Cloud modernization and managed operations
Onata designs, modernizes and operates cloud environments around measurable business value, with security, economics and automation built into the architecture from the start.
Why the operating model matters now
The market signals are clear. The next cloud advantage comes from connecting architecture, economics, governance and AI to measurable outcomes.
64%
Onata starts with outcome measures the business can recognize.
Flexera 2026
49%
Cloud cost becomes more useful when it is tied to the service or workload it enables.
Flexera 2026
29%
Onata puts economics into engineering decisions before inefficiency becomes embedded.
Flexera 2026
Research basis Flexera 2026 State of the Cloud and State of FinOps 2026
The operating question
Treating them as separate workstreams creates more handoffs, more ambiguity and slower decisions. Onata brings those decisions into one operating model so the cloud estate can keep improving after the initial move.
01
Reduce technical debt, simplify dependencies and move workloads with a clear view of the operating model that follows.
02
Connect architecture, usage and unit economics so teams can make better tradeoffs before spend becomes waste.
03
Build the data, platform, access, observability and cost controls required for AI workloads to operate responsibly at scale.
04
Use observability, automation and clear service ownership to reduce operational toil and improve recovery when conditions change.
Capabilities
The work is organized around the estate, not around isolated service lines.
01
Estate assessment, workload placement, landing zones, architecture, governance, business case development and modernization roadmaps.
02
Application, infrastructure and data migration with replatforming, refactoring, containerization and continuous technical debt reduction.
03
Cloud native platforms, infrastructure as code, continuous delivery, developer enablement, observability and reliability engineering.
04
Modern data foundations, analytics, model services, AI applications, agent platforms, deployment pipelines, observability and governance.
05
Identity, policy, posture, data protection, workload security, resilience, recovery and continuous control across the cloud estate.
06
Cloud operations, reliability, incident management, capacity, optimization, cost allocation, forecasting and technology value management.
Operating model
A continuous model that keeps architecture decisions connected to the teams responsible for operating and improving the environment.
01
Frame business outcomes, assess the estate, understand dependencies and make deliberate architecture, security and economic choices.
02
Modernize applications and infrastructure, create platform foundations and automate repeatable engineering work.
03
Operate with observability, reliability practices, clear ownership and disciplined incident and change management.
04
Continuously optimize economics, capacity, architecture health, technical debt and operational performance.
Security, governance and economics remain part of every stage rather than being added after delivery.
How Onata works
Start with what the workload must accomplish, what risk is acceptable and what success will be measured against before choosing the technical path.
Cost, performance and reliability are designed together so optimization starts before deployment rather than after the bill arrives.
Architecture decisions stay connected to operations so the environment can be measured, supported and improved without losing context.
Automation removes repeatable toil while identity, policy, approval, auditability and observability remain explicit.
AI in production
When AI enters production, data access, model choice, agent permissions, inference cost, observability and security become platform concerns. Onata treats them as operating decisions from the beginning.
Data foundations, model services, orchestration, deployment and observability designed for production use.
Identity, policy, data boundaries, approval, auditability and human oversight built into the operating model.
Inference cost, capacity, usage attribution and value per workload made visible as adoption grows.
Measurement
Progress should be visible in how quickly teams can deliver, how reliably systems operate, how clearly spend maps to value and how consistently controls are applied.
01
Time required to move a change safely from decision to production.
02
Service health, operational toil and the ability to recover when conditions change.
03
The cost of technology in relation to the product, service or workload it enables.
04
How consistently security, governance and operational policies are applied across the estate.
Technology foundation
The technology choice follows the workload. The operating principles remain consistent across platforms.
Cloud platforms
Cloud native runtime
Infrastructure as code
Continuous delivery
Observability
Data platforms
AI services
Security tooling
Start with the decision in front of you
Bring the estate, workload, reliability, security or cost question that needs a clear answer. Start with the current state, the tradeoffs and the action that creates the most value next.