Unit 6: Understanding of Monitoring, Logging, Security & DevOps Best Practices - Practice Quiz

INT331 — Fundamentals Of Devops 60 Questions
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1 What is the primary purpose of monitoring in a DevOps environment?

Need for Monitoring in DevOps Easy
A. To detect and respond to issues in systems and applications
B. To design user interface layouts
C. To manage employee schedules
D. To write application source code

2 Which of the following is a key benefit of monitoring in DevOps?

Need for Monitoring in DevOps Easy
A. Faster detection of system failures
B. Reduced need for automation
C. Elimination of all bugs
D. Slower deployment cycles

3 What is Prometheus primarily used for?

Monitoring Tools: Prometheus & Grafana (overview) Easy
A. Compiling programs
B. Editing source code
C. Collecting and storing metrics
D. Designing databases

4 What is Grafana mainly known for?

Monitoring Tools: Prometheus & Grafana (overview) Easy
A. Managing containers
B. Visualizing metrics through dashboards
C. Running unit tests
D. Storing application logs

5 Prometheus and Grafana are commonly used together in which combination?

Monitoring Tools: Prometheus & Grafana (overview) Easy
A. Prometheus for data collection and Grafana for visualization
B. Both for user authentication
C. Both for writing code
D. Prometheus for visualization and Grafana for testing

6 What does the letter 'E' stand for in the ELK Stack?

Logging Fundamentals: ELK Stack (Elasticsearch, Logstash, Kibana) Easy
A. Environment
B. Encryption
C. Elasticsearch
D. Endpoint

7 Which component of the ELK Stack is responsible for collecting and processing log data?

Logging Fundamentals: ELK Stack (Elasticsearch, Logstash, Kibana) Easy
A. Grafana
B. Elasticsearch
C. Logstash
D. Kibana

8 Which ELK Stack component is used to visualize and explore log data?

Logging Fundamentals: ELK Stack (Elasticsearch, Logstash, Kibana) Easy
A. Elasticsearch
B. Prometheus
C. Logstash
D. Kibana

9 Which of the following are considered the three pillars of observability?

Observability: Metrics, Logs, Traces Easy
A. Metrics, Logs, and Traces
B. Users, Servers, and Networks
C. Code, Tests, and Builds
D. Files, Folders, and Drives

10 What do 'traces' primarily help track in a system?

Observability: Metrics, Logs, Traces Easy
A. The color of dashboards
B. The path of a request across services
C. The number of employees
D. The size of source files

11 Which observability pillar consists of numeric measurements collected over time?

Observability: Metrics, Logs, Traces Easy
A. Tickets
B. Logs
C. Traces
D. Metrics

12 What is the main goal of DevSecOps?

Introduction to DevSecOps Easy
A. Integrating security into the DevOps process
B. Removing testing from pipelines
C. Slowing down deployments
D. Replacing developers with tools

13 In DevSecOps, security is best described as being handled at which stage?

Introduction to DevSecOps Easy
A. Only during design
B. Never during development
C. Only after deployment
D. Throughout the entire development lifecycle

14 What does the acronym SRE stand for?

Introduction to Site Reliability Engineering (SRE) Easy
A. System Resource Estimation
B. Software Release Editor
C. Site Reliability Engineering
D. Secure Runtime Environment

15 Which company originally introduced the concept of Site Reliability Engineering?

Introduction to Site Reliability Engineering (SRE) Easy
A. Microsoft
B. Netflix
C. Google
D. Amazon

16 Which of the following is a widely recommended DevOps best practice?

DevOps Best Practices Easy
A. Automating repetitive tasks
B. Avoiding all version control
C. Deploying only once a year
D. Skipping monitoring

17 Which practice encourages frequent, small code changes in DevOps?

DevOps Best Practices Easy
A. Manual deployment
B. Continuous Integration
C. Annual releases
D. Isolated development

18 What is Netflix's Chaos Engineering primarily used for?

Real Industry Case Studies: Google SRE, Netflix Chaos Engineering Easy
A. Writing new movies
B. Managing subscriptions
C. Designing user profiles
D. Testing system resilience by injecting failures

19 Which famous tool did Netflix create for Chaos Engineering?

Real Industry Case Studies: Google SRE, Netflix Chaos Engineering Easy
A. Chaos Monkey
B. Kibana
C. Logstash
D. Prometheus

20 What is the core idea behind GitOps?

Future of DevOps: GitOps, AIOps, NoOps Easy
A. Using Git as the single source of truth for infrastructure and deployments
B. Using Git only for chatting
C. Storing only images in Git
D. Removing Git from all workflows

21 A team notices that their application meets all uptime targets but users still complain about slow checkout times during peak hours. Which monitoring gap does this scenario most directly highlight?

