We build the systems — and the tools — others say can't be built.
Arkynate Labs is a one-operator studio shipping its own engineering tools and taking on the hard backend, data, and integration work behind mid-to-large platforms. Bottleneckers and PingOps are live. More are in the forge.
Studio Readout LIVE
The Arsenal
LiveBottleneckers
Drop services onto a canvas, simulate traffic, and watch where the architecture breaks — retry storms, latency cascades, saturation. A visual playground for stress-testing designs before they hit production.
LivePingOps
A fast, no-fuss uptime monitor that lives on your iPhone. Add any public URL — your website, your team's API, the AI service your tools depend on. Local checks are free + on-device; opt into Cloud monitoring (Sign in with Apple) so checks keep running while your phone sleeps.
Capabilities
Systems Architecture
Distributed systems, event-driven design, multi-tenant SaaS, and enterprise integration — built to stay correct and available under real load.
Data & Integration
CDC pipelines, zero-downtime migrations, legacy bridges, and SOAP/REST adapter layers — scoped against outcomes, shipped with runbooks.
AI Systems
AI-augmented delivery, LLM tooling, agentic workflows, and applied ML — clear architecture in, dependable intelligence out.
Strategy & Enablement
Architecture reviews, ADR libraries, team enablement, and technical leadership — leaving the team stronger than I found it.
Battle Log
legendaryGENERALIZEDPatient-care CMS through the utilization ceiling · MongoDB ReplicaSet → Atlas Sharded Cluster
Solo migration of a vendor-locked clinic CMS off a saturated single ReplicaSet onto a horizontally scalable Sharded Cluster. Profiled the live workload, picked the shard key off real query shapes, fixed a misconfigured Azure network path along the way, rehearsed the cutover twice — patient services never went offline.
epicGENERALIZEDBooking path under the second barrier · sub-1s P99 across 300+ partner integrations
Profilers, execution plans, and traces on a high-traffic booking flow. Query shapes rewritten, N+1s eliminated, caches placed where the data actually allowed it — P99 brought under one second without dropping a single integration.
epicIN-HOUSEPingOps shipped to the App Store · uptime monitoring with cloud coverage
Forged in-house and shipped solo: an iOS uptime monitor with public status pages and cloud-side checks. Design, backend, client, and store release — one operator, end to end.
rareGENERALIZEDEnterprise architecture for a 2M+ member platform
Integration architecture, cloud stack selection, and an ADR library that outlived team rotations. Plus the training programme that levelled up every application engineer in the org.
rareIN-HOUSEBottleneckers live · visual bottleneck simulation for distributed systems
Drag-and-drop service topologies, client-side load simulation, utilization heatmaps, and critical-path analysis — systems intuition, playable in the browser.
rarePRE-STUDIOPro StarCraft player & team captain · Mineski
Map awareness, build orders, APM under pressure, and post-game analysis as a discipline. The strategic instincts behind every system Arkynate ships were forged here first.
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Engagement records sealed pending NDA generalization. Numbers verified, names redacted. Check back — entries are unsealed as clearance allows.
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Engagement records sealed pending NDA generalization. Numbers verified, names redacted. Check back — entries are unsealed as clearance allows.
The Operator
Jose Paolo Javier
// Attributes
// Traits & perks
Full-Stack Systems
Architecture
Engineering
AI
Strategy- Full-Stack Systems (STUDIO · CORE, 10 YRS) — Kotlin LV9, Java LV9, Spring Boot LV9, TypeScript LV8, React LV8, AWS LV8 — Four domains, each battle-tested in a real production system. This is the surface area Arkynate can engineer against.
- Distributed Systems (ARCHITECTURE · LV 9, 8 YRS) — Kafka LV9, MongoDB LV8, Kubernetes LV8, Docker LV8 — Systems that stay correct and available across nodes, regions, and failure modes. Consistency, partitioning, and the trade-offs that bite in production.
- Event-Driven Arch (ARCHITECTURE · LV 8, 6 YRS) — Kafka LV9, Debezium LV8, CDC Pipelines LV8, Idempotent Consumers LV8 — Kafka, CDC, exactly-once delivery, and service choreography that never blocks. Ordering and idempotency as first-class design.
- Multi-Tenant SaaS (ARCHITECTURE · LV 8, 4 YRS) — PostgreSQL LV8, Flyway LV8, Spring Security LV8, JWT Auth LV8 — Tenant isolation, scoped data access, and per-tenant config as foundations — not retrofits.
