Amazon Senior DevOps Engineer Interview Preparation Guide
Amazon's Senior DevOps Engineer interview process typically consists of 6-7 rounds spanning 4-6 weeks from initial application to offer. The process emphasizes practical infrastructure experience, system design thinking, automation expertise, and alignment with Amazon's Leadership Principles. Rounds progress from recruiter screening through technical phone screens, system design interviews, hands-on technical deep dives, and behavioral assessment. Each round evaluates ownership, operational excellence, and ability to architect scalable infrastructure solutions.
Interview Rounds
Recruiter Screening
What to Expect
Initial screen with a technical recruiter to assess background, motivation, and fit for the Senior DevOps Engineer role. The recruiter will validate your experience level, verify key skills match the job description, and explore your interest in Amazon's infrastructure challenges. This round also covers logistics, salary expectations, and timeline. For Senior-level candidates, recruiters expect 5-7 years of relevant infrastructure and DevOps experience with demonstrated impact on system reliability, deployment automation, or cost optimization.
Tips & Advice
Be specific about your infrastructure projects and quantify results. Highlight any AWS experience. Research Amazon's infrastructure challenges (scale, global deployments, reliability requirements). Ask thoughtful questions about the team, infrastructure challenges, and growth opportunities. Have your resume tailored to the job description with keywords like 'Kubernetes,' 'CI/CD,' 'Terraform,' 'Infrastructure as Code,' and 'automation.' Clearly articulate why you're interested in Amazon specifically.
Focus Topics
Motivation for Amazon
Specific reasons why you're interested in Amazon: infrastructure scale, customer impact, technical challenges, team culture, or growth opportunities.
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AWS & Cloud Experience
Hands-on experience with AWS services relevant to infrastructure: EC2, VPC, RDS, S3, IAM, CloudFormation, or other services you've used in production.
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DevOps Experience & Background
Structured overview of your 5-7 years of infrastructure and operations experience, highlighting progression from hands-on engineering to architectural thinking and mentorship.
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Quantified Infrastructure Impact
Specific metrics from past projects: deployment frequency, mean time to recovery (MTTR), infrastructure cost savings, availability improvements, or automation ROI.
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Technical Phone Screen 1: Infrastructure Troubleshooting & Kubernetes
What to Expect
45-60 minute live technical interview focused on diagnosing and resolving infrastructure issues under time pressure. You may be given access to a simulated environment with infrastructure problems or asked to walk through your debugging methodology verbally. Common scenarios include: pods crash-looping in Kubernetes, services becoming unreachable, deployments failing to progress, networking issues, or latency spikes. Interviewers evaluate your systematic debugging approach, knowledge of diagnostic tools, ability to identify root causes vs. symptoms, and clear communication of your troubleshooting process. For Senior-level, expect complex multi-component scenarios requiring you to correlate logs, metrics, and events across the stack.
Tips & Advice
Take a systematic approach: gather symptoms, form hypotheses, test methodically, avoid random guessing. Narrate your thinking aloud so the interviewer follows your logic. Use standard diagnostic tools: kubectl (logs, describe, get events), curl/netstat, Linux commands (ps, top, netstat, ss), cloud provider CLIs, and monitoring systems. Start by defining the problem clearly—what's broken, what's the expected state, what's the actual state? For Kubernetes issues, check node status, pod status, events, resource limits, and network policies. For latency issues, correlate metrics (CPU, memory, network), logs, and traces. State assumptions and ask clarifying questions. Practice time management—don't get stuck on one theory. For Senior-level, explain architectural factors (how does this component relate to others?), failure modes, and prevention strategies. Be honest about what you don't know but show how you'd find the answer.
Focus Topics
Distributed Systems Debugging
Correlating signals across multiple systems: logs from different components, metrics from monitoring tools, traces from distributed tracing systems. Root cause analysis when symptoms appear in one component but the issue originates elsewhere.
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Cloud Provider Infrastructure (AWS)
Troubleshooting AWS-specific issues: security groups, network ACLs, IAM permissions, VPC configuration, ECS/EKS cluster issues, and common AWS service failures. Understanding AWS CloudTrail and monitoring tools.