Need for Monitoring in DevOps Medium
A. Monitoring infrastructure but not the CI/CD pipeline duration
B. Using too many alerting rules for the checkout service
C. Relying only on availability metrics while ignoring performance and latency metrics
D. Collecting logs without retaining them long enough

22 In a Prometheus-based setup, an engineer wants to scrape metrics from a short-lived batch job that exits before Prometheus can poll it. Which component should be used?

Monitoring Tools: Prometheus & Grafana (overview) Medium
A. Grafana Loki
B. Node Exporter
C. Pushgateway
D. Alertmanager

23 A team uses Prometheus for data collection and Grafana for visualization. Which statement correctly describes the division of responsibility?

Monitoring Tools: Prometheus & Grafana (overview) Medium
A. Both tools store data independently and cannot share a data source
B. Prometheus stores and queries time-series data while Grafana renders dashboards from that data
C. Prometheus renders dashboards and Grafana handles alert routing exclusively
D. Grafana stores the time-series data while Prometheus only draws dashboards

24 Which PromQL expression correctly calculates the per-second rate of HTTP requests over the last 5 minutes for a counter named http_requests_total?

Monitoring Tools: Prometheus & Grafana (overview) Medium
A. avg_over_time(http_requests_total[5m])
B. rate(http_requests_total[5m])
C. sum(http_requests_total)
D. increase(http_requests_total)

25 In the ELK stack, an engineer needs to parse raw unstructured log lines, extract fields, and enrich them before storage. Which component is primarily responsible for this?

Logging Fundamentals: ELK Stack (Elasticsearch, Logstash, Kibana) Medium
A. Kibana
B. Logstash
C. Elasticsearch
D. Beats

26 A team wants a lightweight agent installed on hundreds of servers to forward logs to Logstash without heavy processing. Which tool best fits this requirement?

Logging Fundamentals: ELK Stack (Elasticsearch, Logstash, Kibana) Medium
A. Kibana
B. Elasticsearch
C. Grafana
D. Filebeat

27 Which role does Elasticsearch play within the ELK stack?

Logging Fundamentals: ELK Stack (Elasticsearch, Logstash, Kibana) Medium
A. Visualization layer for building interactive dashboards
B. Agent that collects logs from edge servers
C. Distributed search and analytics engine that indexes and stores log data
D. Pipeline that parses and transforms incoming data

28 A microservice request passes through five services and fails intermittently. Which observability pillar is most useful for pinpointing exactly which service in the request path introduced the latency?

Observability: Metrics, Logs, Traces Medium
A. Raw log counts
B. Aggregated metrics
C. Distributed traces
D. Static dashboards

29 Which statement best distinguishes metrics from logs in an observability strategy?

Observability: Metrics, Logs, Traces Medium
A. Metrics and logs are identical and interchangeable in practice
B. Metrics store full request payloads, while logs only store numeric counters
C. Logs are always cheaper to store than metrics at any scale
D. Metrics are numeric aggregates efficient for trends, while logs are discrete event records rich in detail

30 A team says their system is "monitored" but they cannot explain unexpected new failure modes without adding new code. What does this indicate about their setup?

Observability: Metrics, Logs, Traces Medium
A. They have too much observability and should reduce instrumentation
B. Their traces are consuming all metrics storage
C. They have monitoring but lack true observability into unknown-unknowns
D. They have replaced logging entirely with metrics

31 Which practice best embodies the "shift-left" principle of DevSecOps?

Introduction to DevSecOps Medium
A. Running automated security scans within the CI pipeline on every commit
B. Performing a manual security audit only after production release
C. Disabling security tests to speed up deployments
D. Delegating all security to a separate team at the end of the cycle

32 A pipeline scans source code for vulnerabilities without executing it, analyzing the code structure directly. Which type of testing is this?

