Essential Concepts in Serverless Computing Quiz

1. Event-Driven Model Complexity

   Which of the following best explains why debugging serverless applications can be more challenging compared to traditional server-based applications, considering that a developer is tracking a workflow triggered by an uploaded file?

   1. Serverless functions are stateless and may execute in unpredictable order, making tracing events difficult.
   2. Since serverless functions run in dedicated containers, debugging tools are always unavailable.
   3. Serverless platforms prevent access to all types of logging due to strict isolation.
   4. All serverless functions execute sequentially by default, making concurrent events impossible.
   5. Statelessness in serverless ensures all functions are perfectly traceable at any stage.

2. Cost Structure Comparison

   When comparing compute cost models, which statement most accurately describes how serverless computing charges differ from traditional virtual machine (VM) hosting in the case of a batch process that runs sporadically?

   1. Serverless charges based on the exact execution duration and resource usage for each invocation.
   2. Serverless charges are always higher than VM hosting, regardless of usage patterns.
   3. VM hosting costs fluctuate based on the number of serverless invocations per month.
   4. Serverless cost increases linearly with the age of the application, not its usage.
   5. VM hosting bills only for code executed, similar to serverless pricing.

3. Cold Start Phenomenon

   A developer notices that the first HTTP request to their serverless function takes significantly longer after a period of inactivity; what term best describes this occurrence, and why does it happen?

   1. Cold start, because the platform needs to initialize the function's runtime environment before execution.
   2. Warmed delay, as the function is updating its dependencies each time it runs.
   3. Code state lag, since the source code changes must be reapplied before each execution.
   4. Hot boot, since the function runs instantly after configuration updates.
   5. Stale start, as the function instance is kept alive indefinitely by design.

4. Resource Limitations in Serverless

   If a researcher tries to run a computation-heavy task that lasts over two hours on a serverless platform and receives an error, which limitation of serverless architecture are they encountering?

   1. Execution time limit, where functions are restricted to a maximum duration per invocation.
   2. Memory swapping threshold, which automatically expands memory for long-running tasks.
   3. Persistent storage requirement, as all local changes are preserved across invocations.
   4. Unlimited concurrency cap, which allows infinite parallel executions.
   5. Stateful execution lock, enabling extended one-off runs beyond standard limits.

5. Vendor Lock-in Risks

   Why might serverless computing potentially increase the risk of vendor lock-in for organizations developing portable applications?

   1. Serverless platforms often use proprietary event formats and APIs that make migrating to alternate platforms complex.
   2. Serverless functions universally require open-source tools for deployment.
   3. All serverless providers enforce the exact same runtime environments across platforms.
   4. Interoperability is always ensured due to standardized serverless protocols.
   5. Serverless APIs are completely independent of the underlying infrastructure.