A structured view of my ongoing learning across Product Management, Cloud and Support Engineering, and professional skills — turning study into practice.
An 8-week structured learning programme covering PM fundamentals, user research, product design, growth, metrics, tech, and roadmapping — built from real course notes and applied to live products.
What is a PM, responsibilities, role types, myths, and the product life cycle.
5 Whys, MECE, Issue Trees, KPI Trees, Product Thinking, and the Opportunity Solution Tree.
JTBD, personas, segments, journey maps, design thinking, and turning insights into decisions.
Ideation techniques, wireframes, user flows, MVP validation, storyboarding and mind maps.
AARRR framework, growth loops, flywheels, growth channels, and product-led growth.
North Star metrics, cohort analysis, funnels, A/B testing, events design, and root cause analysis.
APIs, databases, system design, technical debt, webhooks, and SQL for product decisions.
OKRs, prioritisation, stakeholder management, customer feedback, PRDs, and roadmapping.
Dual-track Agile, user research, personas, JTBD, usability testing, RICE, Kano, and outcome-based roadmapping.
Open ModuleWriting great Objectives and Key Results, cascading alignment, quarterly cadence, honest grading, and strategy hierarchy.
Open ModuleDouble Diamond, IA, wireframing, prototyping, usability testing, visual design, Gestalt principles, and design systems.
Open ModuleThree disciplines that together cover how software is planned, analysed, and delivered — Agile methodology, Business Analysis, and Project Management. Each is a standalone profession; together they represent the full delivery toolkit.
Agile foundations, Scrum framework, CSPO, CSM, backlog prioritisation, Kanban and flow metrics — with downloadable Excel templates.
BA role and accountability, requirements types, elicitation techniques, use cases vs user stories, BPMN process modelling, gap analysis, BRD documentation, and BA in Agile.
PMBOK process groups and knowledge areas, WBS, critical path, Earned Value Management, risk registers, stakeholder management, RACI, quality, procurement, and Agile/hybrid PM.
Testing fundamentals, STLC, manual vs automated testing, test pyramid, Selenium, API testing, performance testing, test management, and defect lifecycle.
Why change fails, the ADKAR model, change sponsorship, resistance management, communication and training planning, Kotter's 8 steps, and sustaining change.
Lean philosophy and waste elimination, value stream mapping, DMAIC methodology, statistical process control, Six Sigma belts, Design for Six Sigma, and Lean-Agile integration.
Core AWS services, the shared responsibility model, and how cloud infrastructure underpins modern enterprise platforms.
Full AWS Cloud Computing Module — 8 modules · 18 topicsEC2 (virtual machines), Lambda (serverless functions), ECS/EKS (containers). Understanding when to use each and the trade-offs between managed and unmanaged compute.
S3 (object storage), EBS (block storage for EC2), EFS (shared file system). Key use cases: static assets in S3, database volumes on EBS, shared config files on EFS.
VPC, subnets (public vs private), Security Groups, NAT Gateway, and Route 53 (DNS). How traffic flows from internet to application inside a VPC.
RDS (managed relational), DynamoDB (NoSQL), ElastiCache (in-memory caching), Redshift (data warehouse). Choosing the right store for the access pattern.
Identity and Access Management — users, groups, roles, policies. Principle of least privilege. How IAM roles are assumed by services (EC2 instance roles, Lambda execution roles).
SQS (queues), SNS (pub/sub notifications), EventBridge (event routing). Decoupling services so failures don't cascade across the system.
AWS manages security of the cloud (physical hardware, data centres, hypervisor layer). Customers manage security in the cloud (OS patching, application security, data encryption, IAM configuration).
Understanding deployment pipelines, environment promotion, and release strategies that support enterprise software delivery.
Full DevOps Learning Module — 8 modules · 14 topicsContinuous Integration (CI) automates code integration and testing. Continuous Delivery (CD) automates deployment to environments. Together they compress the time between a developer writing code and that code running in production.
