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Platforms that scale
Enterprise application and container platforms for Telkomsel: designing how applications are deployed, scheduled, discovered, secured and operated at scale.
I turn complex technology challenges into solutions that work.
From platform architecture to AI-driven operations, I design, build, and deliver enterprise solutions proven in production at Telkomsel.
A solution architect and technology builder connecting platform engineering, AI and enterprise operations from architecture to production.
01 — Proven in production
Hours to seconds
to identify infrastructure asset ownership
Every alert accounted for
through centralized visibility, ownership and acknowledgement SLAs
Since 2022
across enterprise operations, software development and platform engineering
In production daily
enterprise solutions supporting engineers and operational stakeholders
02 — What I design
I connect technology, product thinking and operational realities to build solutions that solve real problems. Three disciplines, designed to work together.
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Enterprise application and container platforms for Telkomsel: designing how applications are deployed, scheduled, discovered, secured and operated at scale.
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Turning fragmented monitoring, infrastructure and asset data into unified operational systems, with automation and AI-assisted intelligence.
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Turning ideas and operational requirements into working products through architecture, engineering, automation and continuous enablement.
03 — Selected work
Enterprise platforms, operational transformation and AI-enabled solutions built around real challenges at Telkomsel, alongside independent product development. Each one: challenge, solution, impact.
01 · Platform
Engineering a standardized foundation for running applications at enterprise scale.
steps = manual
A business-critical platform operated by a lean L1 / L2 team. Application onboarding was inconsistent, while platform upgrades and maintenance relied heavily on manual execution.
Establishing a consistent operating and engineering model across Nomad, Consul, Vault and MinIO: application onboarding standards for teams adopting Nomad and Consul service mesh, Ansible + GitLab CI automation for provisioning, upgrades and maintenance, and standardized Vault and storage patterns for secrets, certificates and buckets.
Reduced upgrade execution from weeks of manual coordination and work to minutes through automation. Established repeatable workflows and more consistent application onboarding.
02 · Operations
Turning fragmented monitoring and asset data into a unified operational system, with structured alert ownership and acknowledgement SLAs.
01 · Challenge
02 · Insight
More tools didn't mean better operations.
The underlying problem was structural. Monitoring, inventory and operational workflows existed independently, without a unified system connecting the information to the people responsible for acting on it.
03 · Solution
Enterprise operations platform · Server topology
Logical server roles. Sizing, redundancy and network segmentation vary per environment.
Illustrative only. Not a deployment topology.
A centralized ingestion pipeline that receives and normalizes alerts and metrics from multiple enterprise monitoring platforms. Alerts become traceable operational records with defined ownership and acknowledgement SLAs.
A consolidated source of truth for infrastructure assets, bringing existing records into a searchable and structured inventory.
An AI-assisted operational platform built for Telkomsel, bringing infrastructure visibility, asset management, alert workflows and operational intelligence into one connected environment. In production since September 2026.
04 · Delivery
Delivered through independently usable capabilities, allowing asset inventory and operational workflows to provide value while monitoring integrations and AI capabilities continued to evolve.
05 · Impact
Hours to seconds
Identifying who owns an infrastructure asset used to require hours of manual lookup. A centralized inventory reduced that process to seconds.
03 · AI
Bringing AI closer to enterprise operational data, workflows and decision-making.
Enterprise AI needs more than a language model. It needs access to relevant operational context, integration with existing systems, and an architecture that respects enterprise security and infrastructure constraints.
Designing AI-enabled operational capabilities around LLM agents, retrieval-augmented generation, MCP integrations and connected workflows. Exploring local and on-premise LLM architecture to support enterprise-controlled AI environments.
AI-enabled capabilities delivered as part of an operational solution in production, supporting operational stakeholders from engineers to executive-level users.
04 · Practices
Building the standards, technical knowledge and operating models that help teams sustain what they deliver.
Critical operational knowledge and troubleshooting practices were concentrated among a limited number of engineers.
Developing SOPs for platform operations and incident handling, conducting root-cause analyses with actionable follow-ups, coaching L2 engineers, establishing technical ownership across expertise areas, and contributing to team structure and operational capacity planning.
More consistent operations, clearer technical accountability and stronger knowledge transfer across engineering levels.
05 · Founder
An independent technology venture and engineering lab, developed from product concept to working systems.
Turning an idea into a sustainable digital learning platform while building the engineering foundation to develop and operate products independently.
Owning the full product and engineering lifecycle: product direction → software architecture → application development → CI/CD → infrastructure → deployment → monitoring → incident response.
Built an end-to-end product and engineering ecosystem through Lore Up and Lore Up Lab, combining product development with hands-on infrastructure and software engineering.
04 — How I work
Understand the problem, architect the solution, build it, and prove it in production.
Start with the people, processes and operational realities behind the requirement.
Identify what is broken beneath the symptoms.
Connect business needs, technical design and operational ownership.
Deliver working capabilities, validate them and measure the outcome in production.
Automation, documentation, coaching and continuous improvement.
05 — The path behind the work
Different environments shaped the way I approach technology: from software development and infrastructure operations to platform engineering, solution architecture and technical leadership.
06 — Toolbox
HashiCorp Nomad · Consul · Vault · MinIO · Terraform · API gateways
Ansible · GitLab CI · Jenkins · infrastructure as code · pipeline design
Grafana · Loki · Prometheus · vROps · Zabbix · Dynatrace · alert pipelines
LLM agents · RAG · MCP integrations · AI workflow design · local / on-premise LLM architecture
Go · Laravel · Express.js · REST APIs · ClickHouse · PostgreSQL
Vue.js 3 · Svelte · Vite · Tailwind CSS
07 — Recognition & credentials
08 — Contact
Logical server roles. Sizing, redundancy and network segmentation vary per environment.