Hello, I'm Amirudin Hamzah

I build and lead the platforms behind critical software.

Lead DevOps / SRE / Platform Engineer

Hands-on DevOps, SRE, and Platform Engineering leader with 8+ years of experience across software engineering, cloud infrastructure, Kubernetes, CI/CD, observability, production reliability, and security compliance.

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  • 7
    Products
  • 15
    GKE clusters
  • ~~50
    GCP projects
  • 100K+K+
    Users
  • 1M+M+
    Transactions / day
  • ~IDR 1BB
    Annual cloud savings

About

From writing software to engineering the platform it runs on.

Amirudin Hamzah is a hands-on DevOps, SRE, and Platform Engineering leader with more than 8 years of experience across software development, cloud infrastructure, Kubernetes, CI/CD, observability, reliability engineering, and security compliance.

His career began in software engineering, building backend and full-stack applications using PHP, Node.js, and Go. That software background became a foundation for understanding not only infrastructure, but also the applications and developers that depend on it.

Today, he leads DevOps and SRE engineering at PT Bimasakti Multisinergi, directly reporting to the CTO.

Today, the role combines

  • Technical Leadership
  • Architecture
  • Hands-On Engineering
  • Production Reliability
  • Business Impact

From code to leadership

  1. 01Software
  2. 02Infrastructure
  3. 03Cloud
  4. 04Kubernetes
  5. 05SRE
  6. 06Leadership

Current Scale

The platform I help operate.

Seven products, ~50 developers, 15 clusters, 100K+ users — the numbers Amirudin’s team carries. Hover the system or use the list; every node explains what it means in practice.

AmirudinDevOps Supervisor5Engineers7Business products~50Developers~50GCP projects15GKE clusters100K+Users1M+Transactions / day500–700RPS
  • Hover the system, or select a domain

    Experience

    The evolution of an engineer.

    1. 2015CODE

      Backend Engineering

      Started in software engineering — building backend systems in PHP and learning what production code needs to survive.

    2. 2017WEB

      Full-Stack Development

      Expanded across the stack with Node.js and JavaScript — shipping complete products and taking responsibility for how they ran.

    3. 2019SERVERS

      Infrastructure & Compliance

      Crossed from code to infrastructure: servers, virtualization, security standards, and compliance audits — ISO/IEC 27001 and PCI-DSS.

    4. 2022CONTAINERS

      DevOps Supervision

      Began leading DevOps and SRE at PT Bimasakti Multisinergi — a 5-person team, direct to the CTO, across products and projects.

    5. 2024CLOUD

      Cloud Optimization

      Drove the platform's cloud transformation and cost program — from on-premises to GCP, from ~IDR 5B to ~IDR 4B annual cloud spend.

    6. 2026AI OPS

      AI-Assisted Operations

      Turning operational conversations into engineering knowledge: AI-assisted automation, knowledge retrieval, and faster resolution.

      Present

    System eras

    Now — reporting to the CTO

    PT Bimasakti Multisinergi

    DevOps Supervisor · Aug 2022 – Present

    Hands-on technical leader responsible for DevOps, SRE, cloud platform, production infrastructure, observability, reliability, and engineering operations. Lead a 5-person engineering team supporting 7 business products, ~50 developers, ~50 GCP projects, 15 GKE clusters, and hundreds of applications and microservices.

    Responsibility layers

    • Lead and grow a 5-person DevOps / SRE engineering team.
    • Partner with the CTO on platform architecture and infrastructure strategy.
    • Serve ~50 developers across 7 product teams as their platform organization.
    • Recruit, mentor, and raise the team's operating bar.

    Impact

    The work, measured.

    A platform is only as convincing as the outcomes behind it. Four chapters — spend, transformation, reliability, operations — each one an engineering decision that produced a number the business can feel.

    Impact · FinOps

    ~IDR 1B saved every year.

    Annual cloud expenditure reduced from approximately IDR 5 billion to IDR 4 billion — a ~20% reduction sustained through systematic FinOps, not one-off cuts.

    Context matters: spend reduction came from measured usage, workload placement, commitment planning, and commercial review — not from starving environments of capacity.

    • Rightsizing
    • Workload consolidation
    • Kubernetes clusterization
    • Spot VMs
    • Committed Use Discounts
    • Resource segmentation
    • Billing optimization
    • Partner negotiation

    Impact · Cloud Transformation

    From on-premises infrastructure to Google Cloud.

    A full platform migration: ~80 VMs and 6 databases out of a hardware-constrained data center, into a containerized, observable, cloud-native operating model.

    Impact · Reliability

    Built around business-critical reliability.

