How client work, structured learning, hands-on practice, and a few uncomfortable challenges helped me earn all 12 active AWS certifications, along with the now-retired Database Specialty.
In early 2016, I started working with AWS through Lambda, API Gateway, DynamoDB, serverless architectures, and CI/CD pipelines. I learned primarily by building solutions for clients and customers across different domains and use cases.
AWS was not something I opened only while studying. It became part of my everyday working life: designing an API, deciding where a workload should run, investigating a deployment problem, thinking about permissions, or explaining a cloud trade-off to a customer. That daily exposure gave the services context that no list of flashcards could provide.
Over time, I added structure to that experience through AWS certifications, focused reading, courses, and hands-on practice. The result is 12 currently active AWS certifications, plus the AWS Certified Database - Specialty, which has since been retired.
This is the timeline of that journey.
The Timeline
2020: Finally taking the first step
AWS Certified Solutions Architect - Associate
SAA-C02 | June 2020
I had already been working with AWS for four or five years, but I kept postponing the exam because I felt I was not ready. Eventually, I decided to take it anyway and passed.
There was a slightly uncomfortable gap between how much AWS I used at work and how ready I felt for an exam. I could discuss architectures and solve day-to-day problems, but the exam still felt like an official judgement of whether I knew enough. Passing it showed me that the experience was already there; I mainly needed to organise it and trust it.
That first certification was an important lesson: practical experience matters, but waiting until you feel completely ready can become its own form of procrastination.
2021: Building the foundation
AWS Certified Cloud Practitioner
CLF-C01 | June 2021
This was the only certification in the journey that I took after the Solutions Architect - Associate. By then, I had more AWS project experience and a clearer understanding of how the different parts of the platform fit together.
2022: Stretching beyond architecture
I wanted to test myself across the full lifecycle of building and operating cloud applications. I took two Associate exams on the same day, back to back.
AWS Certified Developer - Associate
DVA-C01 | February 2022
AWS Certified SysOps Administrator - Associate
SOA-C02 | February 2022
The SysOps exam was especially memorable because it included a live lab exercise. Instead of answering only multiple-choice questions, I had to work directly in an AWS environment and complete practical tasks. It was a unique and enjoyable experience, and the only exam in this journey that included a similar hands-on lab assessment.
Later that year, I made my first move into the Professional-level exams.
AWS Certified DevOps Engineer - Professional
DOP-C01 | May 2022
Working with AWS CI/CD pipelines and delivering software for customers gave me a strong practical foundation for this exam. The certification also pushed me to think beyond individual services and focus on delivery, reliability, automation, and operations as a complete system.
In real projects, a pipeline is never just a pipeline. It is also about permissions, artifact handling, deployment strategy, rollback, observability, and the point at which a change should be allowed into production. Seeing those concerns repeatedly in customer work made the exam scenarios feel less like isolated questions and more like familiar engineering decisions.
2023: Specialisation and deeper architecture
AWS Certified Database - Specialty
DBS-C01 | January 2023
I have always been fascinated by databases. Before AWS, I had worked with Oracle, IBM Db2, and MySQL. On AWS, I worked with RDS and Aurora from the early days, including experimenting with the first version of Aurora Serverless, which was not yet production-ready.
This was my first AWS Specialty certification. The certification has since been retired, but the knowledge remains useful.
AWS Certified Security - Specialty
SCS-C02 | October 2023
AWS Certified Solutions Architect - Professional
SAP-C02 | November 2023
I completed the Solutions Architect - Professional exam on a day when I was travelling internationally for a vacation. I received the result while on the flight, which made for a memorable end to that part of the journey.
It is not the most conventional place to receive an exam result, but it captured how this journey fitted around life and work. The certification was important, but it was not pursued in a vacuum. It sat alongside projects, deadlines, travel, and the ordinary interruptions that make long-term learning real.
2024: Data, machine learning, and AI
AWS Certified Machine Learning Engineer - Associate (Beta)
MLA-C01 | October 2024
AWS Certified AI Practitioner
AIF-C01 | October 2024
My interest in data and machine learning naturally led me towards these certifications. Taking a beta exam also meant learning from a new blueprint and being comfortable with some uncertainty in the exam experience.
