Orchestrating absolute silence from systemic chaos for teams that cannot afford noise.
InitiateAayan Mateen grew up in Leh, Ladakh — at 3,500 metres, where the air is thin and patience is not optional. That is where the doctrine of Digital Aultis comes from. Not a metaphor borrowed from mountaineering literature, but a way of moving through the world that was learned before it was applied to systems.
Every pipeline we lay, every cluster we tune, is a small act of stillness against the noise of modern software. Observe before you act. Move deliberately. Leave no trace.
Multi-region foundations on AWS, GCP and bare metal. Designed once, scaled silently.
Deployment as a calm ritual — reproducible, signed, observable, reversible.
SLOs, error budgets, on-call hygiene. We measure stillness in nines.
Internal developer platforms that turn velocity into a steady cadence.
LLM serving, tool orchestration and agent observability — intelligence that runs quietly and accountably.
We practice DevOps with a semi-agentic approach. AI agents sit inside our pipelines, our incident response and our review process — observing, diagnosing, and drafting actions for human approval. The human is always in the loop. Agents propose. Humans decide. The system executes.
Every solution below is curated, not improvised: chosen for restraint, wired for auditability, and deployed only where it removes noise rather than adding it.
Agents that watch CI, diagnose the failure, retry what is transient and roll back what is not — before a human is paged.
Incident triage agents that read traces, metrics and runbooks, then draft the first response while the on-call engineer is still pouring tea.
Policy-aware review agents wired into every pull request — security, style and architectural drift caught at the door, quietly.
Your internal tools exposed to agents through governed MCP servers — scoped, audited, revocable. Capability without exposure.
Traces, evaluations and drift guards for agents in production. If intelligence acts on your systems, it acts on the record.
Runbooks that execute themselves under human approval — remediation as a reviewed, reversible, one-click ritual.
The paved road for agents themselves — an internal platform where teams declare, deploy and observe agents the way they ship services. Golden-path templates, scoped credentials issued and revoked centrally, evals wired into CI, one quiet route from prototype to production. Your platform team built roads for services; we extend them to colleagues made of configuration.
The DORA research is clear: teams that automate deliberately deploy more, recover faster, and break less. These are not promises. They are the measurable consequence of doing the boring work well.
You just raised. Every day without CI/CD is a day you are one bad deploy from an outage. Every day without observability is a day you are flying blind.
Basecamp builds your foundation in 7 weeks. CI/CD with GitOps. Cloud architecture on the right provider. Observability from day one. Security baseline. Runbooks your team can follow at 4am.
You own everything. When you hire, you hire for the right seat.
Audit. Assess. Map the terrain.
Build the foundation.
Ship through the new system.
Keys, docs, hiring profile.
We build on the Cloud Native Computing Foundation ecosystem — graduated projects first: Kubernetes, Prometheus, Argo, Helm, OpenTelemetry, Envoy, Cilium. Vendor-neutral by doctrine, so your platform outlives any single cloud, contract, or fashion.
The CNCF landscape is growing an agentic layer. These are the projects we watch, deploy and harden for clients — each marked with where it stands in the foundation.
Kubernetes-native agent framework for DevOps and platform teams — agents declared as CRDs, tools spoken over MCP, governed inside your GitOps workflow. Cluster inspection, policy generation, automated remediation.
The automated SRE — scans the cluster, triages what it finds, and explains failures in plain language using local or remote models, with remediation guidance attached.
An autonomous investigator for production incidents — reads platform telemetry, walks the evidence, and drafts the root-cause story before the human arrives.
Next-generation Kubernetes gateway (formerly Gloo) built for the agentic transition — agent-to-agent communication, traffic shaping and tool routing for autonomous workloads.
Envoy extended for intelligence — manages, secures and routes inference and agentic tool-calling traffic, with emerging MCP connectivity for distributed agents.
Policy as code, now agent-aware — paired with frameworks like kagent, policies are generated, validated and mutated through natural language instead of hand-written YAML.
