Understanding the Company's Infrastructure Context Questions
Research the company's public infrastructure information (engineering blog, tech talks, published case studies, job description). Understand what systems they operate at scale, what problems they likely face, and what your role would contribute to.
MediumTechnical
0 practiced
Review the Terraform S3 snippet below and identify security misconfigurations and best-practice issues. Propose concrete Terraform and policy-level fixes (for example: Block Public Access, server-side encryption, bucket policies, logging).Snippet:resource 'aws_s3_bucket' 'public' { bucket = 'company-uploads' acl = 'public-read'}What are the risks and what concrete changes would you make?
EasyTechnical
0 practiced
A job description emphasizes 'designing highly available services', 'experience with Terraform', and 'multi-region deployments'. Explain in concrete terms what this likely implies about the company's infrastructure (for example: IaC practices, DR strategy, network topology, stateful vs stateless services). What probing questions would you ask the hiring manager to clarify production constraints and team responsibilities?
HardTechnical
0 practiced
Some of the company's stateful services experience 10x spikes during events and suffer cold-start delays. Design autoscaling policies for stateless frontends and stateful backends (like caches and DB replicas) that combine reactive and predictive strategies. Explain warm pools, pre-warming strategies, safety margins, growth-rate limits, and how you would evaluate the effectiveness of the policies.
HardTechnical
0 practiced
A public post shows an outage caused by misconfigured failover that led to split-brain across regions and inconsistent user state. As the on-call senior engineer, list the immediate incident response steps you would take to mitigate customer impact, how you would isolate and limit data divergence, and outline a safe reconciliation plan to restore consistent state. Finally, propose systemic long-term changes to prevent splits and to detect them earlier.
MediumTechnical
0 practiced
Given sample logs in this simple text format (timestamp service latency_ms db_errs), implement a Python function detect_incident_periods(log_lines: List[str]) -> List[dict] that finds contiguous periods where service latency and DB errors spike together. Use a threshold approach: consider latency > 2x median latency for that service and db_errs > 10 as a correlated spike. Merge adjacent high points into incident windows and return start/end timestamps and a short reason summary. Sample lines:2025-05-01T10:00:00Z api 120 02025-05-01T10:00:10Z api 130 02025-05-01T10:00:20Z api 900 502025-05-01T10:00:30Z api 800 452025-05-01T10:00:40Z api 140 0Provide robust parsing and explain how you compute the median baseline.
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