System Status: Operational

I build software like it is meant to survive production.

Mission Control presents how I design, ship, monitor, and improve systems with reliability-first engineering habits.

View Deployments Open Runbook

Engineer: Rashedul Hasan Sojib
Role: Software Engineer | DevOps Enthusiast
Uptime: 99.9% curiosity-driven
Current Focus: Cloud infrastructure, automation, and scalable applications.

mission@control:~

$boot: mission-control v1.2.0

$init: loading profile modules...

$ok: deployments indexed (3 services)

$ok: incident ledger mounted (3 records)

$ok: observability stream connected

$hint: run `help` to list available commands

Currently learning: distributed tracing patternsExperimenting with: cost-aware cloud architectureImproving: CI signal quality and flaky test reductionReading: incident response and reliability case studiesCurrently learning: distributed tracing patternsExperimenting with: cost-aware cloud architectureImproving: CI signal quality and flaky test reductionReading: incident response and reliability case studies

Control Layer

Deployments

Projects reframed as operational services with environment and health metadata.

ServiceAtlas

Environment: Production

Healthy

Next.jsNode.jsPostgreSQLDocker

Latency: 184ms
Logs: Automates user onboarding and account provisioning workflows.
Who It Serves: Operations-heavy teams with frequent account setup requests.
Challenge Solved: Removed bottlenecks from manual approval and setup pipelines.
Links: Source Notes

AlertBridge

Environment: Open Source

Monitoring

NestJSRedisPrometheusGrafana

Latency: 235ms
Logs: Routes and enriches multi-channel incident alerts with context.
Who It Serves: Teams managing multiple service owners and noisy alert streams.
Challenge Solved: Lowered alert fatigue by grouping and prioritizing notifications.
Links: Source

DeployBeacon

Environment: Lab

Scaling

TypeScriptGitHub ActionsTerraformAzure

Latency: 310ms
Logs: A release assistant that validates infra and deployment readiness.
Who It Serves: Small product teams shipping fast with limited DevOps bandwidth.
Challenge Solved: Surfaced configuration drift before release windows.
Links: Source

Control Layer

Infrastructure Layers

A stack view of application, cloud, CI/CD, and observability capabilities.

Application Layer
Builds resilient product interfaces and backend APIs.
ReactNext.jsNode.jsTypeScript
CI/CD Layer
Automates build, test, and deployment with guardrails.
GitHub ActionsGitLab CIJenkins
Container Layer
Packages and orchestrates services for reliable delivery.
DockerKubernetes
Cloud Layer
Deploys and operates cloud-native infrastructure.
AWSAzureGCP
IaC Layer
Codifies infrastructure to reduce drift and manual errors.
TerraformAnsible
Observability Layer
Tracks service health, performance, and incidents.
PrometheusGrafanaELK

Control Layer

Incident Reports

Postmortem-style snapshots that show debugging maturity and reliability mindset.

INC-003: CI pipeline failures due to environment drift

Resolved

Build Success Rate

Before

63%

After

96%

What Broke: Builds passed locally but failed unpredictably in CI.
Why It Mattered: Release cadence slowed and confidence in delivery dropped.
Root Cause: Toolchain version mismatch across local and CI runners.
Fix: Containerized the build environment and pinned dependencies.
Prevention: Added environment parity checks before merge.

INC-006: Latency spike during high-traffic login window

Monitoring

Auth API p95

Before

890ms

After

270ms

What Broke: Authentication API crossed response-time SLO during peak hour.
Why It Mattered: User onboarding dropped when login became unreliable.
Root Cause: An uncached permissions lookup was called on every request.
Fix: Added short-lived cache and query optimization with indexes.
Prevention: Introduced latency budget alerts per endpoint.

INC-009: Missed alerts from webhook retry storm

Closed

Duplicate Alert Volume

Before

4.6x baseline

After

1.2x baseline

What Broke: Duplicate retries overwhelmed notification channels.
Why It Mattered: Real incidents were buried under noisy alerts.
Root Cause: No idempotency key handling in webhook processor.
Fix: Implemented idempotency keys and backoff-aware queuing.
Prevention: Added chaos test for duplicate-delivery scenarios.

Control Layer

Observability Metrics

Static baseline blended with live GitHub-derived signals when available.

Repos Deployed

Production, staging, and open-source services shipped.

Cloud Services Used

Managed services currently used across app and platform workflows.

Pipelines Built

CI/CD pipelines with quality gates and rollout checks.

Bugs Closed

190

Issues resolved across app, infra, and developer tooling.

Automations

Repeatable workflows created to reduce operational toil.

Learning Streak

42days

Current continuous learning and experimentation streak.

Years Learning

6yrs

Continuous software engineering and systems learning journey.

Architecture Blueprint

How software delivery, observability, and reliability decisions connect across the stack.

Delivery Flow

Pull request checks enforce lint, type-safety, and formatting.
Staging deploy validates runtime env and infrastructure assumptions.
Production rollout uses guarded releases with rollback readiness.

Diagram of metrics, logs, and alert feedback loops

Observability Baseline

Service-level metrics with latency and error budget monitoring.
Structured logs for incident traceability and postmortem quality.
Alert thresholds tuned to reduce noise and improve response time.

Diagram of infrastructure as code, hardening cycles, and runbooks

Reliability Practices

Infrastructure as code to prevent manual drift.
Incremental hardening based on recurring failure patterns.
Operational runbooks documented for repeatable incident handling.