Professional Cloud Developer
Professional Cloud Developer
Intermediate
Gauge your current knowledge
Intermediate
Gauge your current knowledge
Designing highly scalable, secure, and reliable cloud-native applications
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Professional Cloud Developer
Gauge your current knowledge
Gauge your current knowledge
High-performing applications handle many users and requests without slowing down. This requires designing the application to scale automatically when demand increases and shrink when demand decreases. In GCP, you use managed services like Cloud Run, App Engine, and Compute Engine autoscaling groups to achieve this. These services automatically add or remove instances based on metrics like CPU usage or request rate. You also need to design efficient APIs that respond quickly, which involves minimizing the amount of data transferred and caching frequently accessed information using services like Memorystore for Redis.
Designing secure applications means protecting them from unauthorized access and attacks. This involves managing who can do what within your GCP project using Identity and Access Management (IAM). IAM policies define which users or service accounts have permission to access specific resources. Applications should authenticate users securely, often using managed services like Identity-Aware Proxy (IAP) or Cloud Identity. To protect data, you must encrypt it both when it is stored (at rest) and when it is sent over the network (in transit). GCP services like Cloud KMS manage the encryption keys. Security also depends on the network; you use Virtual Private Cloud (VPC) networks to isolate resources and control traffic flow with firewall rules.
Choosing the right database or storage service depends on what your application needs to do with the data. For structured data that requires complex queries and transactions, you use a relational database like Cloud SQL or Cloud Spanner. For flexible, semi-structured data or high-speed reading and writing, you might choose a NoSQL option like Firestore or Cloud Bigtable. The data lifecycle is important: you store active data in these databases, archive older data to cheaper services like Cloud Storage, and analyze large datasets with BigQuery. Your application code accesses this data through secure connections, and the performance of your application often depends on how quickly it can read and write this data.