Technology – GK Questions

Terraform (HashiCorp) uses HCL declarative language to provision cloud resources across providers (AWS, Azure, GCP). Supports state management, modules, and plan/apply workflow. Ansible is configuration management; Jenkins is CI/CD; Docker is containerization. Critical for IaC questions.

Serverless query engines (AWS Athena, Google BigQuery) enable SQL queries directly on data in object storage (S3, GCS) using schema-on-read. Eliminates ETL for ad-hoc analysis. Pay-per-query pricing. Critical for modern data lake architecture questions.

Canary Release deploys new version to small user subset (canary group), monitors metrics, and gradually expands if stable. Reduces risk vs big-bang releases. Implemented via service mesh, load balancers, or feature flags. Critical for safe deployment strategies.

Authenticator apps (Google Authenticator, Authy) generate TOTP locally, immune to SIM swapping, SS7 attacks, and phishing that compromise SMS OTP. NIST recommends moving away from SMS for high-security applications. Critical for authentication best practices questions.

Data Protection Board of India is independent regulatory body established under DPDP Act 2023 to: adjudicate disputes, impose penalties, and enforce compliance. Distinct from CERT-In (cyber incidents) and MeitY (policy). Critical for data governance questions.

Chaos Engineering (Netflix Chaos Monkey) proactively tests system resilience by injecting failures (network latency, instance termination) in controlled experiments. Builds confidence in fault tolerance. Requires monitoring, blast radius limits, and automated rollback. Critical for SRE practices.

Star Schema (data warehousing) uses denormalized fact tables linked to dimension tables for fast analytical queries. Optimizes read performance at cost of storage redundancy. Contrasts with 3NF (normalized for OLTP). Critical for BI and analytics architecture questions.

Serverless (AWS Lambda, Azure Functions) scales automatically: from zero to thousands of instances based on demand. Pay-per-execution pricing eliminates idle costs. Trade-offs: cold starts, execution time limits, vendor lock-in. Critical for cost-optimized cloud architecture questions.

Meltdown/Spectre (2018) exploit CPU speculative execution and cache side-channels to read kernel memory or other processes' data. Mitigated via microcode updates, OS patches, and compiler fixes. Highlights hardware-level security challenges. Critical for system security questions.

RBI's Digital Lending Guidelines (2022) regulate: entity eligibility (banks/NBFCs only), direct fund flow, standardized disclosures, cooling-off period, and grievance redressal. Aims to protect consumers from predatory apps and data misuse. Critical for fintech compliance questions.

Automated Rollback uses monitoring alerts (error rate, latency) to trigger immediate reversion to previous stable version. Reduces MTTR and blast radius of bad releases. Implemented via CI/CD pipelines and SRE runbooks. Critical for production reliability practices.

CDC captures insert/update/delete operations from database logs (binlog, WAL) and streams to targets (Kafka, data lake). Enables real-time analytics, cache invalidation, and event-driven architectures. Tools: Debezium, AWS DMS. Critical for modern data integration patterns.

StatefulSet manages stateful applications: provides stable pod names (pod-0, pod-1), persistent storage, and ordered deployment/scaling. Used for databases, Kafka, etc. Deployment is for stateless apps; DaemonSet runs one pod per node; ReplicaSet manages pod replicas.

Zero Trust Security assumes breach and verifies every request regardless of source. Implements: identity verification, least privilege, micro-segmentation, and continuous monitoring. Contrasts with perimeter-based 'castle-and-moat' model. Critical for modern enterprise security architecture.

CERT-In Direction 20 (April 2022) requires service providers to synchronize ICT system clocks with NIC's National Time Server for accurate incident timeline correlation. Also mandates 6-hour incident reporting and 180-day log retention. Critical for cybersecurity compliance questions.

Blue-Green deployment: run current version (Blue) and new version (Green) in parallel; switch traffic to Green after validation. Enables instant rollback by reverting traffic. Reduces risk vs in-place updates. Critical for zero-downtime release strategies in DevOps.

Apache Spark provides in-memory distributed computing for big data: batch, streaming, ML, graph processing. Faster than Hadoop MapReduce due to in-memory processing. Supports Scala, Python, SQL. Critical for big data engineering and analytics questions.

Containerization (Docker, containerd) packages apps with runtime, libraries, and config into isolated, portable containers. Enables consistent deployment across environments. Contrasts with VMs (heavier, OS-level isolation). Foundation of cloud-native architecture. Critical for modern deployment questions.

Behavioral Analytics uses ML to establish baselines of normal behavior and flag deviations indicating threats (insider threats, zero-days). Complements signature-based detection. Implemented in UEBA, NDR solutions. Critical for next-gen SOC and threat hunting questions.

IT Rules 2021 mandate Significant Social Media Intermediaries (50L+ users) to appoint: Chief Compliance Officer, Nodal Contact Person, and Resident Grievance Officer. Also require traceability of first originator for certain messages. Critical for platform governance and compliance questions.