Microsoft DevOps Engineer (Mid-Level) Interview Preparation Guide
Microsoft's DevOps Engineer interview process for mid-level candidates typically includes an initial recruiter screening, a technical phone screen, and 4-5 onsite interview rounds conducted by different interviewers. The process evaluates technical depth in cloud infrastructure (Azure), containerization, CI/CD pipeline design, system reliability engineering (SRE) concepts, and your ability to own medium-to-large infrastructure projects end-to-end. Behavioral and culture-fit assessments are integrated throughout. Expect a mix of system design questions, hands-on technical troubleshooting, deep-dive discussions on past projects, and infrastructure architecture challenges specific to multi-cloud and Azure environments.
Interview Rounds
Recruiter Screening
What to Expect
Initial phone call with a recruiter to assess basic fit, background, and motivation. The recruiter will verify your DevOps experience level, familiarity with relevant tools and cloud platforms, and interest in Microsoft's culture and mission. This round is conversational and relationship-building; it focuses on whether you meet baseline requirements and your communication skills. Typically 30-45 minutes. Rare to be rejected here if your resume matches the role; rejection usually only occurs if there is a significant gap in required experience or if communication is notably poor.
Tips & Advice
Research Microsoft's cloud strategy and the role's impact on product development. Be specific about why you are interested in Microsoft (not just 'it's a big company'). Briefly describe your most significant DevOps project and what you learned. Be honest about gaps; recruiters respect candidates who acknowledge areas for growth over those who overstate skills. Ask thoughtful questions about the team, the infrastructure challenges they face, and growth opportunities—this shows genuine interest and helps the recruiter advocate for you.
Focus Topics
Questions for the Recruiter
Prepare 2-3 thoughtful questions about the team's infrastructure challenges, the current tech stack, team structure, growth opportunities, and how success is measured in the role.
Practice Interview
Study Questions
Technical Stack Familiarity
Discuss your hands-on experience with containerization (Docker, Kubernetes), CI/CD tools (Jenkins, GitLab CI, GitHub Actions), Infrastructure as Code (Terraform, ARM templates, CloudFormation), and cloud platforms (AWS, Azure, GCP). Highlight which you use daily and where your strengths lie.
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Study Questions
Background and Experience Summary
Provide a concise 2-3 minute summary of your DevOps journey: your current role, key achievements (e.g., infrastructure migrations, pipeline improvements), primary tools and platforms you work with, and the scale of systems you manage.
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Study Questions
Key DevOps Project or Initiative
Prepare a 2-3 minute story about a significant infrastructure or CI/CD project you owned or heavily contributed to. Include the business context, your role, the tools and practices you implemented, and the outcome (e.g., reduced deployment time, improved reliability).
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Career Motivation and Role Fit
Articulate why you are interested in the DevOps engineer role at Microsoft, what aspects of infrastructure automation and deployment efficiency excite you, and how your past experience aligns with the role's responsibilities.
Practice Interview
Study Questions
Technical Phone Screen
What to Expect
A 45-60 minute phone interview with a senior engineer or tech lead from the Microsoft DevOps or infrastructure team. This round assesses your technical depth and problem-solving approach. You may be asked to design a CI/CD pipeline, troubleshoot a simulated infrastructure issue, discuss a past infrastructure project in detail, or solve a scenario-based infrastructure challenge. Some teams may include a hands-on component where you are given a coding or scripting challenge (e.g., write a bash script to automate a deployment task or configure a Kubernetes resource). The focus is on your reasoning, knowledge of DevOps practices, and ability to communicate technical decisions clearly.
Tips & Advice
For a mid-level candidate, expect questions that require both breadth (familiarity across multiple DevOps domains) and depth (detailed knowledge of your area of expertise). Practice explaining infrastructure design decisions out loud and defending trade-offs. If asked a scenario question, think out loud and ask clarifying questions before diving into a solution—this demonstrates maturity. Prepare 2-3 detailed infrastructure projects you can discuss for 10-15 minutes each, including specific technical decisions, what went wrong, and what you would do differently[1][2]. Be ready to live-code a simple script or explain Kubernetes/Terraform configurations. For Microsoft roles, be prepared for questions about Azure-specific services (Azure VMs, AKS, Azure DevOps), although general cloud knowledge is acceptable if you can learn quickly.
