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bulktrends > Blog > Online Learning > Cloud Certifications That Pay: 9 Practical Paths (AWS vs Azure vs Google Cloud)
Online Learning

Cloud Certifications That Pay: 9 Practical Paths (AWS vs Azure vs Google Cloud)

Ishimwe Gael
Last updated: August 17, 2025 7:12 pm
Ishimwe Gael
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13 Min Read
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Which provider fits your background, timeline, and goals? This field-tested guide compares roles, pathways, and study plans—so you can prep with focus and ship results without burning out.

Contents
Who should pick which provider?Role-based pathways (entry → associate → pro)Realistic costs & booking tips30/60-day study plans you can copyBuild visible proof (so interviews feel easy)Mistakes that waste time (and quick fixes)More resources on Bulktrends can be found below:Provider trade-offs (what trips teams up)12 hands-on labs that double as interview storiesRésumé & LinkedIn: translate labs into proofInterview prep (scenario prompts you can practice)Study rhythm for busy professionals to achieve your cloud certifications goals (8-week template)Lab cost control (so practice doesn’t surprise you)Readiness checklist (use before you book)Authoritative external resources (dofollow)Bottom line
cloud certifications study setup with laptop and server gear
Pick a provider, a role path, and a finish date—then make weekly deliverables non-negotiable. Photo via Unsplash.

TL;DR

  • Choose your role first (admin, architect, data/ML, security), then the provider.
  • Use a 30/60-day plan and publish lab notes weekly.
  • Book the exam only after two full practice tests at passing scores.

If you’re comparing cloud certifications, start with the role you want to interview for, not the shiniest badge. Map skills to real job posts, then pick the provider and path that delivers those skills with hands-on labs.

Employers value projects and proof. That’s why the best use of cloud certifications is to structure your learning and demonstrate fundamentals through repeatable lab work you can talk about in detail.

Provider choice follows your market and stack. If your target companies run mostly on Microsoft, Azure is pragmatic; if your startup scene is AWS-heavy, start there; if your team builds data products on BigQuery, GCP is sensible. The point is using cloud certifications to validate skills that match hiring demand in your region.

Be honest about time and budget. Entry exams are approachable with consistent study, while associate and professional tracks demand deeper practice. The fastest wins with cloud certifications come from a fixed end date and weekly artifacts (diagrams, scripts, costs, and trade-off notes).

Pathways matter more than badges alone. Align cloud certifications to a role path—admin→architect, developer→DevOps, analyst→data engineer—so every hour of work compounds toward interviews instead of scattered trivia.

Which provider fits which role? For platform-agnostic fundamentals, any associate-level path works; for Microsoft-centric IT, Azure shines; for startups and global scale, AWS breadth helps; for analytics-heavy teams, GCP’s data suite is compelling. Your shortlist of cloud certifications should reflect the tools you’ll actually use on day one.

Study cadence beats intensity. Break topics into small, testable labs and annotate decisions (why this service, limits, cost). In practice, cloud certifications reward calm consistency over binge learning.

Build public proof as you go. Write short readmes for each mini-project—inputs, architecture diagram, deployment steps, cost notes. Hiring managers trust cloud certifications more when your portfolio shows how you apply them.

Avoid common traps. Memorizing product names without deploying anything, skipping IAM fundamentals, or ignoring costs will undercut the value of your cloud certifications in interviews.

Keep scope tight. Choose one provider, one role path, and one exam window; otherwise your cloud certifications effort stretches indefinitely with no portfolio to show for it.

Bottom line: pick a role, follow a provider path, and publish labs weekly. Treated this way, your cloud certifications translate directly into interviews and confidence.

Who should pick which provider?

  • AWS: broad service coverage; great for startups, global scale, and multi-role exposure.
  • Azure: the default in Microsoft-centric enterprises; tight AD/M365 integration.
  • Google Cloud: excellent data/ML tooling (BigQuery, Vertex AI); favored by analytics teams.

Role-based pathways (entry → associate → pro)

Target RoleAWS PathAzure PathGCP Path
Cloud AdministratorCloud Practitioner → SysOps Admin (SOA-C02)AZ-900 → AZ-104Cloud Digital Leader → Associate Cloud Engineer
Solutions ArchitectCloud Practitioner → Solutions Architect Associate → Solutions Architect ProfessionalAZ-900 → AZ-305Cloud Digital Leader → Professional Cloud Architect
Developer / DevOpsDeveloper Associate → DevOps Engineer ProfessionalAZ-204 → AZ-400Associate Cloud Engineer → Professional DevOps Engineer
Data / MLData Engineer Associate / ML SpecialtyDP-900 → DP-203 (Data Engineer) → AI-102 (AI Engineer)Professional Data Engineer / Professional ML Engineer
SecuritySecurity Specialty (after associate)SC-900 → AZ-500Professional Cloud Security Engineer

Realistic costs & booking tips

  • Entry exams are relatively affordable; associate/pro tracks cost more—verify prices on official pages.
  • Plan for retakes: block a second attempt on your calendar two weeks after the first, just in case.
  • Use free tiers and sandboxes to keep lab costs predictable; track spend and tear down nightly.
  • Join user groups—practice questions and lab ideas surface quickly when you learn in public.

30/60-day study plans you can copy

PlanWeekly FocusDeliverable
30-Day Booster (entry/associate)IAM basics; compute; storage; networking; monitoring5 mini-labs + 1 full practice test ≥ passing
60-Day Builder (associate/pro)Resiliency & cost; automation; security; data services; architecture trade-offs10 mini-labs + 2 practice tests ≥ passing

Build visible proof (so interviews feel easy)

  1. Architecture notes: diagram + why you picked each service.
  2. Steps & scripts: exact commands or console clicks to reproduce.
  3. Cost & limits: what it cost to run, quotas, and pitfalls.
  4. Variations: how you’d do it for higher traffic, stricter security, or lower spend.

