# Senad Dizdarević — DevOps & Cloud Engineer > AWS-certified DevOps and cloud engineer focused on secure automation, reliable delivery pipelines, and measurable cloud outcomes. Works in two delivery modes: embedded partner for hiring teams and focused consultant for freelance clients. In both cases the goal is the same: simple architecture first, reliable automation, strong security posture, and clear operational ownership after handover. Site: https://senad-d.github.io/portfolio/ Email: senad.dizdarevic.ri@gmail.com GitHub: https://github.com/senad-d LinkedIn: https://www.linkedin.com/in/senad-dizdarevic-devops Upwork: https://www.upwork.com/freelancers/~017a10028c45b2150f YouTube: https://www.youtube.com/@senaddizdarevic7849 # Experience ## DevOps Engineer — Principal Technology CSE — Valcon (full-time) Period: Jan 2026 — Present - Focus: Amazon Web Services (AWS), Terraform, and platform engineering. - Lead enterprise cloud delivery with secure and scalable infrastructure patterns. ## DevOps Engineer — Upwork (freelance) Period: Feb 2025 — Present - Focus: Amazon Web Services (AWS) and Terraform. - Design and operate production-ready AWS environments for freelance clients. ## DevOps Engineer — Senior Specialist — Valcon (full-time) Period: Jul 2024 — Jan 2026 - Focus: Amazon Web Services (AWS) and Terraform. - Scaled reusable IaC and deployment workflows across client engagements. ## DevOps Technology Specialist — Valcon (full-time) Period: Jan 2023 — Jul 2024 - Focus: infrastructure and Linux. - Supported stable operations and core infrastructure improvements. ## DevOps Engineer — Valcon (full-time) Period: Sep 2022 — Jan 2023 - Focus: infrastructure, Git, and DevOps tooling. - Built foundational delivery workflows for cloud platform work. ## Technical Support Manager — INA Grupa (full-time) Period: Jan 2011 — Nov 2022 - Led long-term on-site production support operations. - Built incident communication and coordination discipline applied in later DevOps delivery. # Skills Core tools: AWS, Terraform, Docker, Git, Pi ## AWS Platform Delivery - AWS Organisations - AWS SecurityHub - AWS Config - IAM - VPC - AWS TransitGateway - LoadBalancer - CloudMap - EC2 - ECS - EKS - Lambda - API Gateway - RDS - DynamoDB - S3 - ECR - ElastiCache - CodeArtifact - CloudFront - Route 53 - Cognito - WAF - SES - SNS - SQS - SecurityHub - ParameterStore - CodeConnect ## Tools & Automation - Terraform - CloudFormation - GitHub Actions - CodePipeline - Jenkins - Git - Docker - OpenID - Keycloak - OpenVPN ## Frameworks and Languages Used Across Projects - Spring Boot - Golang - Java - Node.js - React - Angular - TypeScript - JavaScript - .NET - Python - Bash ## Observability & Security - CloudWatch - Grafana - Loki - Prometheus - Tempo - OpenTelemetry - Trivy - OWASP Dependency-Check - Security Hub - AWS Config ## LLM Tooling - Microsoft Foundry - AWS Bedrock - Claud - Codex - Pi - LiteLLM - Ollama - LM Studio # Certifications ## AWS Certified Solutions Architect — Associate - Issuer: Amazon Web Services - Issued: Jan 2023 - Credential ID: 9FRV6K8KYBVEQG92 - Verify: https://www.certmetrics.com/amazon/public/verification.aspx?code=9FRV6K8KYBVEQG92&lang=en # Projects ## DrawMe Natural-Language Diagramming for Pi - Slug: drawme-pi-diagram-authoring - Lane: personal - Status: in-progress - Period: Aug 2026 — Present - Stack: Pi, TypeScript, Node.js, npm, draw.io, Mermaid - Impact: Published DrawMe as a scoped npm package with global, project-local, one-run, Git, and local checkout install paths. | Delivered nine agent tools and three commands for planning, authoring, validating, previewing, explaining, and exporting diagrams. | Improved diagram accuracy with structural linting, image-aware review, editable exports, and a local index of more than 10,000 official cloud and modeling shapes. - Link (github): https://github.com/senad-d/DrawMe - Link (npm): https://www.npmjs.com/package/@senad-d/drawme - Markdown: https://senad-d.github.io/portfolio/projects/drawme-pi-diagram-authoring.md Built a Pi extension that turns natural-language descriptions into validated, editable draw.io diagrams and local image exports. ## Problem Architecture and workflow diagrams are valuable documentation, but manually laying out editable diagrams and checking connections, geometry, and export quality interrupts development flow. ## Approach Built DrawMe as a Pi extension that plans diagrams from natural-language prompts, authors draw.io XML or Mermaid, validates each revision with a deterministic structural linter, reviews rendered previews when the active model supports images, and exports editable PNG, SVG, PDF, or JPG deliverables through the local draw.io CLI. ## Result DrawMe turns a single Pi prompt into a repeatable local diagram workflow with editable source, deterministic validation, exact shape lookup, and multi-format output. ## AnalyseMe