Introduction to DevSecOps Medium
A. Penetration testing by a red team
B. Dynamic Application Security Testing (DAST)
C. Interactive Application Security Testing (IAST)
D. Static Application Security Testing (SAST)

33 A service has an SLO of 99.9% availability over 30 days. Roughly how much error budget (allowed downtime) does this permit in that period?

Introduction to Site Reliability Engineering (SRE) Medium
A. About 43 minutes
B. About 5 minutes
C. About 7 hours
D. About 24 hours

34 In SRE, what is the primary purpose of an error budget?

Introduction to Site Reliability Engineering (SRE) Medium
A. To measure the number of engineers on call
B. To track the cloud infrastructure cost per month
C. To eliminate all outages permanently
D. To balance reliability with the pace of feature releases

35 Which pairing correctly orders these SRE reliability terms from customer commitment to internal target to measured value?

Introduction to Site Reliability Engineering (SRE) Medium
A. SLI → SLO → SLA
B. SLA → SLO → SLI
C. SLA → SLI → SLO
D. SLO → SLA → SLI

36 A team commits small changes frequently to a shared branch and runs automated builds and tests on each commit. Which DevOps practice are they primarily following?

DevOps Best Practices Medium
A. Blue-green deployment
B. Infrastructure as Code
C. Chaos engineering
D. Continuous Integration

37 Why is treating infrastructure as version-controlled code (IaC) considered a DevOps best practice?

DevOps Best Practices Medium
A. It permanently prevents all production incidents
B. It makes environments reproducible, auditable, and consistent across stages
C. It eliminates the need for monitoring tools
D. It removes the need for any testing before deployment

38 Google SRE caps the amount of manual, repetitive operational work engineers do so they can focus on engineering. What is this repetitive work called?

Real Industry Case Studies: Google SRE Medium
A. Churn
B. Drift
C. Slack
D. Toil

39 Netflix's Chaos Monkey randomly terminates production instances. What is the main engineering goal of this practice?

Real Industry Case Studies: Netflix Chaos Engineering Medium
A. To verify that systems are resilient and can tolerate failures gracefully
B. To slow down deployments so bugs are caught manually
C. To reduce cloud infrastructure billing by shutting down servers
D. To replace automated monitoring with manual checks

40 In a GitOps workflow, how is the desired state of infrastructure and applications typically applied to a cluster?

Future of DevOps: GitOps, AIOps, NoOps Medium
A. A controller continuously reconciles the cluster to match declarations stored in a Git repository
B. Changes are emailed to operators who apply them by hand
C. Engineers manually run kubectl commands directly against production
D. A monitoring tool randomly adjusts the cluster state

41 In a Prometheus setup scraping 5000 targets every 15s, an SRE observes that rate(http_requests_total[1m]) produces erratic spikes while rate(http_requests_total[5m]) is smooth. What is the most accurate explanation?

Monitoring Tools: Prometheus & Grafana (overview) Hard
A. Grafana downsamples the 5m query on the client side, which removes all high-frequency variation
B. The 5m window silently discards counter resets, so it always appears smoother than reality
C. The 1m window contains too few scrape samples, making the rate sensitive to individual sample jitter and counter resets
D. Prometheus cannot compute rate() on windows shorter than the global scrape interval regardless of target count

42 A team has metrics, logs, and distributed traces but still cannot answer why a specific user's request was slow. Which gap in their observability practice is the most likely root cause?

Observability: Metrics, Logs, Traces Hard
A. Their metrics have insufficient cardinality to store one series per user
B. They collect logs in JSON rather than plain text, preventing correlation
C. They are using pull-based metrics instead of push-based metrics
D. Traces and logs are not correlated via a shared context such as a propagated trace/span ID

43 During a traffic surge, Logstash falls behind and Elasticsearch shows rejected bulk requests. Which architectural change best addresses back-pressure without dropping logs?