Mistakes that waste time (and quick fixes)

  • Only watching videos: replace 30% of watch time with hands-on labs.
  • Ignoring IAM: learn roles/policies early; permissions issues derail real projects.
  • Skipping costs: tag resources, set budgets/alerts, and practice teardown.
  • Over-scoping: one provider, one path, one exam window—finish and move on.

More resources on Bulktrends can be found below:

  • AI Tools for Online Jobs: 12 Proven Workflows
  • Remote Work Burnout: 15 Proven Ways
  • Passive Income Online: 7 Proven Models

Provider trade-offs (what trips teams up)

All three major providers can carry you to a solid role—what matters is how their defaults shape day-to-day work. Understanding these trade-offs makes your study time much more targeted.

  • AWS: unmatched breadth and pace of new services. The flip side is choice overload and subtle service overlaps. Build a habit of comparing “good enough + simple” against “perfect + complex.”
  • Azure: superb fit in Microsoft-centric environments—identity, governance, and desktop tooling feel native. Watch for evolving service names and licensing nuances that impact cost modeling.
  • Google Cloud: first-class analytics/ML stack with BigQuery and Vertex AI. Networking and IAM models feel opinionated; do an extra pass on shared VPC patterns and least-privilege design.
developer laptop with code editor open and architecture notes beside it
Learn by shipping tiny, testable labs—diagram, deploy, measure, and document your decisions. Photo via Unsplash.

12 hands-on labs that double as interview stories

Build one mini-project per topic and document four things: diagram, steps, costs, and trade-offs. These labs map directly to typical associate-level interviews.

LabFocusDeliverable
1) Static site on CDNStorage + CDN + DNSDiagram + cost note + TTL explanation
2) Containerized web appRegistry + orchestrationDockerfile + service manifest + scaling policy
3) RDS/managed DB backupSnapshots + retentionBackup plan + restore test results
4) Message queue workerAsync processingQueue config + idempotent worker notes
5) Event-driven image resizeFunctions + triggersFunction code + retry/backoff strategy
6) VPC with public/private subnetsNetworking + NATCIDR plan + route tables + security groups
7) Centralized logs & alertsObservabilityAlert rules + runbook for a common error
8) Cost guardrailsBudgets + alerts + tagsBudget policy + teardown script
9) Three-tier web appLB + compute + DBHA diagram + failover test notes
10) Data pipelineIngest → store → transformETL code + partitioning rationale
11) Secrets managementKMS + rotationRotation plan + least-privilege policy
12) Blue/green or canary releaseSafe deploysSwitch strategy + rollback checklist

Résumé & LinkedIn: translate labs into proof

  • Role-matching headline: “Cloud Admin | Infra as Code | Monitoring & Cost Controls.”
  • Project bullets: use problem → action → quantified result. Example: “Cut page load by 48% using CDN + object storage; reduced egress by 22% with cache headers.”
  • Portfolio links: pin two or three labs with short readmes and diagrams; keep the rest in a “more projects” list.

Interview prep (scenario prompts you can practice)

  • Design for resiliency: “Traffic will spike 5× for 48 hours. How do we scale safely and cap costs?”
  • Identity & access: “A contractor needs temporary access to a single bucket; what’s the minimum set of permissions?”
  • Networking: “Two services in different subnets need to talk securely—outline your approach.”
  • Observability: “We’re blind to 502s at the edge—what would you instrument and where?”

Answer out loud while pointing at a simple sketch. Emphasize trade-offs: cost vs. latency, simplicity vs. control, speed vs. safety.

team whiteboarding network and service interactions with sticky notes
Sketch first, then pick services. Clear diagrams make interviews—and real deployments—go faster. Photo via Unsplash.

Study rhythm for busy professionals to achieve your cloud certifications goals (8-week template)

WeekFocusDeliverable
1Identity + IAM basicsTwo policies + least-privilege notes
2Compute + autoscalingHorizontal scale lab + cost note
3Storage tiers + CDNCache headers + invalidation test
4Networking + security groupsVPC + subnet diagram
5ObservabilityAlerts + runbook
6Data servicesETL pipeline + partition plan
7Security hardeningKey rotation + secrets lab
8Practice tests + gaps≥1 full practice test at passing score

Lab cost control (so practice doesn’t surprise you)

  • Budgets & alerts: set a low monthly cap and configure email/SMS at 50/80/100% thresholds.
  • Tags: tag every resource by project and auto-delete anything without a tag using a nightly script.
  • Teardown: keep a single destroy-all script; run it after each session and before bed.
  • Free tiers: stick to smallest instance types; turn off logging you don’t need in prototypes.

Readiness checklist (use before you book)

  • You’ve finished two full practice tests at or above the passing score.
  • You can whiteboard a three-tier app with identity, networking, and cost notes in under 7 minutes.
  • You have three mini-projects with readmes and diagrams you can explain without looking at notes.
  • Your calendar has a retake window two weeks after the first attempt—just in case.

Authoritative external resources (dofollow)

  • AWS — Certification Portal
  • Microsoft Learn — Certifications
  • Google Cloud — Certification

Bottom line

Keep your plan small and concrete—one role, one provider path, one exam date. Publish lab notes weekly, and use practice tests to close gaps. With that rhythm, the interviews come faster and feel easier.

Disclaimer: Informational content. Verify current exam names, formats, and prices on official certification pages. No employment or earnings guarantees.

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