Focus Topics
System Reliability Engineering (SRE) Fundamentals
Understand and discuss SLOs (Service Level Objectives), SLIs (Service Level Indicators), error budgets, blameless postmortems, observability, toil reduction, and chaos engineering. Explain how you would measure system health, detect failures, and prioritize reliability work versus feature work[1].
Practice Interview
Study Questions
Observability and Monitoring System Design
Design a complete observability stack including metrics collection (Prometheus, Azure Monitor), log aggregation (ELK, Loki, Azure Log Analytics), distributed tracing (OpenTelemetry, Jaeger), alerting strategies, and dashboard design. Demonstrate understanding of the three pillars of observability: metrics, logs, and traces. Practice querying metrics with PromQL, building dashboards that answer 'Is the system healthy?' and 'Where is the bottleneck?'[1].
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Study Questions
Kubernetes Troubleshooting and Container Orchestration
Debug real or simulated Kubernetes issues under time pressure (e.g., pods crash-looping, service unreachable, deployment stuck, resource exhaustion). Walk through your diagnostic approach systematically: kubectl logs, describe, get events, check node status, inspect manifests. Understand common failure modes (image pull errors, resource requests/limits, health checks, config issues) and remediation strategies[1].
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Study Questions
Infrastructure as Code (Terraform, ARM Templates, or CloudFormation)
Design and implement Infrastructure as Code for a multi-environment infrastructure (dev, staging, production). Cover module design (inputs, outputs, reusability), state management strategy, drift detection, code organization, testing IaC changes, and promotion workflows. For Microsoft roles, Azure Resource Manager (ARM) templates or Terraform for Azure is expected; general IaC principles apply across platforms[2].
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Study Questions
CI/CD Pipeline Design and Implementation
Design, explain, and implement a complete CI/CD pipeline for a multi-service application. Cover pipeline architecture, build stages, testing integration, artifact management, deployment strategy (blue-green, canary, rolling), rollback mechanisms, and how you handle infrastructure provisioning within the pipeline. Discuss tools like Jenkins, GitHub Actions, or GitLab CI[1][2].
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Study Questions
Past Infrastructure Project Deep Dive
Prepare detailed discussion of 2-3 significant infrastructure projects you have built, migrated, or improved. For each: explain the business context, the challenge, your design decisions and trade-offs, tools and practices used, what went wrong (and why), how you fixed it, the outcome (measurable impact), and what you would do differently in hindsight[1][2].
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Study Questions
Onsite: Infrastructure System Design
What to Expect
A 45-60 minute in-person or virtual session where you are asked to design infrastructure for a real or hypothetical application or migration scenario. You will be evaluated on your ability to design scalable, resilient, and cost-effective infrastructure at the system level. You are expected to draw architecture diagrams, discuss specific services and their configuration, estimate scale and cost, justify trade-offs, and address failure scenarios and disaster recovery. Common scenarios include: design infrastructure for a SaaS product serving global traffic; migrate a monolithic application from VMs to containers and Kubernetes; build a platform for internal developer teams; or design multi-region infrastructure with failover. For Microsoft roles, scenarios may involve Azure-specific services (Azure App Service, AKS, Azure DevOps, Azure Storage, networking components). You should think about compute, networking, storage, CI/CD, monitoring, and DR strategy holistically.