Logging Fundamentals: ELK Stack (Elasticsearch, Logstash, Kibana) Hard
A. Insert a durable buffer such as Kafka or Redis between shippers and Logstash to decouple ingestion from indexing
B. Increase the Logstash pipeline.workers beyond the number of CPU cores to force higher throughput
C. Move Kibana to a separate node so it stops competing with Logstash for memory
D. Disable Elasticsearch replicas permanently so indexing has less overhead

44 A service has an SLO of 99.9% availability over 30 days. After 12 days it has already consumed 80% of its error budget. According to SRE principles, what is the correct action?

Introduction to Site Reliability Engineering (SRE) Hard
A. Ignore the budget since it resets at the end of the 30-day window
B. Page the on-call engineer continuously until availability returns to 100%
C. Immediately raise the SLO to 99.99% to give the team more room
D. Freeze risky feature releases and prioritize reliability work until the budget recovers

45 A pipeline runs SAST, DAST, SCA, and secrets scanning. A subtle vulnerability arises from how two independently-safe microservices interact at runtime under load. Which control is most likely to catch it?

Introduction to DevSecOps Hard
A. DAST and runtime/IAST testing against a deployed, integrated environment
B. SCA, because interaction bugs originate in third-party dependencies
C. Secrets scanning, since inter-service auth relies on shared credentials
D. SAST, because it analyzes all source code paths statically

46 Which statement best captures the core scientific discipline that distinguishes chaos engineering from simply 'breaking things in production'?

Netflix Chaos Engineering Hard
A. You form a hypothesis about steady-state behavior, then inject failure to test whether that steady state holds
B. You randomly terminate as many instances as possible to maximize test coverage
C. You disable monitoring during experiments to observe raw system behavior
D. You only run experiments in staging to guarantee zero customer impact

47 In a GitOps model using a pull-based reconciliation agent, an operator manually runs kubectl scale to increase replicas during an incident. What happens and why?

Future of DevOps: GitOps, AIOps, NoOps Hard
A. Nothing happens because pull-based agents only apply changes at deploy time
B. The agent detects drift from the Git-declared state and reverts the replica count back
C. The manual change is permanently accepted because live cluster state overrides Git
D. The agent merges the manual change into Git automatically to preserve it

48 An engineer creates a label user_id on a Prometheus metric to track per-user latency across millions of users. Why is this considered a serious anti-pattern?

Monitoring Tools: Prometheus & Grafana (overview) Hard
A. It causes a cardinality explosion, creating a separate time series per label combination and overwhelming memory
B. Labels can only hold numeric values, so user_id strings are silently dropped
C. Prometheus rejects any metric with more than 100 distinct label values by default
D. Grafana cannot render dashboards for metrics that include user identifiers

49 Google's SRE model caps operational 'toil' at roughly 50% of an SRE's time. What is the primary strategic reason for this ceiling?

Google SRE Hard
A. It is a legal labor requirement limiting operational workload hours
B. It matches the maximum uptime achievable by any distributed system
C. It ensures every SRE spends exactly half their time on manual pager duty
D. It guarantees engineers have time for automation and engineering work that reduces future toil

50 A system emits 10 million spans/hour, and storing all of them is cost-prohibitive. The team wants to keep traces of slow or errored requests. Which sampling strategy fits best?

Observability: Metrics, Logs, Traces Hard
A. Uniform random sampling at a fixed 1% rate applied per span
B. No sampling, relying on Elasticsearch index compression to reduce cost
C. Head-based sampling, which decides at the first span before the outcome is known
D. Tail-based sampling, which decides after a trace completes based on latency or error attributes

51 Consider the relationship between availability nines and downtime. Which pairing of monthly (30-day) allowable downtime is correct?

Introduction to Site Reliability Engineering (SRE) Hard
A. 99.9% 4.32 min/month; 99.99% 0.43 min/month
B. 99.9% 8.64 min/month; 99.99% 43.2 min/month
C. 99.9% 43.2 min/month; 99.99% 4.32 min/month
D. 99.9% 72 min/month; 99.99% 7.2 min/month

52 A security team wants to enforce that no build proceeds if a critical CVE is found, but developers complain about excessive false-positive build failures. What is the most balanced DevSecOps approach?