Sonar Quality Analysis for Pi - Slug: analyseme-pi-sonar-analysis - Lane: personal - Status: in-progress - Period: Jul 2026 — Present - Stack: Pi, TypeScript, Node.js, npm, SonarQube, SonarCloud - Impact: Published AnalyseMe as a scoped npm package with global, project-local, one-run, Git, and local checkout install paths. | Delivered six tools and two commands for quality gates, metrics, issues, source context, security hotspots, guidance, and fresh scanner submissions. | Kept analysis reads repository-safe and masked Sonar tokens across command output, tool results, errors, and tests. - Link (github): https://github.com/senad-d/analyseme - Link (npm): https://www.npmjs.com/package/@senad-d/analyseme - Markdown: https://senad-d.github.io/portfolio/projects/analyseme-pi-sonar-analysis.md Built a Pi extension that lets coding agents inspect SonarQube and SonarCloud quality data and optionally submit a fresh local scan. ## Problem Code-quality findings often live outside the coding-agent workflow, forcing developers to switch context and manually translate quality gates, issue locations, rule guidance, and security hotspots into actionable changes. ## Approach Built AnalyseMe as a Pi extension that resolves project and branch context, reads SonarQube or SonarCloud quality data, returns bounded issue and hotspot details with source guidance, and optionally invokes the local SonarScanner to submit a requested fresh analysis. Credentials stay in environment variables and are masked from outputs. ## Result AnalyseMe brings quality-gate and finding context into Pi through read-focused tools, with one explicit scan path for validating changes against the configured Sonar server. ## ObservMe OpenTelemetry for Pi Agent Sessions - Slug: observme-pi-opentelemetry-observability - Lane: personal - Status: in-progress - Period: Jul 2026 — Present - Stack: Pi, TypeScript, Node.js, npm, OpenTelemetry, Grafana - Impact: Published ObservMe as a scoped npm package with global, project-local, one-run, Git, and local checkout install paths. | Instrumented session, turn, model, tool, shell, compaction, branch, workflow, and multi-agent lineage events as OTLP traces, metrics, and logs. | Preserved coding flow with fail-open exporters and privacy-first defaults that exclude prompts, responses, tool payloads, and shell content unless explicitly enabled. - Link (github): https://github.com/senad-d/ObservMe - Link (npm): https://www.npmjs.com/package/@senad-d/observme - Markdown: https://senad-d.github.io/portfolio/projects/observme-pi-opentelemetry-observability.md Built a Pi extension that exports privacy-conscious traces, metrics, and logs for agent sessions to standard observability backends. ## Problem Multi-step coding-agent sessions are difficult to troubleshoot because model calls, tools, shell activity, compaction, and child-agent work span one workflow without a shared operational view. ## Approach Built ObservMe as a Pi extension that maps lifecycle and agent events to OpenTelemetry traces, metrics, and logs, exports them through bounded OTLP pipelines, and propagates agent lineage plus W3C trace context across subagent processes. Content capture remains disabled by default and enabled data passes through redaction and path scrubbing. ## Result ObservMe makes Pi workflows observable in standard Collector and Grafana stacks without blocking sessions when telemetry is unavailable or collecting prompt and tool content by default. ## ProtectMe Network Access Guardrails for Pi - Slug: protectme-pi-network-access-guardrails - Lane: personal - Status: in-progress - Period: Jul 2026 — Present - Stack: Pi, TypeScript, Node.js, npm, Network Security, Shell - Impact: Published ProtectMe as a scoped npm package with global, project-local, one-run, Git, and local checkout install paths. | Guarded curl, wget, http, and https requests, including approved wrappers and options that can introduce additional destinations. | Added default-block allow-list policy, one-time or persisted approval flows, and bounded local logs that redact common credential-bearing fragments. - Link (github): https://github.com/senad-d/protectme - Link (npm): https://www.npmjs.com/package/@senad-d/protectme - Markdown: https://senad-d.github.io/portfolio/projects/protectme-pi-network-access-guardrails.md Built a Pi extension that checks supported agent and user shell network requests against global and project allow lists before execution. ## Problem Coding agents and direct terminal commands can contact unapproved destinations, creating accidental data exposure and dependency-download risks that are difficult to review after execution. ## Approach Built ProtectMe as a Pi event guard that inspects supported request-making shell commands, extracts destinations, and checks them against normalized global and trusted project allow lists. Unknown hosts fail