Tips & Advice
Approach system design methodically: clarify requirements and constraints first (scale, regions, SLO targets, budget), outline a high-level architecture, dive into specific components (compute platform, networking, storage, databases), address fault tolerance and disaster recovery, estimate costs, and be prepared to defend trade-offs. Draw clear diagrams and explain your reasoning step-by-step. For mid-level, you are not expected to design perfect solutions, but you should demonstrate architectural thinking and ability to navigate trade-offs (e.g., managed services vs self-managed, cost vs resilience, complexity vs reliability). Ask clarifying questions about requirements. At Microsoft, emphasize understanding of Azure services: VMs, App Service, AKS, Azure Storage (blobs, tables, files), networking (VNet, ExpressRoute, Load Balancer, Application Gateway), Azure Database services, and integration with Azure DevOps for CI/CD[2]. Be prepared to discuss how you would monitor and operate the infrastructure post-deployment. Practice drawing architectures on a whiteboard or virtual whiteboard.
Focus Topics
Cost Estimation and Optimization
Estimate infrastructure costs realistically: compute hours, data transfer, managed services pricing, and cost optimization strategies (reserved instances, spot instances, autoscaling, non-prod shutdowns, egress minimization). Show ability to balance cost and reliability. Discuss cost governance and tagging strategies[2].
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Study Questions
Networking and Multi-Region Architecture
Design networking for resilience and global reach: VPC/VNet segmentation, load balancing strategies (global, regional, layer 7), DNS failover, content delivery networks (CDN), and multi-region architectures. Discuss service mesh (Istio, Linkerd) for advanced traffic management. Consider Azure-specific networking: VNets, Network Security Groups, Azure Load Balancer, Application Gateway, Azure Front Door for global routing. Address network isolation, security boundaries, and traffic routing patterns[2].
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Storage and Database Strategy
Select appropriate storage and database solutions: relational databases (SQL), NoSQL (DynamoDB, Cosmos DB), object storage (S3, Blob Storage), and caching layers (Redis). Discuss replication strategies, backup and disaster recovery, consistency trade-offs, and cost optimization. For Azure: Azure SQL Database, Cosmos DB, Azure Blob Storage, Azure Cache for Redis. Design for high availability and data durability.
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CI/CD Pipeline Integration with Infrastructure
Design how CI/CD pipelines integrate with your infrastructure: IaC provisioning stages, artifact management, deployment strategies (blue-green, canary, rolling), automated testing of infrastructure changes, and rollback mechanisms. Show how infrastructure changes are validated and promoted across environments.
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Study Questions
Disaster Recovery and Business Continuity Planning
Design DR strategy: RPO (Recovery Point Objective) and RTO (Recovery Time Objective) targets, data replication across regions, failover mechanisms, and runbook discipline. Discuss backup strategies, testing DR procedures (chaos engineering, game days), and post-incident improvements. Explain how you would validate failover and maintain DR readiness.
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Compute Platform Selection and Configuration
Choose appropriate compute platforms (VMs, containers/Kubernetes, managed services like App Service or Cloud Run) based on application requirements. For Kubernetes-based design: discuss cluster sizing, node pools, scaling strategies (HPA, VPA, cluster autoscaling), resource requests/limits, and cost optimization. For managed services: understand when managed solutions are better than self-managed alternatives. Consider Azure-specific options: Azure VMs, App Service, AKS, Container Instances.
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Onsite: Infrastructure Hands-On Technical Challenge
What to Expect
A 45-60 minute hands-on technical session where you are given access to a cloud environment (Azure sandbox, AWS sandbox, or local Kubernetes cluster) and tasked with solving a practical infrastructure problem or building a component from scratch. Scenarios may include: deploy a containerized application to Kubernetes with monitoring, configure a CI/CD pipeline for a given application, troubleshoot and fix a broken infrastructure, implement Infrastructure as Code for a specified architecture, or optimize an existing system. You are expected to use the command line, write or modify configuration files (YAML, HCL, JSON), and debug issues in real-time. The interviewer observes your problem-solving approach, familiarity with tools, ability to learn from errors, and communication during the process.
