Dashboards can include charts, text widgets, and predefined components.
18. How does Stackdriver Monitoring use Metrics?
Metrics: Quantitative measurements representing the behavior of a system over time. Stackdriver Monitoring collects and stores metrics that help in understanding the performance and health of resources.
19. What is an Alert Policy in Stackdriver Monitoring?
Alert Policy: Defines conditions for triggering alerts based on specified metrics and thresholds. When conditions are met, notifications can be sent via various channels like email, SMS, or third-party integrations.
20. Explain the integration of Stackdriver Trace with Logging and Monitoring.
Stackdriver Trace: A distributed tracing service that allows you to trace the performance of requests as they travel through your application.
Integration: Trace data can be correlated with logs and monitoring metrics in Stackdriver, providing a comprehensive view of the application's behavior.
21. How can you export logs from Stackdriver Logging?
Export Sinks: You can export logs to other Google Cloud services, Cloud Storage, or external systems using export sinks. This allows for archiving, analysis, and integration with third-party tools.
22. Explain the concept of Metrics Explorer in Stackdriver Monitoring.
Metrics Explorer: A tool in the Stackdriver Monitoring console that allows users to explore and visualize metrics data. It provides a flexible interface for creating custom charts and analyzing metric data.
23. How does Stackdriver handle autoscaling in GCP?
Autoscaler: Stackdriver provides autoscaling policies that use metrics to dynamically adjust the number of instances in a managed instance group. This ensures optimal utilization of resources based on demand.
24. What is the purpose of Stackdriver Error Reporting?
Error Reporting: Automatically detects and aggregates errors produced by applications. It provides insights into the frequency and impact of errors, helping identify and resolve issues.
25. How can you set up alerting in Stackdriver Monitoring?
Alerting Policies: You can create alerting policies in Stackdriver to define conditions for triggering alerts. These policies can be associated with specific resources, and notifications can be configured for various channels.