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Container Networking & Service Mesh
Understanding container network models, service discovery, DNS resolution in containerized environments, network policies, and basics of service meshes (Istio/Linkerd). Debugging connectivity between containers and services.
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Linux System Administration & Diagnostics
Deep Linux system knowledge: process management, network diagnostics (netstat, ss, iptables), disk/memory analysis, user/permission management, and system logging. Ability to use tools like strace, lsof, and /proc filesystem.
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Kubernetes Troubleshooting & Debugging
Systematic debugging of Kubernetes cluster issues: pod crashes, resource exhaustion, network connectivity, persistent volume issues, and control plane problems. Proficiency with kubectl commands, event analysis, and log correlation.
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Technical Phone Screen 2: CI/CD Pipeline Design & Automation
What to Expect
45-60 minute technical interview focused on designing and optimizing CI/CD pipelines, deployment automation, and infrastructure automation practices. You'll be presented with scenarios like: design a CI/CD pipeline for a microservices application, optimize pipeline performance to reduce deployment time, implement GitOps workflows, or improve deployment safety with blue-green or canary strategies. Expect questions about Jenkins, GitLab CI, GitHub Actions, or similar tools; Infrastructure as Code with Terraform or CloudFormation; testing strategies in CI/CD; and deployment strategies (rolling, blue-green, canary). For Senior-level, demonstrate understanding of pipeline reliability, observability within pipelines, security gates, and scalability of CI/CD infrastructure itself.
Tips & Advice
Start by clarifying requirements: What's the deployment frequency target? What's the risk tolerance? Are we targeting high reliability, high speed, or both? What's the current state? Propose a baseline architecture first, then optimize based on constraints. For a solid CI/CD design, include: version control integration, automated build, unit/integration testing, artifact management, deployment stages (dev→staging→prod), approval gates, and rollback capability. Discuss testing strategy: what tests run in which stage, how you balance speed vs. comprehensiveness. Address safety: how do you prevent bad code reaching production? Consider canary deployments, blue-green deployments, or feature flags. For Infrastructure as Code, explain your choice of tool (Terraform vs. CloudFormation), state management, testing IaC changes, and drift detection. Discuss observability: how will you know if a deployment succeeded or failed? What metrics matter? How do you correlate deployment events with system behavior? For a Senior candidate, address pipeline scalability—how does this design scale to 100s of applications? How do you manage secrets, permissions, and audit trails? What's your disaster recovery strategy if CI/CD infrastructure fails?
Focus Topics
Pipeline Security & Compliance
Security practices in CI/CD: secrets management, IAM and RBAC in pipelines, audit trails, compliance scanning, container image scanning, and least-privilege access for deployment tools.
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Deployment Strategies & Risk Mitigation
Advanced deployment patterns: blue-green deployments, canary releases, rolling deployments, and feature flags. Rollback strategies, health checks during deployment, and automated deployment validation.
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Testing in CI/CD Pipelines
Test strategy and automation: unit tests, integration tests, contract tests, smoke tests, performance tests, and security scanning in pipelines. Understanding test scope, coverage, and pipeline speed optimization.
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Infrastructure as Code (IaC) & Configuration Management
Deep expertise in Terraform or CloudFormation: writing modular code, state management, environment management, testing IaC changes, and drift detection. Knowledge of configuration management tools (Ansible, Chef, Puppet).
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CI/CD Pipeline Architecture & Tools
Designing end-to-end CI/CD pipelines: pipeline stages (build, test, deploy), tool selection and integration, artifact management, version control workflows (GitFlow, trunk-based development), and scaling pipelines across multiple teams.
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System Design Interview 1: Infrastructure Architecture for Scalable Application
What to Expect
60-75 minute in-depth technical interview focusing on designing infrastructure architecture for a large-scale application. You'll receive a scenario like: design the infrastructure for a SaaS application serving 100M+ requests daily across multiple regions, migrate a monolithic application to microservices architecture on Kubernetes, or build infrastructure for a real-time data processing platform. You're expected to create architecture diagrams showing compute, networking, storage, databases, caching, CDN, monitoring, and disaster recovery. Discuss specific technology choices, tradeoffs (consistency vs. availability, latency vs. cost, reliability vs. complexity), capacity planning with concrete numbers, cost estimation, and how the architecture scales. Senior-level expectations include multi-region design, failover strategies, global load balancing, data replication strategies, and architectural resilience. Interviewers probe deeply: Why did you choose that database? How do you handle data consistency? What happens if a region fails? How do you monitor this system?