closed, while interactive approvals can permit one request or persist a narrow host decision without storing secrets. ## Result ProtectMe adds transparent network-destination control to supported Pi shell flows with project-aware policy and secret-conscious audit logs, while clearly remaining a guardrail rather than a firewall or sandbox. ## BranchMe Git Workflow Automation for Pi - Slug: branchme-pi-git-workflow-automation - Lane: personal - Status: in-progress - Period: Jun 2026 — Present - Stack: Pi, TypeScript, Node.js, npm, Git, GitHub - Impact: Published BranchMe as a scoped npm package with global, project-local, one-run, Git, and local checkout install paths. | Exposed 19 agent-callable tools plus a bounded read-only repository snapshot for branch, worktree, integration, push, and pull request workflows. | Added strict safety boundaries that verify repository and worktree state, avoid force pushes, and never stage files or create user-authored commits. - Link (github): https://github.com/senad-d/branchme - Link (npm): https://www.npmjs.com/package/@senad-d/branchme - Markdown: https://senad-d.github.io/portfolio/projects/branchme-pi-git-workflow-automation.md Built a Pi extension that verifies repository state and automates branch, worktree, integration, push, and pull request workflows. ## Problem Coding agents need current Git context to work safely, but branch, worktree, and pull request automation can damage local history when repository state or command scope is assumed rather than verified. ## Approach Built BranchMe as a Pi extension that injects a bounded read-only repository snapshot and exposes strict tools for repository initialization, branch changes, linked worktrees, integration, retirement, remote updates, pushes, and GitHub pull requests. Each mutating workflow validates its repository, cleanliness, branch, and worktree preconditions before acting. ## Result BranchMe provides a context-aware Git workflow for Pi that supports isolated agent handoffs and pull request delivery while keeping history rewrites explicit and commit creation outside the extension. ## CommitMe Pi Commit Assistant - Slug: commitme-pi-commit-assistant - Lane: personal - Status: in-progress - Period: Jun 2026 — Present - Stack: Pi, TypeScript, Node.js, npm, Git, LLM Tooling - Impact: Published CommitMe as a scoped npm package with slash-command, agent-tool, global, project-local, one-run, Git, and local checkout install paths. | Improved commit quality by gathering staged and unstaged git context, trimming noisy diffs, accepting steering text, and producing Lightweight Conventional Commit messages. | Added safety guardrails that redact sensitive context, refuse known secret files and high-confidence tokens, recheck repository status before staging, and never push. - Link (github): https://github.com/senad-d/CommitMe - Link (npm): https://www.npmjs.com/package/@senad-d/commitme - Markdown: https://senad-d.github.io/portfolio/projects/commitme-pi-commit-assistant.md Built a Pi extension that turns local git changes into safe Lightweight Conventional Commit messages and creates local commits. ## Problem Turning a busy local diff into a clear commit message takes time, and inconsistent commit wording becomes more likely when work spans staged, unstaged, generated, or noisy files. ## Approach Built CommitMe as a Pi extension and npm package that reads local git status, staged and unstaged paths, diff stats, redacted diff excerpts, and safe project metadata. It builds a compact prompt for the active Pi model, supports optional steering text and confirmation, validates the Lightweight Conventional Commit shape, then stages changes and creates a local commit without pushing. ## Result CommitMe provides a repeatable local workflow for drafting, reviewing, and creating clear commits from actual repository changes while keeping safety checks, redaction, and no-telemetry behavior built in. ## GuardMe Pi Tool-Call Safety Guardrails - Slug: guardme-pi-tool-call-safety-guardrails - Lane: personal - Status: in-progress - Period: Jun 2026 — Present - Stack: Pi, TypeScript, Node.js, npm, YAML, Security, LLM Tooling - Impact: Published GuardMe as a scoped npm package with global, project-local, one-run, Git, and local checkout install paths for Pi. | Reduced accidental risky model actions with deny-first shell and filesystem guards for cloud CLIs, credentials, `.git`, `.env`, destructive commands, and sensitive paths. | Added a policy-driven approval workflow that merges global and project YAML rules, tracks warned fingerprints, and supports safe one-time or persisted decisions. - Link (github): https://github.com/senad-d/GuardMe - Link (npm): https://www.npmjs.com/package/@senad-d/guardme - Markdown: https://senad-d.github.io/portfolio/projects/guardme-pi-tool-call-safety-guardrails.md Built a Pi extension that enforces deny-first