Infrastructure teams
Cloud operators running OpenStack, OpenShift, Kubernetes, Linux services, and the messy integrations between them.
Incident reasoning for serious infrastructure teams.
Wavesync is shaping an AI-assisted operations platform that gathers evidence, explains system behavior, retrieves the right runbook, and proposes safe next actions for cloud incidents.
Input
Logs, alerts, configs, tickets
Control
Human-approved actions
Stacks
OpenStack, OpenShift, Kubernetes
Built for
Teams that live close to production.
The platform is for engineers who need faster diagnosis without hiding the evidence trail behind a black-box assistant.
Support engineers
L2 and L3 teams who need incident summaries, triage paths, evidence capture, and repeatable customer-facing explanations.
Managed service teams
Providers who want consistent runbook execution, faster escalation notes, and safer automation across many environments.
Outcomes
Useful AI means shorter investigation loops.
Wavesync focuses on assistive workflows that improve operational clarity before any automated change is allowed.
Reduce time to diagnosis
Correlate symptoms across alerts, logs, topology notes, and recent changes so engineers start closer to the fault domain.
Preserve the evidence trail
Keep source references visible, separate facts from guesses, and make post-incident review easier to reconstruct.
Standardize runbooks
Turn proven checks into repeatable workflows that junior and senior engineers can both inspect and improve.
Automate with restraint
Suggest commands and remediation paths, but keep destructive or high-impact action behind explicit human approval.
Workflow
From signal to action, with the operator still steering.
The page borrows the clarity of a program detail page, but the offer is a platform pilot: scoped, measurable, and grounded in your own operational data.
Collect
Ingest logs, alerts, tickets, topology notes, and runbooks.
Correlate
Connect symptoms with dependencies, versions, and changes.
Explain
Summarize what happened, what is known, and what is uncertain.
Recommend
Propose checks, runbooks, and low-risk remediation paths.
Approve
Let engineers review and approve any action before execution.
Architecture fit
Designed around the stacks Wavesync already works in.
The first version is practical: read-only evidence capture, runbook retrieval, incident summaries, and operator-reviewed recommendations. It is meant to integrate with existing tools instead of asking teams to replace their operating model.
OpenStack
OpenShift
Kubernetes
Linux
JBoss
Prometheus
Grafana
Logs
Runbooks
Ticketing data
Proof of work
Built from small, concrete operational tools.
The platform direction comes from hands-on builds rather than a generic chatbot wrapper.
Endpoint Checker Automation
Workbook-driven DNS and TCP reachability checks for application endpoint review.
EX180 Practice Lab
OpenShift task practice with isolated namespaces, timed objectives, and practical grading.
Ticketing Demo
Checkout, e-ticket, admin, quota, and QR scan flow built as an internal product demo.
Edge Device Web Lab
Lightweight Linux and web experiments on constrained hardware exposed through secure tunnels.
Pilot package
Start with one painful incident class.
A good pilot should not boil the ocean. Pick one repeatable operational problem, connect the evidence sources, validate the reasoning, and decide which steps deserve automation.
Discovery
Map systems, incident patterns, evidence sources, and approval boundaries.
Prototype
Build read-only investigation flows around real logs, runbooks, and tickets.
Controlled automation
Convert accepted checks into repeatable tasks with review before execution.
Handoff
Document the workflow, limits, next improvements, and rollout path.
Work with Wavesync
Want to test this against your own incident workflow?
Wavesync is open to focused AI operations pilots, cloud platform support, and automation builds across Indonesia and Southeast Asia.