Tips & Advice
Structure your approach: 1) Clarify requirements (scale, latency targets, availability SLOs, geographic distribution, consistency requirements, budget). 2) Define core components (compute, storage, networking, caching, CDN). 3) Sketch high-level architecture with specific AWS services (EKS for compute, RDS/DynamoDB for data, ElastiCache for caching, CloudFront for CDN, Route53 for DNS). 4) Discuss capacity: estimate requests per second, data volume, storage needs, and bandwidth. 5) Address reliability: failover within a region (AZ resilience), failover across regions, health checks, auto-scaling. 6) Plan monitoring: what metrics matter? How do you detect failures? 7) Cost analysis: break down costs by component, identify optimization opportunities. 8) Security: data encryption, network isolation, IAM policies. For Senior-level, interviewers expect you to think about operational complexity, team structure, and runbook development. How would you operate this in production? What operational overhead does each decision create? What's your disaster recovery plan? Can you recover from regional failure? Be prepared to dive deep into specific areas: if they ask about the database, explain data model, indexing strategy, replication, backup/recovery. If they question your compute choice, explain why Kubernetes vs. ECS, how you handle node failures, how you scale. Draw diagrams, explain tradeoffs explicitly (e.g., 'We chose DynamoDB over RDS because we need horizontal scalability and eventual consistency is acceptable for this use case, but we trade strong consistency and complex queries'). Ask clarifying questions and verify assumptions with the interviewer.
Focus Topics
Observability & Monitoring Architecture
Designing monitoring and logging systems: metrics collection (Prometheus, CloudWatch), log aggregation, distributed tracing, dashboards, alerting rules, and runbooks. The three pillars of observability: metrics, logs, and traces.
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Capacity Planning & Performance Optimization
Estimating infrastructure needs based on traffic projections, latency requirements, and storage needs. Load testing, performance optimization, and cost optimization strategies.
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High Availability & Disaster Recovery
Designing for resilience: active-active vs. active-passive configurations, replication strategies, failover mechanisms, backup and recovery procedures, and RTO/RPO planning. Multi-region failover and data consistency across regions.
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Distributed Systems Design & Trade-offs
Architectural trade-offs: consistency vs. availability vs. partition tolerance (CAP theorem), synchronous vs. asynchronous processing, vertical vs. horizontal scaling, monolith vs. microservices, and database choices (SQL vs. NoSQL).
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Cloud Architecture Design (AWS)
Designing scalable, resilient infrastructure on AWS: compute options (EC2, ECS, EKS), storage decisions (RDS, DynamoDB, S3), networking (VPC, security groups, NACLs), CDN (CloudFront), and load balancing (ALB, NLB). Multi-AZ and multi-region architecture patterns.
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System Design Interview 2: Deployment Platform & Automation Infrastructure
What to Expect
60-75 minute technical interview focused on designing infrastructure for deployment automation and DevOps tooling. Scenarios might include: design an internal deployment platform that multiple teams use to deploy their services, build a GitOps platform for managing thousands of applications across multiple clusters, or design an automated infrastructure provisioning system for on-demand environment creation. You're expected to discuss: architecture of the platform itself, API design, multi-tenancy considerations, security and isolation between teams, integration with CI/CD, state management, and operational scaling. Senior-level candidates should address: how the platform evolves as the organization scales from 10 teams to 100 teams, how you ensure reliability of the platform itself, how you monitor and debug platform issues, and how you balance feature velocity with stability.