Tips & Advice
For a mid-level candidate, you are expected to move quickly and accomplish meaningful work within the time limit. If you get stuck, ask clarifying questions and try a different approach rather than spending 20 minutes on one problem. Use the command line confidently: practice kubectl, terraform, docker, bash, and cloud CLI tools (azure cli, aws cli, gcloud) before the interview. Structure your approach: read the requirements, outline a plan, implement step-by-step, validate, and explain your choices. If something breaks, troubleshoot methodically using logs and diagnostic tools. Practice on real cloud sandboxes or local Kubernetes (minikube, kind) beforehand. For Microsoft interviews, expect Azure-specific tasks: deploying to AKS, using Azure DevOps or GitHub Actions, configuring Azure resources. Be comfortable writing bash scripts and basic IaC. Time management is critical; focus on completing the core requirements and explaining your approach clearly.
Focus Topics
Script Automation (Bash, Python, or Go)
Write scripts to automate tasks such as deployment, configuration, health checks, or cleanup. Scripts should handle errors, be idempotent, and be understandable. Practice writing or modifying scripts in Bash or Python. For DevOps, Bash is essential.
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Study Questions
Monitoring, Logging, and Observability Setup
Configure monitoring and logging for the deployed infrastructure or application. Set up metrics collection (Prometheus, Azure Monitor), log aggregation, dashboards, and basic alerts. Validate that you can observe the system's health and diagnose issues using the observability stack.
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Study Questions
CI/CD Pipeline Configuration and Automation
Build or configure a CI/CD pipeline for a given application using tools like Jenkins, GitHub Actions, GitLab CI, or Azure Pipelines. Implement build stages, automated testing, artifact creation, and deployment stages. Integrate infrastructure provisioning if applicable. Ensure the pipeline handles errors and provides meaningful feedback.
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Problem-Solving and Debugging in Live Environment
When unexpected issues arise (which they will), systematically diagnose and resolve them. Use logs, CLI commands, and diagnostic tools to identify root causes. Communicate your approach to the interviewer. Learn from errors and adapt your strategy.
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Study Questions
Kubernetes Deployment and Troubleshooting Under Time Pressure
Deploy a containerized application to Kubernetes (or a Kubernetes-like environment) including: writing Deployment manifests, configuring resource requests/limits, setting up health checks (liveness/readiness probes), exposing services, and validating the deployment. Debug and fix issues that arise (e.g., image pull errors, CrashLoopBackOff, pods not receiving traffic). Use kubectl commands efficiently to inspect and diagnose problems[1].
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Infrastructure as Code Implementation and Testing
Write Infrastructure as Code (Terraform, ARM templates, or CloudFormation) to provision a multi-component infrastructure. Organize code into modules, use variables and outputs, validate syntax, plan changes, and apply configuration. Handle state management. Test that the provisioned infrastructure meets requirements. For Azure: use Terraform for Azure or ARM templates to create resources like VMs, storage, networking.
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Study Questions
Onsite: Technical Deep Dive on Past Experience
What to Expect
A 45-60 minute in-depth conversation with a senior engineer or team lead about your past infrastructure work and decision-making. You will be asked to describe in detail: what you built, why you made specific technical and architectural decisions, what went wrong and how you handled it, and what you would do differently in hindsight. This round is behavioral and technical combined; it assesses your ownership mentality, learning from failures, trade-off thinking, and ability to communicate complex technical decisions clearly. The interviewer will ask deep follow-up questions to understand your thought process and technical depth. Expect questions like: 'How did you structure your Terraform modules? How did you handle state management across teams? What was your testing strategy? What was the biggest challenge and how did you solve it?'[1][2] This round is where mid-level candidates demonstrate that they can own projects end-to-end and think critically about infrastructure decisions.