2025: Connecting data engineering to the cloud
AWS Certified Data Engineer - Associate
DEA-C01 | March 2025
This certification brought together several areas I had been working towards: data stores, data processing, governance, security, monitoring, and designing reliable data pipelines on AWS.
2026: Generative AI, renewal, and a networking challenge
AWS Certified Generative AI Developer - Professional (Beta)
AIP-C01 | March 2026
This was almost three and a half hours of intense concentration. My experience with Amazon Bedrock and Retrieval-Augmented Generation helped me relate many of the exam scenarios to real use cases. Those practical connections made the exam challenging, but approachable.
AWS Certified Solutions Architect - Associate
SAA-C03 | April 2026
In the meantime, my original Solutions Architect - Associate certification had expired, so I took the current version again. Renewal was a useful reminder that certifications are not only milestones; they are also a reason to revisit fundamentals and keep them current.
AWS Certified Advanced Networking - Specialty
ANS-C01 | May 2026
Networking was the area I had consciously avoided because I had not had as many opportunities to work deeply in it. Eventually, I decided to challenge myself.
I did not clear my first attempt, possibly missing by only one question or one option. Then work became busy, and I saw the announcement that the exam was scheduled to be retired on 25 August. I took it again the day before the announced deadline and passed. AWS later extended the exam availability until December 2026, but by then my result was already in.
That experience was a useful counterweight to the successful first attempts. A failed exam does not always mean that the whole approach is wrong. Sometimes it points to a narrow gap, a weak area, or the need to become more comfortable with the way questions are framed. The second attempt was less about starting over and more about closing that specific gap.
What Actually Helped
The early certifications were based heavily on experience gained through project work across customers, industries, and use cases. That experience gave me context for the services and architecture patterns that appeared in the exams.
Working on AWS day in and day out creates a library of mental examples. A question about an asynchronous integration can connect to a real Lambda workflow. A question about deployment safety can bring back a pipeline decision. A question about database scaling can connect to a production conversation about read replicas, caching, or Aurora. The details vary, but the underlying decision patterns repeat.
Structured learning helped me organise that experience. I used AWS documentation, Stephen Marek's courses, and other Udemy courses depending on the topic and the exam.
For the later certifications, especially data engineering, machine learning, and generative AI, I relied more on a combination of structured reading, scenario-based learning, and hands-on work. When a concept was unclear, I used Google Search and Google Chat to gather explanations and related scenarios instead of trying to navigate the enormous AWS documentation landscape for every question.
That approach supplemented, rather than replaced, the official material. I still validated concepts by using the services and tools directly. Reading about a feature helped me recognise it; building with it helped me understand it.
The correlation between study and real work also made recall faster. Instead of memorising that a service had a particular feature, I could attach the concept to a scenario: a customer constraint, a design trade-off, a deployment failure, or a small experiment I had run myself. Those associations gave the information somewhere to live.
Hands-on work was especially useful when a topic felt abstract. Creating a small proof of concept, checking how a service behaved, or tracing a request through several AWS components often answered a question more clearly than another hour of passive reading. The goal was not to reproduce an entire customer system at home. It was to isolate one idea and make it observable.
The most effective loop for me was:
Project experience -> Structured study -> Scenario-based questions -> Hands-on practice -> Exam
Each part strengthened the others. Client work made the material concrete. Study exposed gaps in my understanding. Practice questions showed me how concepts were tested. Hands-on work made the answers easier to remember.
That is why I do not see work experience and certification preparation as separate tracks. Work gives the concepts texture; study gives them structure. When the two are connected, learning becomes quicker, recall becomes more reliable, and the exam preparation feels much closer to the engineering problems I actually enjoy solving.
The Bigger Lesson
I did not earn these certifications by following a perfect plan. I postponed the first exam, took two exams back to back, attempted a difficult Specialty twice, and kept learning as my work changed from serverless applications to databases, security, data engineering, machine learning, and generative AI.
The certifications gave structure to a decade of learning. The project work gave that structure meaning.
My advice to anyone considering an AWS certification is simple: use your real work as the foundation, add enough structure to expose what you do not know, and take the exam before waiting for perfect confidence.
What has helped you most when preparing for cloud certifications: project experience, structured study, or hands-on practice?
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