policy for shell and filesystem tool calls with YAML rules, path protections, and approval flows. ## Problem Coding agents can call powerful local shell and filesystem tools with full user permissions, so a mistaken or overly broad model request can read secrets, mutate protected files, or run risky commands before the user notices. ## Approach Built GuardMe as a Pi extension that checks shell and file tool calls before execution. It merges global and project YAML policy, evaluates compound shell commands by executable segment, protects sensitive paths and generated shell-like content, and uses in-session approval only after first blocking and coaching risky actions that are not hard-denied. ## Result GuardMe gives Pi sessions IAM-like deny-first guardrails while staying configurable through `/guardme` and policy files, making local AI-assisted development safer without presenting itself as an OS sandbox. ## IssueMe GitHub Issue Management for Pi - Slug: issueme-pi-github-issue-management - Lane: personal - Status: in-progress - Period: Jun 2026 — Present - Stack: Pi, TypeScript, Node.js, npm, GitHub REST API, GraphQL - Impact: Published IssueMe as a scoped npm package with global, project-local, one-run, Git, and local checkout install paths. | Exposed 29 tools for issues, labels, milestones, comments, assignees, Projects v2, sub-issues, development links, deletion, and bulk workflows. | Kept agent context bounded with a local issue cache while protecting tokens and requiring explicit confirmation for destructive taxonomy and deletion operations. - Link (github): https://github.com/senad-d/IssueMe - Link (npm): https://www.npmjs.com/package/@senad-d/issueme - Markdown: https://senad-d.github.io/portfolio/projects/issueme-pi-github-issue-management.md Built a Pi extension that gives coding agents repository-scoped GitHub issue workflows through structured API tools and bounded local context. ## Problem Agents need complete issue context to plan and track work, but raw GitHub API usage creates authentication, repository-boundary, pagination, destructive-action, and oversized-response risks. ## Approach Built IssueMe as a Pi extension that resolves the active repository, communicates with GitHub through REST and GraphQL APIs, stores bounded non-secret issue context locally, and exposes structured tools for issue lifecycle, planning metadata, Projects v2, sub-issues, and linked development. ## Result IssueMe provides an agent-friendly issue management layer that supports discovery and updates from Pi while keeping repository scope, local cache behavior, token handling, and destructive confirmations explicit. ## MicMe Local Voice-to-Text Pi Extension - Slug: micme-local-voice-to-text-pi-extension - Lane: personal - Status: in-progress - Period: Jun 2026 — Present - Stack: Pi, TypeScript, Node.js, npm, ffmpeg, whisper.cpp - Impact: Published MicMe as a scoped npm package with global, project-local, one-run, Git, and local checkout install paths. | Preserved privacy by keeping speech-to-text local by default with ffmpeg, whisper.cpp, Python Whisper, or custom backends. | Improved coding-agent prompt flow with toggle recording, review-first transcript insertion, device discovery, configuration, and diagnostics. - Link (github): https://github.com/senad-d/micme - Link (npm): https://www.npmjs.com/package/@senad-d/micme - Markdown: https://senad-d.github.io/portfolio/projects/micme-local-voice-to-text-pi-extension.md Built a local-first voice-to-text extension for Pi that records coding prompts, transcribes locally, and inserts reviewed transcripts into the editor. ## Problem Writing longer coding prompts in a terminal can interrupt flow, while cloud dictation tools add privacy concerns and extra moving parts. ## Approach Built MicMe as a Pi extension that records microphone input with ffmpeg, transcribes locally through whisper.cpp, Python Whisper, or a custom backend, and pastes the transcript into Pi for review before submission. Added configuration, device discovery, diagnostics, and npm publishing workflows so the package is practical to install and maintain. ## Result MicMe provides a local-first voice input workflow for coding prompts, letting users speak, review, and submit transcripts without leaving the Pi editor. ## Pi Code DevOps Automation Workspace - Slug: pi-code-devops-automation-workspace - Lane: personal - Status: in-progress - Period: May 2026 — Present - Stack: Pi, TypeScript, Node.js, AWS, YAML - Impact: Standardized multi-agent workflows for planning, implementation, QA, and documentation. | Improved operational safety with write guards, destructive-command blocking, and host allowlists. | Increased delivery speed with reusable chains, specialist agents, and deterministic utility tools. - Link (github): https://github.com/senad-d/pi-code - Markdown: https://senad-d.github.io/portfolio/projects/pi-code-devops-automation-workspace.md Built a project-local Pi workspace that combines agent orchestration, safety guardrails, and reusable skills for reliable automation. ## Problem Ad hoc automation workflows are difficult to scale safely when every task uses different prompts, tools, and execution patterns. ## Approach Created a DevOps-focused Pi workspace with custom extensions, agent teams, chain pipelines, and reusable skills. Added guardrails for filesystem writes and outbound hosts, plus utility tools for AWS docs lookup, concise summarization, commit generation, and token usage reporting. ## Result The workspace enables safer, repeatable, and auditable engineering workflows across planning, coding, QA, and documentation. ## Terraform Skills Bundle for Codex CLI - Slug: terraform-skills-codex-cli-bundle - Lane: personal - Status: in-progress - Period: Jan 2026 — Present - Stack: Terraform, AWS CLI, Bash, MCP, Codex CLI, LocalStack - Impact: Reduced repeated setup work with memory-bank bootstrap and reusable project rules. | Improved consistency through guided workflows for child modules, root modules, planning, and review. | Added AWS reporting coverage for cost, IAM, TLS, and network inventory. - Link (github): https://github.com/senad-d/terraform-skills - Markdown: https://senad-d.github.io/portfolio/projects/terraform-skills-codex-cli-bundle.md Created a reusable Codex CLI skill bundle to standardize Terraform planning, module delivery, review, and AWS reporting. ## Problem Terraform delivery quality often varies when teams rely on inconsistent templates, review depth, and planning habits. ## Approach Packaged opinionated Codex skills, scripts, and templates for memory bootstrap, Terraform planning, module creation, code review, and AWS account reporting, with MCP-aware context support. ## Result The bundle enables faster, more predictable Terraform and AWS delivery with shared standards, stronger validation gates, and less rework. ## Calm&Clear Serverless AWS Platform - Slug: calm-clear-serverless-platform - Lane: professional - Status: in-progress - Period: Nov 2025 — Present - Stack: Terraform, AWS Organizations, CloudFront, API Gateway, Lambda, DynamoDB, WAF, ECS, EC2, RDS, S3, SES - Impact: Established isolated development, staging, and production accounts to strengthen governance and release safety. | Replaced server-managed integration flows with API Gateway, Lambda, and DynamoDB to lower maintenance effort. | Improved payment and invoicing reliability with centralized API monitoring, logging, and tracing. - Link (github): https://calmclear.com/ - Markdown: https://senad-d.github.io/portfolio/projects/calm-clear-serverless-platform.md Built a secure multi-account serverless backend that reduced operational overhead and improved integration reliability. ## Problem The client needed a secure and scalable integration backend without adding long-term infrastructure overhead. ## Approach Implemented a multi-account AWS foundation and built a serverless integration layer on API Gateway, Lambda, and DynamoDB. Secured public entry points with WAF, custom domains, and Route 53 routing, then added centralized observability for API and function behavior. ## Result The platform now supports faster delivery, clearer environment boundaries, and a scalable integration architecture ready for additional business workflows. ## NeuroEAye Secure AWS Foundation - Slug: neuroeaye-secure-cloud-foundation - Lane: professional - Status: in-progress - Period: Apr 2025 — Present - Stack: AWS Organizations, AWS SecurityHub, Terraform, ECS, CloudFront, EFS, RDS, S3, Docker, CloudMap, GitHub Actions, CodePipeline - Impact: Reduced configuration drift by standardizing infrastructure provisioning with Terraform. | Improved release consistency through Dockerized workloads and automated pipelines. | Strengthened security posture across infrastructure and delivery workflows for healthcare use cases. - Link (github): https://neuroaeye.com/ - Markdown: https://senad-d.github.io/portfolio/projects/neuroeaye-secure-cloud-foundation.md Delivered secure, automated AWS infrastructure for healthcare workloads with repeatable CI/CD and lower release risk. ## Problem Healthcare-related applications required a secure and repeatable cloud foundation where reliability and controlled delivery were critical. ## Approach Automated AWS infrastructure provisioning with Terraform, containerized workloads with Docker, and implemented CI/CD pipelines with GitHub Actions and AWS CodePipeline. ## Result The project gained safer release workflows, consistent infrastructure delivery, and a cloud baseline ready for regulated growth. ## S3 Explorer Browser File Manager - Slug: s3-explorer-browser-file-manager - Lane: personal - Status: completed - Period: Feb 2025 — Apr 2025 - Stack: HTML, CSS, Amazon S3, AWS SDK for JavaScript v2 - Impact: Enabled direct S3 workflows in the browser, including browse, upload, download, move, and delete. | Improved maintainability by refactoring a single-file app into modular CSS and JavaScript assets. | Preserved security posture by keeping credentials in memory only and never persisting secrets. - Link (github): https://github.com/senad-dizdarevic-valcon/s3-explorer - Markdown: https://senad-d.github.io/portfolio/projects/s3-explorer-browser-file-manager.md Built a lightweight browser-only S3 manager with session-only credentials and no backend dependency. ## Problem Managing S3 objects often requires heavyweight tooling, while ad hoc scripts can be difficult for non-CLI users. ## Approach Implemented a browser-native S3 utility using AWS SDK v2 from a CDN, then expanded UX with breadcrumbs, filtering, previews, multipart uploads, bulk actions, and theme switching. ## Result The app delivers practical day-to-day S3 operations in a minimal interface with improved code structure and no server-side credential storage. ## Devbox Global Machine Bootstrap - Slug: devbox-global-conf-machine-bootstrap - Lane: personal - Status: completed - Period: Jan 2025 — Mar 2025 - Stack: Bash, Linux, macOS, Git - Impact: Reduced manual onboarding effort by automating baseline machine setup steps. | Standardized workstation provisioning across macOS and Linux with one entrypoint. | Improved setup reliability through explicit OS detection, logging, and error handling. - Link (github): https://github.com/senad-d/devbox-global-conf - Markdown: https://senad-d.github.io/portfolio/projects/devbox-global-conf-machine-bootstrap.md Automates fresh macOS and Linux workstation setup for DevOps tooling through a reusable shell bootstrap. ## Problem Setting up a new development machine repeatedly is slow and error-prone, especially across different operating systems. ## Approach Built a function-based shell bootstrap project that detects the host OS, installs required software, logs progress, and handles failures consistently. ## Result The project provides a repeatable, low-friction way to prepare DevOps workstations while reducing configuration drift between machines. ## UK Home Office DSP Serverless Delivery - Slug: public-sector-serverless-modernization - Lane: professional - Status: in-progress - Period: Nov 2024 — Present - Stack: AWS Lambda, API Gateway, CloudFront, RDS, S3, CloudWatch, GitHub Actions, Grafana - Impact: Accelerated release flow by automating quality checks, security scans, and deployments. | Improved operational transparency through CloudWatch and Grafana dashboards. | Supported secure, high-availability architecture patterns for critical public services. - Link (caseStudy): https://www.gov.uk/ - Markdown: https://senad-d.github.io/portfolio/projects/public-sector-serverless-modernization.md Contributed to high-assurance serverless AWS delivery, improving automation, observability, and governance in a public-sector program. ## Problem A large public-sector digital service required resilient cloud infrastructure with strong security controls and dependable deployment automation. ## Approach Worked in a global team to implement serverless AWS architecture using API Gateway, Lambda, Aurora, S3, and CloudFront. Strengthened CI/CD with GitHub Actions and expanded monitoring through CloudWatch and Grafana. ## Result The platform achieved more reliable releases, stronger governance controls, and clearer operational visibility across distributed teams. ## Personal Observability Engineering Lab - Slug: devops-observability-lab - Lane: personal - Status: in-progress - Period: Jun 2024 — Present - Stack: Grafana, Loki, Prometheus, Tempo, OpenTelemetry, Docker - Impact: Tested dashboard and alerting patterns in a safe environment before applying them to client systems. | Improved troubleshooting workflows through end-to-end log, metric, and trace correlation. | Reduced rollout risk by validating runbooks against realistic telemetry scenarios. - Link (github): https://github.com/senad-d - Markdown: https://senad-d.github.io/portfolio/projects/devops-observability-lab.md Built a personal observability sandbox to validate logs, metrics, and tracing patterns before production rollout. ## Problem Experimenting directly in production observability environments is costly and risky, especially when testing alerting and correlation changes. ## Approach Built a local lab stack with Grafana, Loki, Prometheus, Tempo, and OpenTelemetry to prototype dashboards, alerts, and trace-to-log workflows under repeatable test conditions. ## Result The lab serves as a reliable proving ground for observability decisions, improving confidence and reducing risk before production rollout. ## Docker Compose Remote Control API - Slug: docker-compose-remote-control-api - Lane: personal - Status: completed - Period: Jun 2024 — Aug 2024 - Stack: Python, Flask, Docker Compose, Gunicorn, Nginx, JWT - Impact: Enabled secure remote control of auxiliary container services through REST endpoints. | Protected command execution with JWT-based authentication and authorization. | Simplified operations with containerized deployment and clear API/Gunicorn/Nginx log paths. - Link (github): https://github.com/senad-d/DockerComposeAPI - Markdown: https://senad-d.github.io/portfolio/projects/docker-compose-remote-control-api.md Developed a Dockerized Flask API behind Gunicorn and Nginx for authenticated remote docker-compose operations. ## Problem Operating occasional infrastructure services on remote hosts is inconvenient when shell access is the only control path. ## Approach Built a REST API with login and command endpoints, constrained execution to docker-compose commands, and packaged the service as Flask + Gunicorn behind Nginx. ## Result Operators can trigger compose workflows from external tools (for example Grafana buttons) without exposing full interactive shell access. ## Typla.nl AWS Reliability & Support Program - Slug: typla-aws-maintenance-support - Lane: professional - Status: in-progress - Period: Feb 2024 — Present - Stack: Terraform, AWS Organizations, OpenTelemetry, Lambda, AWS EC2, AWS ECS, Cognito, S3, CloudFront, SES, SNS, SQS, WAF, CloudMap, CodePipeline, Jenkins, Ansible - Impact: Strengthened governance and security across shared multi-account AWS environments. | Improved deployment consistency across client applications with standardized CI/CD workflows. | Reduced infrastructure drift by managing platform changes through Terraform. - Link (live): https://www.typla.nl/ - Markdown: https://senad-d.github.io/portfolio/projects/typla-aws-maintenance-support.md Improved stability, security, and delivery predictability across multi-client AWS environments through IaC and pipeline standardization. ## Problem A mixed client portfolio running on EC2 and ECS created operational complexity around reliability, governance, and consistent delivery. ## Approach Focused on infrastructure hardening and optimization across AWS accounts while improving release workflows with CodePipeline, Jenkins, Ansible, and GitHub-based version control. Standardized infrastructure change management through Terraform. ## Result The environment became easier to operate and scale, with clearer account boundaries, stronger delivery consistency, and lower operational risk. ## Lundbeck Batch Tracking AWS Launch - Slug: lundbeck-batch-tracking-platform - Lane: professional - Status: completed - Period: Oct 2023 — Dec 2023 - Stack: AWS ECS, AWS CloudFront, AWS CodePipeline, Terraform - Impact: Delivered a production-ready cloud environment aligned with launch milestones. | Improved frontend delivery performance through CloudFront edge distribution. | Ensured stable backend operations with an ECS-based architecture. - Link (caseStudy): https://www.lundbeck.com/ - Markdown: https://senad-d.github.io/portfolio/projects/lundbeck-batch-tracking-platform.md Delivered production AWS infrastructure under launch deadlines, combining ECS reliability with CloudFront performance gains. ## Problem A newly developed batch-tracking application required secure and dependable AWS infrastructure before release. ## Approach Implemented an ECS-centered backend architecture and configured CloudFront for frontend delivery performance, using infrastructure patterns focused on reliability, maintainability, and predictable operations. ## Result The application launched on a stable cloud foundation with consistent backend behavior and improved end-user delivery performance. ## Construction Site Inventory AWS Launch Foundation - Slug: construction-site-inventory-cloud-foundation - Lane: professional - Status: completed - Period: Aug 2023 — Sep 2023 - Stack: AWS ECS, AWS S3, AWS CloudFront, Terraform, IAM - Impact: Provisioned separate development and production environments from day one. | Secured static asset delivery using private S3 origins behind CloudFront. | Delivered an ECS backend foundation aligned with reliability and budget constraints. - Link (caseStudy): https://www.linkedin.com/in/senad-dizdarevic-devops - Markdown: https://senad-d.github.io/portfolio/projects/construction-site-inventory-cloud-foundation.md Delivered a secure, cost-aware AWS launch baseline with private asset delivery and resilient container services. ## Problem The client needed a practical AWS baseline for a new product with clear environment separation and controlled access to stored assets. ## Approach Provisioned development and production infrastructure in a new AWS account, delivered frontend assets through CloudFront with private S3 origins, and deployed backend services on ECS using high-availability design principles. ## Result The team received a stable and maintainable cloud setup that balanced security, cost, and