Tips & Advice
Start by understanding the problem deeply: Who are the users of this platform (developers, ops, teams)? What problem are they solving? What scale are we designing for (number of deployments, services, clusters)? Propose a platform architecture that includes: frontend (CLI, UI, API), authentication and authorization, workflow engine, integration points with CI/CD and cloud providers, state management, and observability. Discuss multi-tenancy and isolation: how do you prevent one team's deployments from affecting others? How do you ensure security? Address scalability of the platform infrastructure itself: if 1000 teams are using your platform simultaneously, what happens? How do you scale your control plane? Discuss reliability: what if your platform goes down? How do you handle upgrades without disrupting deployments? For GitOps specifically, discuss your approach to reconciliation (how often do you check desired state vs. actual state?), conflict resolution, rollback, and secret management. Be prepared for questions about operational complexity: what monitoring does the platform need? What are common failure modes? How do you debug when someone says 'my deployment is stuck'? How do teams troubleshoot without getting stuck in your platform's internals? Consider the human factors: platform adoption, developer experience, and self-service capabilities. Senior candidates should think about how the platform enables or constrains organizational practices (e.g., deployment frequency, blast radius reduction, compliance).
Focus Topics
State Management & Data Consistency
Managing deployment state, configuration state, and infrastructure state in distributed systems. Conflict resolution, eventual consistency, and handling state divergence.
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Operational Excellence & Platform Reliability
Ensuring the deployment platform itself is reliable and maintainable: monitoring platform health, capacity planning for platform infrastructure, handling platform upgrades without disruption, and designing for observability and debuggability.
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Multi-Tenancy & Security in Shared Platforms
Designing platforms for multiple teams: isolation strategies, RBAC (role-based access control), quota management, audit logging, and preventing cross-tenant interference. Security considerations in shared infrastructure.
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GitOps & Infrastructure-as-Code Automation
GitOps principles and implementation: using Git as source of truth, reconciliation loops, declarative configuration, automated synchronization, and secret management in GitOps workflows.
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Deployment Platform Architecture
Designing scalable, multi-tenant deployment platforms: API design, workflow orchestration, state management, and integration with Kubernetes, CI/CD systems, and cloud providers. Handling deployments at scale (hundreds of teams, thousands of services).
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Technical Deep Dive: Past Infrastructure Experience & Complex Problem-Solving
What to Expect
60-75 minute intensive technical interview where you discuss your past infrastructure and DevOps work in depth. Interviewers will select one or two significant projects from your background and ask detailed follow-up questions: What was the architecture? Why did you make specific technical decisions? What went wrong and how did you debug it? What would you do differently? How did you measure success? What trade-offs did you accept? For Senior-level candidates, expect questions about: How did you justify this architectural decision to leadership? How did you manage the complexity? How did you test changes to critical systems? What was your disaster recovery plan? How did you handle on-call responsibilities? How did you mentor junior team members through complex deployments? Interviewers will probe for evidence of: deep technical understanding (not just high-level knowledge), ownership mentality (not just executing someone else's plan), pragmatic decision-making under constraints, and ability to communicate complex technical decisions clearly.
Tips & Advice
Prepare 3-4 detailed infrastructure or DevOps projects you can discuss for 15-20 minutes each. For each project, have clear answers to: What problem were you solving? What was your role and the team structure? What was the architecture (be specific about tools, services, and components)? What metrics did you define for success (uptime, deployment frequency, MTTR, cost)? What challenges did you face and how did you overcome them? What would you do differently with hindsight? For complex projects, prepare a simple diagram you can sketch during the call. Use numbers liberally: 'We deployed 50 microservices to a Kubernetes cluster with 100 nodes, reducing deployment time from 2 hours to 10 minutes, and increasing deployment frequency from monthly to daily.' Have specific examples of: problems you diagnosed and fixed, decisions you made under constraints, failures you learned from, and impact you drove. Practice explaining technical decisions to non-technical audiences—why did you choose Kubernetes over Lambda? Why did you implement blue-green deployments instead of canary? Why that database? Be ready for deep follow-ups: 'You mentioned you use Terraform. How did you manage state across teams? Did you run into any state corruption issues? How did you test Terraform changes?' If the interviewer goes deep on a specific aspect, follow their lead. They're probing your real expertise, not testing your ability to recite facts. It's perfectly acceptable to say 'That's an edge case we didn't encounter, but here's how I would approach it...' Show your thinking, not memorized answers. For Senior candidates, emphasize: How did you scale this as the organization grew? How did you mentor team members? How did you balance technical excellence with shipping features? How did you handle production incidents? What operational burden did your solution create?