    Operating against a 99.9% organizational platform SLA target — with a defined tolerance of ~5 minutes of unplanned downtime — across platforms carrying 100K+ users, 500–700 RPS, and 1M+ transactions a day.

    • ~5 minDefined unplanned downtime tolerance
    • 100K+Users
    • 500–700RPS
    • 1M+Transactions / day

    Reliability is an operating discipline here: SLO thinking, staged rollouts, incident response, and post-incident learning keep the platform inside its tolerance — not a single-number promise.

    Impact · AI-Assisted Operations

    Turning operational conversations into engineering knowledge.

    Engineering operations transformation through AI-assisted automation and knowledge reuse — not an AI product. Operational signals that once lived in chat now flow through an automated pipeline and return as retrievable engineering knowledge.

    • 100%

      Manual WhatsApp monitoring eliminated

      Engineers no longer watch chat channels for operational signals — the pipeline does.

    • ~90%

      Engineering workload focused on technical engineering

      The operational loop that consumed attention now runs automatically.

    1. Signal

      WhatsAppOperational messages
    2. Automation

      n8nAutomation workflow
    3. Understanding

      Vertex AIUnderstanding & triage
    4. State

      PostgreSQLStructured state
    5. ResolutionAction taken
    6. Memory

      QdrantVector knowledge
    7. Reuse

      Knowledge RetrievalAnswers for future issues
    8. Reuse

      Future issuesRetrieved answers short-circuit re-investigation

    Those outcomes run on an architecture — explore the stack that carries them.

    Architecture

    The platform, drawn as layers.

    Not a system diagram of a data center — the operating model of a platform: what carries traffic, where workloads run, what holds state, and how every layer reports. Sanitized and conceptual; explore it like a system.

    Drag to pan · scroll or +/− to zoom · hover a node for its links · click for context

    100%

    Users

    The people and clients of the products on the platform.

    Edge / Ingress

    The single front door for external traffic into the platform.

    Kubernetes

    Where applications and services run: GKE, segmented by workload domain.

    Data / Services

    The state layer: databases, queues, and storage the platform runs on.

    Observability

    Metrics, logs, APM, and security signals from every layer.

    Alerting

    Where signals become attention — routed to the channels engineers actually watch.

    6 conceptual layers · 14 systems — sanitized view, no internals. Hover a system to trace its links.

    1. Where applications and services run: GKE, segmented by workload domain.

    Observability

    Every layer reports to one place.

    Workloads

    ApplicationsServicesAPIs

    Signals

    Metrics→ PrometheusLogs→ ElasticsearchAPM→ APM SystemSecurity→ Wazuh
    Grafana

    Channels

    WhatsAppSlackTelegram

    Skills

    Nine disciplines around one center.

    Tools rotate; the disciplines they serve are the stable part. This is the working toolkit behind each capability — the stacks I run, not a rating of myself.

    Center of gravity

    Platform Engineering

    01 / 09

    Cloud

    • Google Cloud Platform
    • Compute Engine
    • GKE
    • Networking
    • IAM & Segmentation
      • Google Cloud Platform
      • Compute Engine
      • GKE
      • Networking
      • IAM & Segmentation

    Work

    Three cases, one operating model.

    Platform-level work, each with its own full case study: what the problem was, how it was engineered, and what measurably changed.

    Leadership

    Lead from the architecture, not just the meeting room.

    Technical leadership shows up in what the platform can do without supervision — in alerts that carry context, in capacity that scales before it pages, in knowledge that outlives a single conversation. Five principles guide how I work.

    Stay Hands-On

    Technical leadership remains connected to production systems and real engineering challenges.

    Build Leverage

    Automation, platforms, standards, and knowledge systems should multiply engineering capability.

    Reliability Is a Product Feature

    Infrastructure exists to enable reliable business outcomes.

    Measure Impact

    Engineering decisions should improve reliability, delivery speed, scalability, cost efficiency, operational efficiency, and risk reduction.

    Bridge Business & Engineering

    Translate organizational objectives into technical priorities and architecture.

    Foundation

    Where the engineering story started.

    Universitas Muhammadiyah Sidoarjo

    Bachelor of Information Technology

    GPA 3.4 · Outstanding Graduate with two national achievements.

    SMKN 2 Buduran Sidoarjo

    Software Engineering

    Vocational secondary — where the engineering story started.

    Recognition

    2nd Awardee

    Two-time national awardee, 2018 – 2019.

    UNESA National Web Design Championship

    Contact

    Let's build somethingreliable.

    Open to conversations around Lead DevOps, Senior Cloud Engineering, SRE, Platform Engineering, Cloud Infrastructure, and technical infrastructure leadership.