- Enterprise Architecture (CAPSTONE · LV 10, 5 YRS) — Integration Patterns LV9, Cloud Architecture LV9, AWS LV8, Azure LV7 — Integration architecture, cloud stack selection, ADR libraries, and enablement for a platform serving 2M+ members.
- Backend APIs (ENGINEERING · LV 9, 10 YRS) — Kotlin LV9, Java LV9, Spring Boot LV9, REST Design LV9, WebSocket / STOMP LV7 — Java/Kotlin Spring REST APIs across web, mobile, and partner clients — to a standard that survives real traffic.
- Performance Eng (ENGINEERING · LV 9, 5 YRS) — JVM Profiling LV9, SQL Tuning LV9, Distributed Tracing LV8, Load Testing LV8 — Profilers, execution plans, traces. Took a booking path to sub-1s P99 across 300+ integrations.
- CDC & Pipelines (ENGINEERING · LV 8, 4 YRS) — Debezium LV8, Kafka Connect LV8, MongoDB LV8, PostgreSQL LV8 — Debezium-sourced capture, ordered streams, idempotent sinks. Sub-100ms sync across heterogeneous DBs.
- Zero-Downtime Migration (CAPSTONE · LV 9, 3 YRS) — MongoDB Atlas LV9, Shard-Key Design LV8, Dual-Write Cutover LV9, Azure Networking LV7 — On-prem → managed sharded cluster with zero downtime. Dual-write, rehearsed cutover, tested rollback.
- AI-Augmented Dev (AI · LV 8, 2 YRS) — Claude Code LV9, Agent Orchestration LV8, AI Code Review LV8 — Frontier tooling as a senior-engineer force multiplier — search, refactor, tests, docs. One human at small-team velocity.
- LLM Tooling (AI · LV 7, 2 YRS) — Anthropic API LV8, Structured Output LV8, Prompt Caching LV7, Evals LV7 — Building with LLM APIs: prompt architecture, structured output, evals, and guardrails for trustworthy systems.
- Agentic Workflows (AI · LV 7, 1 YR) — Multi-Agent Pipelines LV7, Tool Use LV8, Workflow Orchestration LV7 — Multi-step agent loops wired into real delivery pipelines. AI amplifies intent — it never replaces it.
- Applied ML Systems (CAPSTONE · LV 7, 2 YRS) — Model Serving LV7, Feature Pipelines LV7, ML Observability LV7 — ML-powered architecture that learns and scales — model serving, feature pipelines, and the observability to keep them honest.
- Systems Thinking (STRATEGY · LV 9, 15 YRS) — StarCraft II LV10, Trade-off Analysis LV9, Post-Mortems LV9 — Forged as a pro StarCraft player and captain at Mineski: map awareness, build orders, post-game analysis as improvement.
- ADRs & Docs (STRATEGY · LV 8, 6 YRS) — ADR Libraries LV9, Runbooks LV8, C4 / Architecture Diagrams LV8, Confluence LV8 — Documentation as the memory of a system. ADR libraries that outlive team changes.
- Team Enablement (STRATEGY · LV 8, 5 YRS) — Training Programmes LV8, Mentorship LV8, Code Review Culture LV9 — Ran the training programme for all IT application engineers at an enterprise. Leave the team stronger.
- Technical Leadership (CAPSTONE · LV 9, 5 YRS) — Stack Selection LV9, Technical Roadmapping LV8, Stakeholder Comms LV8 — Lead Developer → Enterprise Architect. Setting direction, selecting stacks, owning the call.
- Map Awareness (innate trait) — Pro-gamer instinct — sees the whole system, not just the ticket. Reads second-order effects before they land.
- Zero-Downtime Nerve (innate trait) — Runs live cutovers and migrations without flinching — because the rollback is rehearsed and tested.
- Documentarian (innate trait) — Leaves ADRs and runbooks behind. The team is stronger after the engagement than before it.
- Async-Native (innate trait) — Forged in international remote teams. Communicates in writing, ships on overlap, never blocks on a meeting.
- APM (innate trait) — Actions per minute, applied to shipping — high-tempo execution that never drops the macro plan.
- Scout (innate trait) — Probes early and often — new stacks, tools, and models are scouted and evaluated before they are needed.
- Macro (innate trait) — Plays the long game — invests in architecture and docs that compound over quarters, not sprints.
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