scalability for early product growth. ## YouChooseWork AWS Launch Infrastructure - Slug: youchoosework-ecs-cloudfront-platform - Lane: professional - Status: completed - Period: Mar 2023 — Apr 2023 - Stack: AWS ECS, AWS CloudFront, Terraform, AWS CloudWatch, SNS - Impact: Delivered a production-ready backend environment on a highly available ECS architecture. | Improved user-facing performance with CloudFront distribution. | Accelerated launch readiness with repeatable infrastructure provisioning patterns. - Link (live): https://youchoosework.com/ - Markdown: https://senad-d.github.io/portfolio/projects/youchoosework-ecs-cloudfront-platform.md Designed and delivered launch-ready AWS infrastructure balancing performance, reliability, and long-term maintainability. ## Problem The platform needed dependable AWS infrastructure to support launch goals while maintaining performance and operational stability. ## Approach Designed and provisioned AWS resources for backend and frontend delivery, using ECS for service resilience and CloudFront for low-latency content distribution. ## Result The product launched on a cloud setup that balanced reliability, performance, and maintainability for ongoing growth. ## Compli AWS Observability Baseline - Slug: aws-observability-platform - Lane: professional - Status: completed - Period: Feb 2023 — Feb 2023 - Stack: AWS CloudWatch, Grafana, InfluxDB, Telegraf, Slack, SNS - Impact: Centralized CloudWatch telemetry into shared Grafana dashboards used across workloads. | Introduced Slack-routed alert workflows with clearer ownership and faster first response. | Extended diagnostic depth by combining CloudWatch with InfluxDB and Telegraf metrics. - Link (caseStudy): https://www.compli.nl/ - Markdown: https://senad-d.github.io/portfolio/projects/aws-observability-platform.md Unified AWS monitoring into a shared observability baseline that improved alert quality and sped up incident triage. ## Problem Monitoring was fragmented across services, slowing incident triage and reducing confidence in alerts. ## Approach Designed a centralized observability layer with CloudWatch as the primary source and Grafana as the shared visualization surface. Added InfluxDB and Telegraf for deeper telemetry coverage, then connected alerting to Slack support channels for faster team response. ## Result Teams moved to a consistent monitoring model with clearer alert ownership, less noisy escalation, and a faster path from detection to resolution. ## Nebula Internal EKS Platform Enablement - Slug: nebula-eks-platform-foundation - Lane: professional - Status: in-progress - Period: Feb 2023 — Present - Stack: AWS EKS, Terraform, Kubernetes, AWS Networking, GitHub Actions, OpenVPN - Impact: Standardized baseline infrastructure patterns for new internal development projects. | Improved consistency and repeatability through Terraform-driven provisioning. | Reduced setup time for teams launching new platform workloads. - Link (caseStudy): https://www.linkedin.com/in/senad-dizdarevic-devops - Markdown: https://senad-d.github.io/portfolio/projects/nebula-eks-platform-foundation.md Helped standardize internal EKS platform provisioning, improving environment consistency and onboarding speed for teams. ## Problem Internal teams needed a dependable AWS platform baseline to avoid repeated manual setup and inconsistent environment quality. ## Approach Contributed to an internal EKS platform initiative that provisions core infrastructure with Terraform, with emphasis on repeatability, resilient networking, and operational consistency. ## Result Teams gained a predictable platform foundation that shortened project startup time and improved long-term maintainability. ## Office Reservation Manager AWS Delivery Baseline - Slug: office-reservation-manager-delivery-environment - Lane: professional - Status: completed - Period: Dec 2022 — Jan 2023 - Stack: AWS CloudFormation, GitHub Actions, Mendix, ECS, EFS, RDS - Impact: Delivered a ready-to-use development environment for application teams. | Reduced manual provisioning work through CloudFormation automation. | Improved CI reliability with repeatable GitHub Actions workflows. - Link (caseStudy): https://www.linkedin.com/in/senad-dizdarevic-devops - Markdown: https://senad-d.github.io/portfolio/projects/office-reservation-manager-delivery-environment.md Automated Mendix environment provisioning and CI workflows to reduce setup effort and improve release consistency. ## Problem The team needed a dependable development environment for a Mendix application with minimal setup friction and repeatable delivery steps. ## Approach Implemented infrastructure provisioning through AWS CloudFormation and standardized CI pipeline execution with GitHub Actions. ## Result Environment setup became faster and more reliable, enabling smoother day-to-day development and release preparation.