Introduction to DevSecOps Hard
A. Block all builds on any finding regardless of severity to maximize safety
B. Tune policies to fail only on exploitable, high-confidence findings while reporting lower-severity issues without blocking
C. Remove the security gate entirely and rely on periodic manual audits
D. Move all scanning to production so it never blocks the build pipeline

53 An organization has excellent uptime dashboards but repeatedly suffers outages that dashboards did not predict. Which monitoring gap most directly explains this?

Need for Monitoring in DevOps Hard
A. They store metrics for too long, diluting recent data with historical noise
B. They monitor only known failure symptoms and lack leading indicators like saturation and error-rate trends
C. They use black-box monitoring instead of exclusively white-box monitoring
D. Their dashboards refresh too slowly, at 30-second intervals instead of real time

54 In Elasticsearch, a team indexes daily log indices but query latency degrades over months. Their oldest data is rarely queried. Which optimization directly addresses this?

Logging Fundamentals: ELK Stack (Elasticsearch, Logstash, Kibana) Hard
A. Disable the Elasticsearch query cache to prevent stale results
B. Use Index Lifecycle Management to roll over and move old indices to a warm/cold tier and force-merge segments
C. Reindex all historical data into a single massive index for simpler querying
D. Increase the number of primary shards on every daily index to speed up all queries

55 An 'AIOps' platform correlates thousands of alerts into a single incident and suppresses the rest. During a novel failure mode, it wrongly suppresses the one alert that mattered. What is the key limitation illustrated?

Future of DevOps: GitOps, AIOps, NoOps Hard
A. AIOps cannot ingest alerts from more than one monitoring source at a time
B. AIOps replaces all human on-call responders, so no one reviewed the alert
C. AIOps only works on metrics and is incapable of processing alert data
D. ML-based correlation depends on historical patterns and can misclassify or suppress genuinely novel signals

56 A team practices trunk-based development but suffers frequent broken builds on the main branch. Which combination of practices most directly restores main-branch stability?

DevOps Best Practices Hard
A. Committing directly to main and fixing breakages forward as they occur
B. Long-lived feature branches merged monthly after extensive manual QA
C. Short-lived branches with mandatory pre-merge CI checks and feature flags to decouple deploy from release
D. Disabling CI on pull requests to speed up the merge process

57 Google SRE distinguishes SLI, SLO, and SLA. A team promises customers 99.5% availability contractually but targets 99.9% internally and measures request success ratio. Which mapping is correct?

Google SRE Hard
A. SLI = 99.5% contract; SLO = 99.9% target; SLA = request success ratio
B. SLI = 99.5% contract; SLO = request success ratio; SLA = 99.9% target
C. SLI = request success ratio; SLO = 99.9% internal target; SLA = 99.5% customer contract
D. SLI = 99.9% target; SLO = 99.5% contract; SLA = request success ratio

58 Netflix's Chaos Monkey randomly terminates instances in production during business hours. What is the deliberate engineering rationale for this seemingly reckless timing?

Netflix Chaos Engineering Hard
A. Business hours have the least traffic, so failures are cheapest then
B. It maximizes customer-visible downtime to justify larger infrastructure budgets
C. Production is the only environment where instances can be terminated at all
D. Engineers are present to observe and respond, forcing systems to be resilient to routine instance loss

59 A team argues that metrics alone are sufficient because they can compute percentiles and rates cheaply. What fundamental limitation of pre-aggregated metrics does this overlook?

Observability: Metrics, Logs, Traces Hard
A. Metrics are always more expensive to store than raw logs at any scale
B. Metrics cannot be visualized in dashboards without traces present
C. Metrics cannot represent latency, only counts of successful requests
D. Metrics lose per-event context, so you cannot ask arbitrary new questions after the data is aggregated

60 A startup claims to have achieved true 'NoOps' by adopting serverless. Which critique most accurately reflects the practical reality of NoOps?

Future of DevOps: GitOps, AIOps, NoOps Hard
A. NoOps requires abandoning all monitoring since the provider guarantees uptime
B. Operational concerns like observability, cost governance, and failure handling still exist; they shift to developers and the provider rather than disappearing
C. NoOps is fully achievable and eliminates all operational responsibility once serverless is adopted
D. NoOps only applies to on-premises data centers and is impossible in the cloud