Developer pushes to version control (Git). CI server triggers automated build — compiles code, resolves dependencies, creates a deployable artifact (Docker image, JAR, ZIP).
Unit tests, integration tests, and security scans run automatically. If any test fails, the pipeline stops — preventing broken code from progressing to deployment.
Artifact is deployed to Dev → QA → Staging → Production. Each stage has approval gates and environment-specific configuration (different DB endpoints, feature flags, logging levels).
Deployment to production using a controlled strategy. Monitoring is triggered post-deploy to catch regressions. Rollback plan is pre-defined before any release goes live.
Two identical environments. Traffic is switched from Blue (old) to Green (new) instantly. Easy rollback — just switch traffic back. Higher infrastructure cost.
New version rolled out to a small % of users first (e.g. 5%). Monitor metrics. If healthy, gradually increase to 100%. Limits blast radius of bad releases.
Instances updated one-by-one or in batches. Old and new versions run simultaneously during rollout. No extra infrastructure needed but rollback is slower.
Logs, metrics, and alerts — the three pillars of observability that enable proactive support and fast incident response.
Timestamped records of events. Used for debugging specific errors. Structured logs (JSON) are searchable. Centralised using CloudWatch Logs, ELK Stack, or Datadog Log Management.
Numeric time-series data — CPU %, memory usage, API response time, error rate, request count. Aggregated and visualised on dashboards. Trigger alarms when thresholds are crossed.
End-to-end visibility across distributed services. A trace shows the full path of a request through multiple microservices — helps identify which service is the bottleneck causing latency.
AWS CloudWatch collects metrics from all AWS services automatically. Custom application metrics can be published via the PutMetricData API. Alarms trigger SNS notifications (email, Slack, PagerDuty) or Auto Scaling actions.
Set thresholds based on baselines, not guesses. Use anomaly detection for variable patterns. Avoid alert fatigue by only alerting on conditions that require human action.
Define log retention periods per environment. Production logs: 90 days minimum for audit compliance. Dev/QA logs: 7-14 days. Archive to S3 for cost-efficient long-term storage.
Structured response to system failures — from detection and triage through resolution and post-incident review.
Alert fires from monitoring (CloudWatch alarm, Datadog monitor, user-reported ticket). Incident declared and severity level assigned (P1 = critical, P2 = major, P3 = minor).
Incident commander assigned. Relevant engineers, support leads, and stakeholders join the incident bridge (Zoom/Teams). Communication channel opened in Slack.
Check recent deployments (last change = first suspect). Review CloudWatch metrics and error logs. Isolate whether it is infrastructure, application code, data, or a third-party integration.
Apply fix or workaround to restore service — even before root cause is fully known. Examples: rollback deployment, increase instance capacity, disable a broken feature flag, re-route traffic.
Service restored and confirmed stable. Update all stakeholders and status page. Close the incident. Schedule post-incident review within 48 hours.
Blameless review of what happened, why it happened, and what will prevent recurrence. Outputs: timeline of events, root cause, action items with owners and due dates.
The 5 Whys technique traces a problem back to its root cause by asking "why" repeatedly until you reach a systemic issue, not just a symptom.
Using SQL to quickly diagnose data issues, investigate customer problems, and validate system state without waiting for an analyst.
Full SQL & Data Fundamentals Module — 5 modules · 12 topicsSELECT a.action_type, a.created_at, a.status
FROM user_activity a
WHERE a.user_id = '12345'
ORDER BY a.created_at DESC
LIMIT 20;SELECT t.transaction_id, t.user_id, t.amount, t.error_code, t.created_at
FROM transactions t
WHERE t.status = 'FAILED'
AND t.created_at >= NOW() - INTERVAL '24 hours'
ORDER BY t.created_at DESC;SELECT error_code, COUNT(*) AS occurrences
FROM transactions
WHERE status = 'FAILED'
AND created_at >= NOW() - INTERVAL '7 days'
GROUP BY error_code
ORDER BY occurrences DESC;Structured approaches to diagnosing and resolving complex technical issues under time pressure.