Focus Topics
Cross-Functional Collaboration & Stakeholder Management
How you worked with development teams, security teams, and leadership. Communication of complex technical decisions to non-technical stakeholders. Balancing infrastructure improvements with product feature timelines.
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Learning from Failures & Operational Excellence
Discussing technical failures you've experienced, root causes, and how you prevented recurrence. Culture of blameless postmortems and continuous improvement. Toil reduction and automation ROI.
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Metrics-Driven Decision Making
How you defined success metrics for infrastructure projects, measured outcomes, and used data to drive decisions. Examples: deployment frequency, MTTR, error rates, availability, cost per transaction.
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Production Incident Management & Resolution
Discussing real incidents you've handled: root cause analysis process, debugging methodology, communication during incidents, and post-incident learning. Demonstrating systematic problem-solving under pressure.
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Architecture Evolution & Technical Debt Management
How you evolved infrastructure systems over time: migrating from monolith to microservices, modernizing deployment processes, implementing GitOps, or scaling systems 10x. Balancing technical debt with feature velocity.
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Behavioral Interview: Amazon Leadership Principles & Culture Fit
What to Expect
45-60 minute behavioral interview where interviewers assess your alignment with Amazon's Leadership Principles and cultural values. Expect questions framed around: Customer Obsession ('Tell me about a time you improved something because of customer feedback'), Ownership ('Describe a situation where you took ownership of something beyond your job title'), Invent and Simplify ('Give an example of how you simplified a complex process'), Are Right, A Lot ('Tell me about a decision you made that turned out to be wrong; what did you learn?'), Learn and Be Curious, Hire and Develop the Best, Insist on the Highest Standards, Think Big, Bias for Action, Frugality, and Earn Trust. For Senior-level, interviewers probe deeper: How did you mentor team members? How did you drive organizational change? How do you balance technical idealism with pragmatism? How do you handle disagreement with leadership? For DevOps specifically, expect questions about: incident response culture, how you made trade-offs between reliability and speed, how you drove infrastructure modernization, and how you fostered collaboration between development and operations teams.
Tips & Advice
For each Amazon Leadership Principle, prepare specific STAR (Situation, Task, Action, Result) stories from your experience. Stories should be 2-3 minutes long and include concrete numbers/outcomes. Structure stories to highlight: What was the situation? What was your role? What was the problem or opportunity? What action did you take (focus on your individual contribution)? What was the result and what did you learn? For Senior-level candidates, stories should demonstrate: ownership (not just executing, but driving decisions), mentorship (helping others grow), and organizational impact (beyond your immediate team). For the 'Are Right, A Lot' principle, prepare a story about a decision that turned out to be wrong—this is an opportunity to show humility and learning, not failure. For 'Invent and Simplify' in infrastructure context, talk about how you simplified infrastructure processes, reduced operational toil, or introduced new tools/practices. For 'Think Big,' discuss long-term infrastructure strategy or modernization efforts. For 'Bias for Action,' describe times you moved quickly despite incomplete information. For 'Frugality,' discuss cost optimization efforts. Avoid generic answers—interviewers want specific stories that reveal how you think and behave. Practice your stories out loud so you can tell them naturally without sounding scripted. Be concise—use the time to tell great stories, not ramble. If asked about conflict or disagreement, show how you resolved it professionally and what you learned. Avoid criticizing past managers or companies; instead, focus on what you learned. Have questions ready about Amazon's culture, team dynamics, or how DevOps practices are evolving at the company.
Focus Topics
Amazon Leadership Principle: Insist on the Highest Standards & Learn and Be Curious
Maintaining high standards for infrastructure quality, reliability, and security. Continuous learning and curiosity about new technologies, industry trends, and improvement opportunities. Examples of keeping up with the industry.