Tips & Advice
Prepare 3-4 significant infrastructure or DevOps projects you can discuss deeply for 15-20 minutes each. For each project, be ready to explain: business context and goals; your role and ownership level; technical architecture and specific tools used; key decisions you made and why; trade-offs you navigated (e.g., complexity vs reliability, cost vs performance); what went wrong (failures, incidents, or unexpected challenges); how you diagnosed and fixed issues; measurable outcomes (e.g., reduced deployment time from 30 min to 5 min, improved system reliability from 95% to 99.9%, reduced infrastructure costs by 40%); and lessons learned or what you would do differently. Use the STAR method (Situation, Task, Action, Result) to structure your stories. Be specific: include numbers, timelines, team sizes, and concrete metrics. Show vulnerability by discussing failures and what you learned. Mid-level candidates should focus on projects where they had significant ownership and influence, not just tasks they completed. Practice explaining technical decisions in simple language without jargon. Be prepared for deep technical follow-ups: 'Why did you choose Kubernetes over managed services? How did you handle state in your IaC? What was your testing strategy for infrastructure changes?'
Focus Topics
Collaboration and Cross-Functional Impact
Describe how you collaborated with developers, operations teams, security teams, or product teams to achieve infrastructure goals. Show examples of how your work enabled other teams to move faster or operate more reliably. Highlight communication and partnership.
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Measurable Impact and Business Value
Quantify the impact of your work: reduced deployment time, improved reliability (uptime percentage), reduced infrastructure costs, faster onboarding for developers, or reduced mean time to recovery (MTTR) for incidents. Connect infrastructure improvements to business outcomes.
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End-to-End Project Ownership and Delivery
Discuss a project from conception to production: defining requirements, designing the solution, implementing it, testing, deploying, and operating it. Emphasize your ownership level, decision-making authority, and impact. Show how you worked with other teams (developers, operations, security) to deliver the project.
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Technical Decision-Making and Trade-Off Thinking
Explain the key technical decisions you made in a project: tool selection, architecture choices, technology stack, and why you made those decisions given the constraints. Discuss trade-offs you navigated (e.g., simplicity vs capability, cost vs performance, time to market vs scalability). Show that you understand the implications of your choices.
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Handling Failures and Learning from Incidents
Share a story about something that went wrong (a production incident, a failed deployment, an architectural mistake, or a scaling challenge). Explain the root cause, how you diagnosed it, how you fixed it, and what you learned or changed afterward. Show a growth mindset and blameless postmortem thinking.
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Technical Depth in Tools and Practices
Demonstrate deep knowledge of the tools and practices you use: if you mention Terraform, be ready to discuss module design, state management, testing strategies, and team collaboration patterns. If you discuss Kubernetes, explain how you handle multi-tenancy, security, or scaling. Show nuanced understanding, not surface-level familiarity[1][2].
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Onsite: Behavioral and Culture Fit
What to Expect
A 30-45 minute conversation with a team member, manager, or HR representative focused on behavioral competencies, values alignment, and culture fit. This round assesses soft skills, communication, teamwork, reliability, growth mindset, and alignment with Microsoft's values (innovation, integrity, accountability, customer focus). Common questions include: Tell me about a time you had to work with a difficult team member; how do you handle ambiguity or uncertainty; describe a situation where you had to learn a new technology quickly; how do you prioritize when you have competing demands; tell me about your approach to mentoring or helping junior colleagues. For mid-level candidates, expect questions about leadership potential and initiative-taking. This round may also cover work-life balance, remote work preferences, and long-term career goals.
Tips & Advice
Prepare STAR-format answers (Situation, Task, Action, Result) for common behavioral questions. Focus on examples that showcase collaboration, problem-solving, learning, and impact. Be authentic and honest; culture fit is assessed through genuine interaction. Research Microsoft's mission, values, and culture; ideally, explain why you want to work there specifically. Practice discussing failures and lessons learned without defensiveness. Show growth mindset: talk about skills you've developed, challenges you've overcome, and areas you're still learning. For mid-level candidates, emphasize initiative-taking and mentoring: have you taken on additional responsibility, led any initiatives, or helped junior colleagues grow? Be prepared to discuss your approach to code/infrastructure review, knowledge sharing, and team collaboration. Ask genuine questions about the team culture, mentoring opportunities, and how success is measured. Be warm, conversational, and genuine in this round—interviewers are assessing if they would enjoy working with you.