Runtime security for agentic workloads — discovers security posture, enforces zero-trust bounds and intercepts threats at machine speed, without waiting on an operator.
Isolation primitives for agents that act — gVisor and Kata Containers-backed sandboxes giving autonomous workloads a safe, multi-tenant place to run.
One runtime orchestrates the agents; one protocol — MCP — connects them to every tool; policy and runtime security hold the guardrails. Everything declarative, everything on the record, everything inside the cluster.
K8sGPT spots the failing pod in the cluster scan.
HolmesGPT gathers telemetry, events and the root cause.
kagent drafts the remediation steps from available tools.
Actions run through MCP — kubectl, Kyverno, Argo CD.
Results validated and reported back to the human.
Pre-product-market-fit, a €20 server with Docker Compose beats a managed container platform on cost, speed and sleep. The real numbers — and the honest moment to switch.
Terraform taught us to declare machines instead of building them by hand. The next step is infrastructure that is operated by agents — and agents that are themselves declared, reviewed and promoted like any other artifact.
On-call, code review, runbooks, postmortems — every ritual of DevOps is being renegotiated as AI agents take their place in the loop. What survives, what inverts, and what becomes more important than ever.
Observability is not a tool. It is the ability to ask any question of your system from the outside and get an answer without changing the code. Most teams have monitoring. Few have observability.
We build the kind where you open a dashboard and know what is wrong in 10 seconds. Where alerts fire before your users notice. Where the on-call engineer follows a signal, not a hunch.
Prometheus scraping every service. Grafana dashboards your CTO can read at a glance. SLOs with error budgets that tell you when to slow down, not just when something broke.
OpenTelemetry distributed tracing. Follow a request across every service. See where it slows, where it fails, where it waits. The difference between knowing something is slow and knowing why.
Structured logs in Loki, not grep in a terminal. Correlated with metrics and traces. When an alert fires, the logs that matter are one click away, not one grep away.
The CNCF stack: Kubernetes, ArgoCD, Prometheus, OpenTelemetry, Envoy, Cilium, Terraform. Plus the agentic layer: kagent, K8sGPT, HolmesGPT, kgateway, Kyverno, KubeArmor. We are vendor-neutral. Your platform should outlive any single cloud provider.
Yes. We handle migrations from VMs, Docker Compose, ECS, and Cloud Run to Kubernetes. We also tell you honestly if you are not ready for Kubernetes yet. Sometimes a well-run VPS is the right answer for your stage.
Yes. We serve clients across the EU, Middle East, and US. All work is remote-first. We have operated production from Leh, Ladakh at 3,524m for years. Distance is a design constraint we have already solved for.
Both. Expedition is a one-time audit. Ascent is a monthly retainer. Residency is a quarterly partnership. Most clients start with Expedition and move to Ascent once they see the value.
Security is built in, not bolted on. We implement Pod Security Standards, network policies, secrets management, supply-chain signing, and policy-as-code from day one. We are GDPR-compliant and ISO 27001-ready. But we start with a threat model, not a certificate.
We practice DevOps with a semi-agentic approach, not fully autonomous. AI agents sit inside our pipelines, our incident response, and our code review, governed by MCP. But humans are always in the loop. Agents propose actions. Humans approve them. Every action is logged, reversible, and audited. We are in transition from traditional DevOps toward agentic DevOps, and we think that is the right place to be.
Not a pitch deck. Working infrastructure, delivered in weeks, owned by you.
Validate your architecture through hands-on implementation, not theory. We design, build, and hand off Kubernetes platforms your team can operate.
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Not a hype list. Not a vendor pitch. These are the tools I wire together for clients when they want agents in their pipelines, their incident response, and their code review. What each one does, where it breaks, and when I would not use it.
Read article →After running Coolify in production for months, here is what it actually does well, where it breaks, and why I recommend it to startups who are not ready for Kubernetes but have outgrown Docker Compose.
Read article →On-call, code review, runbooks, postmortems — every ritual of DevOps is being renegotiated as AI agents take their place in the loop. What survives, what inverts, and what becomes more important than ever.
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