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Amazon Leadership Principle: Invent and Simplify
Examples of simplifying complex infrastructure processes, introducing new tools or practices that improved efficiency, or solving problems in novel ways. Balancing innovation with pragmatism.
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Amazon Leadership Principle: Hire and Develop the Best
Mentoring junior engineers, building high-performing teams, and helping others grow. Specific examples of how you developed team members and raised team capabilities.
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Amazon Leadership Principle: Customer Obsession
Understanding and acting on behalf of customers: how infrastructure decisions impact customer experience, feedback loops with development teams (internal customers), and examples of prioritizing customer needs over internal preferences.
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Amazon Leadership Principle: Ownership
Demonstrating ownership beyond your job title: taking responsibility for outcomes, driving decisions without waiting for permission, and maintaining high standards even when no one is watching. Stories showing bias toward action and accountability.
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Frequently Asked DevOps Engineer Interview Questions
Sample Answer
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Sample Answer
#!/usr/bin/env python3
import subprocess, sys, json, requests
# Config
STAGING_REG = "staging.example.com"
PROD_REG = "prod.example.com"
IMAGE = "my-app" # repo/name
TAG = "sha-abcdef" # candidate tag (immutable digest tag recommended)
TEST_TAG = "test"
MAX_CRITICAL = 0 # fail if any CRITICAL vuln
def run(cmd):
print("+", " ".join(cmd)); subprocess.run(cmd, check=True)
def verify_signature(full):
# uses cosign; assumes cosign is configured with public key or keyless
try:
run(["cosign", "verify", full])
return True
except subprocess.CalledProcessError:
return False
def scan_vulns(full):
# uses trivy JSON output; assumes trivy installed
out = subprocess.check_output(["trivy", "image", "--quiet", "--format", "json", full])
data = json.loads(out)
counts = {"CRITICAL":0,"HIGH":0}
for r in data.get("Results",[]):
for v in r.get("Vulnerabilities",[]):
sev = v.get("Severity")
if sev in counts: counts[sev]+=1
return counts
def tag_exists_same_digest(reg, image, tag, digest):
# call Docker Registry HTTP API v2 to get manifest digest for tag and compare
url = f"https://{reg}/v2/{image}/manifests/{tag}"
headers = {"Accept":"application/vnd.docker.distribution.manifest.v2+json"}
r = requests.head(url, headers=headers, verify=True) # add auth if needed
if r.status_code!=200: return False
return r.headers.get("Docker-Content-Digest")==digest
def get_digest(reg,image,tag):
url = f"https://{reg}/v2/{image}/manifests/{tag}"
headers = {"Accept":"application/vnd.docker.distribution.manifest.v2+json"}
r = requests.head(url, headers=headers, verify=True)
r.raise_for_status()
return r.headers.get("Docker-Content-Digest")
def promote():
src = f"{STAGING_REG}/{IMAGE}:{TAG}"
if not verify_signature(src):
print("Signature verification failed"); sys.exit(1)
vulns = scan_vulns(src)
if vulns["CRITICAL"]>MAX_CRITICAL:
print("Vulnerability threshold exceeded:", vulns); sys.exit(1)
digest = get_digest(STAGING_REG, IMAGE, TAG)
if not tag_exists_same_digest(STAGING_REG, IMAGE, TEST_TAG, digest):
print("Test tag not present for same digest"); sys.exit(1)
# Promotion: pull, tag, push (or use registry API to copy)
run(["docker", "pull", src])
prod_ref = f"{PROD_REG}/{IMAGE}:{TAG}"
run(["docker", "tag", src, prod_ref])
run(["docker", "push", prod_ref])
print("Promotion successful:", prod_ref)
if __name__=="__main__":
promote()Sample Answer
Sample Answer
kubectl run -it --rm debug --image=busybox --namespace=team -- sh
# inside pod
wget -qO- http://remote-service.namespace.svc.cluster.local:8080 || curl -v ...kubectl exec -n kube-system -it coredns-pod -- cat /etc/resolv.conf
kubectl get endpoints remote-service -n namespace -o yamlsudo tcpdump -n -i any host <remote-pod-ip> and port 8080kubectl -n kube-system logs deployment/federation-controller-managerSample Answer
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