Gather facts: what is broken, who is affected, when did it start, what changed recently? Separate symptoms from the actual failure.
Is it one user or all users? One region or global? One feature or the entire platform? Scope narrows the search space dramatically.
Follow the request path end-to-end: browser → CDN → load balancer → application server → database. Check logs and metrics at each layer.
List the most likely causes. Prioritise by probability and ease of testing. Test the most likely cause first — check recent deployments, configuration changes, and data anomalies.
Apply a fix or workaround. Test in a non-production environment first if time allows. Validate that the fix resolves the issue and does not create a new one.
Record the timeline, root cause, and resolution in the ticket or incident record. Add to the runbook. Share learnings with the team so the same issue is resolved faster next time.
How APIs work, REST principles, HTTP methods, OAuth 2.0, JWT authentication, API design best practices, and GraphQL vs gRPC comparisons.
Full API Fundamentals Module — 7 modules · 15 topicsGET (read, safe, idempotent) · POST (create, non-idempotent) · PUT (full replace, idempotent) · PATCH (partial update) · DELETE (remove, idempotent). Method choice determines caching, safety, and retry behaviour.
2xx Success · 3xx Redirect · 4xx Client Error (401 unauthenticated, 403 forbidden, 404 not found, 422 validation, 429 rate limited) · 5xx Server Error. Always return meaningful status codes — never 200 for errors.
API Key (server-to-server) · OAuth 2.0 (delegated user auth — Auth Code + PKCE for browsers/mobile, Client Credentials for M2M) · JWT (self-contained token, verified by signature, not lookup).
REST: public APIs, universal browser support. GraphQL: complex data graphs, precise field selection. gRPC: internal microservices, binary Protocol Buffers, HTTP/2, streaming — 5–10x faster than JSON.
Learning modules built from real course notes, plus professional Excel templates you can download and use directly.
8 modules · 61 topics — PM foundations, user research, ideation, growth, metrics, roadmapping.
Open module →Requirements elicitation, stakeholder mapping, use cases, and BA documentation standards.
Open module →Sprint ceremonies, backlog management, story pointing, velocity tracking, and retrospectives.
Open module →9 modules · 20 topics — EC2, Lambda, S3, RDS, VPC, CloudWatch, Secrets Manager, SSM, and more.
Open module →8 modules · 14 topics — pipelines, containers, IaC, monitoring, and DevOps culture.
Open module →5 modules · 12 topics — SELECT to JOINs, aggregations, subqueries, and BI query patterns.
Open module →7 modules · 15 topics — REST, HTTP, OAuth, JWT, GraphQL, gRPC, and Postman.
Open module →6 modules · 13 topics — design thinking, user research, wireframing, and design systems.
Open module →6 modules · 12 topics — ADKAR, change readiness, stakeholder engagement, and resistance.
Open module →8 modules · 15 topics — Lean, Six Sigma, value stream mapping, and process optimisation.
Open module →8 modules · 15 topics — testing types, test plans, automation, and QA best practices.
Open module →Setting and tracking Objectives and Key Results — strategy, alignment, and scoring.
Open module →Prioritise features using RICE scores, story points, sprint assignment, and status.
DownloadQuarterly objectives with key results, current scores, owner, and confidence ratings.
DownloadRisk log with probability, impact, severity score, mitigation plan, and owner.
DownloadWeekly health report — Red/Amber/Green status, issues, decisions needed, and next actions.
DownloadWhat went well, what didn't, what to try next sprint — with action items and owners.
DownloadTrack team velocity sprint-over-sprint — planned vs completed points with trend charts.
DownloadInfluence-interest grid, stakeholder profiles, engagement level, and communication preferences.
DownloadTeam capacity planning across sprints — allocation, availability, and workload balancing.
DownloadTrack change requests — impact, priority, approval status, and implementation dates.
Download