Focus Topics
Initiative and Going Beyond the Job Description
Share an example of taking initiative beyond your assigned responsibilities: starting a knowledge-sharing session, mentoring a junior colleague, improving a process, or proposing a new tool or practice that benefited the team. Show proactive mindset.
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Handling Ambiguity and Uncertainty
Describe a situation where requirements were unclear, technical approach was uncertain, or the path forward was ambiguous. Explain how you gathered information, made a decision, and moved forward despite uncertainty. Show comfort with iterative learning.
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Communication and Clarity
Discuss how you communicate complex technical concepts to non-technical stakeholders, keep teams informed during incidents, or document your work for others. Show ability to adapt communication style to audience.
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Ownership and Accountability
Describe a situation where something went wrong on your watch. How did you respond? Did you take ownership, communicate transparently, and work to fix it? Show accountability without defensiveness.
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Growth Mindset and Continuous Learning
Discuss a skill or technology you learned on the job, why you needed to learn it, how you approached learning (courses, documentation, hands-on practice, mentorship), and how you apply it now. Show curiosity and commitment to growth.
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Teamwork and Collaboration
Share examples of effective collaboration with teammates: how you worked with developers to improve CI/CD, partnered with operations to respond to incidents, or helped resolve disagreements on technical decisions. Show empathy, willingness to listen, and ability to find win-win solutions.
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Frequently Asked DevOps Engineer Interview Questions
Sample Answer
Sample Answer
Sample Answer
apiVersion: v1
kind: ConfigMap
metadata:
name: otel-collector-config
data:
otel-collector-config.yaml: |
receivers:
otlp:
protocols:
grpc:
http:
processors:
batch:
timeout: 10s
send_batch_size: 512
exporters:
kafka:
brokers: ["kafka-broker-1:9092","kafka-broker-2:9092"]
topic: "otel-collector-buffer"
encoding: "otlp_proto"
protocol_version: "2.0.0"
# TLS/auth blocks omitted — add as needed
service:
pipelines:
traces:
receivers: [otlp]
processors: [batch]
exporters: [kafka]
metrics:
receivers: [otlp]
processors: [batch]
exporters: [kafka]
---
apiVersion: apps/v1
kind: Deployment
metadata:
name: otel-collector
labels:
app: otel-collector
spec:
replicas: 2
selector:
matchLabels:
app: otel-collector
template:
metadata:
labels:
app: otel-collector
annotations:
prometheus.io/scrape: "true"
prometheus.io/port: "8888"
# KEDA external scaler example (if using KEDA)
autoscaling.keda.sh/scalerVersion: "2"
spec:
containers:
- name: otel-collector
image: otel/opentelemetry-collector-contrib:latest
args: ["--config=/conf/otel-collector-config.yaml"]
ports:
- containerPort: 4317 # OTLP gRPC
- containerPort: 4318 # OTLP HTTP
- containerPort: 8888 # metrics
resources:
requests:
cpu: "250m"
memory: "256Mi"
limits:
cpu: "1000m"
memory: "1Gi"
volumeMounts:
- name: config
mountPath: /conf
volumes:
- name: config
configMap:
name: otel-collector-configapiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
name: otel-collector-hpa
spec:
scaleTargetRef:
apiVersion: apps/v1
kind: Deployment
name: otel-collector
minReplicas: 2
maxReplicas: 10
metrics:
- type: Resource
resource:
name: cpu
target:
type: Utilization
averageUtilization: 60Sample Answer
Sample Answer
Sample Answer
# check-and-create
if ! dpkg -s nginx >/dev/null 2>&1; then
apt-get update && apt-get install -y nginx
fi# use-state-marker + check
import pwd, os
if 'deploy_user_created' not in open('/var/run/mytool.state').read():
try:
pwd.getpwnam('deploy')
except KeyError:
run(['useradd','-m','deploy'])
with open('/var/run/mytool.state','a') as f:
f.write('deploy_user_created\n')Sample Answer
Sample Answer
Sample Answer
Sample Answer
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