Cloud and server foundations
Accounts, projects, networking, compute, storage, DNS, certificates, environments, access boundaries, and shared services.
Infrastructure
Infrastructure designed around the workload and its operating owner
Kubto helps teams plan and improve the compute, network, data, deployment, monitoring, and recovery paths that AI and business applications rely on.
Who this is for
Engineering, platform, infrastructure, security, and product leaders preparing a new workload or resolving reliability, deployment, performance, and cost constraints.
Problem to solve
Production risk appears when application architecture, model behavior, data services, cloud limits, security controls, and on-call ownership are treated as separate decisions.
Scope
Infrastructure capability areas
The design starts with workload characteristics and recovery needs rather than assuming one cloud, orchestrator, or topology.
Containers and orchestration
Image lifecycle, runtime configuration, scheduling, autoscaling, secrets, ingress, health checks, and deployment controls.
AI serving and data paths
Model APIs or serving, queues, vector and relational data, object storage, caching, batch work, and rate-limit behavior.
Delivery engineering
Build and release pipelines, artifact controls, infrastructure as code, environment promotion, migrations, and rollback.
Observability and operations
Logs, metrics, traces, service objectives, alert ownership, runbooks, incident review, capacity, and cost signals.
Resilience and recovery
Failure domains, backups, restore tests, dependency degradation, redundancy, disaster recovery, and continuity decisions.
Architecture
A workload-led infrastructure process
The target state is selected only after current constraints and operational responsibilities are understood.
- 01
Characterize the workload
Document traffic, data sensitivity, latency, availability, throughput, batch, GPU or CPU, storage, and dependency patterns.
- 02
Map the current state
Identify environments, assets, trust boundaries, operational gaps, vendor limits, failure modes, and existing standards.
- 03
Design and validate
Compare options, prototype uncertain components, define service objectives, model cost, and test recovery assumptions.
- 04
Deliver and operationalize
Automate the approved design, validate controls, document procedures, assign owners, and establish improvement review.
Deliverables
What the engagement can produce
✓
Current-state and risk map
Workloads, dependencies, data paths, trust boundaries, constraints, owners, failure scenarios, and prioritized gaps.
✓
Target architecture and decisions
Diagrams and decision records explaining topology, services, tradeoffs, security boundaries, resilience, and cost assumptions.
✓
Delivery foundation
Agreed infrastructure code, deployment pipeline, environments, observability, validation, and rollback capability.
✓
Operational readiness pack
Service objectives, dashboards, alerts, runbooks, backup and restore evidence, ownership, and review cadence.
Boundaries
Boundaries and decisions to verify
Good work is easier to trust when the team knows what is included, what still needs proof, and who owns each decision.
Cloud provider is part of shared responsibility
Provider capabilities do not replace customer configuration, application controls, access governance, backups, or incident ownership.
Availability is engineered and contracted
Topology alone is not an SLA. Service objectives, exclusions, dependencies, support, and recovery commitments require explicit agreement.
Managed scope must be named
Monitoring, response, patching, backups, optimization, and on-call work remain with the agreed owner unless the contract states otherwise.
Bring the workload, constraints, and current architecture
Kubto can help turn them into a prioritized readiness review, target design, and delivery plan without assuming a one-size-fits-all stack.
Request an infrastructure review