Testing Infrastructure and Tool Development Questions
Knowledge of designing, building, and improving testing infrastructure and custom tooling that supports reliable software delivery. This includes test environment provisioning, test data generation, mock and staging systems, logging and observability for tests, test automation frameworks, reporting dashboards, and strategies to increase test reliability and execution speed. Candidates should be able to propose how to build or adapt tools to address the team's testing pain points and explain infrastructure considerations specific to testing at scale.
EasyTechnical
23 practiced
You maintain a fleet of containerized test runners used by CI to execute integration tests. Implement a Python (3.8+) script that: 1) accepts a list of shell commands from stdin (one per line), 2) runs up to N commands concurrently, 3) enforces a per-command timeout, 4) captures stdout/stderr to per-job log files, and 5) returns a non-zero exit code if any command fails. Describe how you'd integrate this into a Kubernetes Job runner later.
MediumTechnical
28 practiced
You have a large suite of end-to-end browser tests using Selenium that are flaky due to UI timing. Propose a combination of infra and test-level changes to reduce flakiness and improve execution speed, including strategies like headless rendering, network throttling, retry policies, and dedicated UI test runners.
MediumTechnical
23 practiced
Write a test harness in pseudocode that runs a suite of tests against multiple service versions to validate backward compatibility. The harness should iterate over combinations (old client + new server, new client + old server) and report incompatible pairings.
MediumTechnical
22 practiced
Write a short plan to implement test-data versioning and schema migration testing for a service that uses a relational DB. Include how to store dataset versions, run migrations safely in CI, and validate data migrations both forward and backward.
HardTechnical
21 practiced
Scenario: A test suite spike causes Kubernetes cluster autoscaler to spin up many nodes, increasing cost and slowing other workloads. Propose changes at the test infra layer to prevent autoscaler storms while preserving test throughput, including queueing, rate-limiting, and pre-warming strategies.
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