Infrastructure That Moves at the Speed of Your Business.

Cloud & DevOps services from Frequent Research make releases routine, production visible and cloud spend deliberate. We engineer the environment around how your application needs to run — on AWS, Azure or Google Cloud — and keep it ready for AI workloads.

• AWS, Azure & Google Cloud
• Automated CI/CD
• Observability & reliability
• AI-ready infrastructure

Cloud is not a destination. It's an operating environment.

Moving an application to the cloud is one step. A mature environment connects all of these — and the business feels the difference when one is missing.

• Architecture
• Automation
• Security
• Observability
• Reliability
• Cost
• Performance
• AI readiness

Moving to the cloud doesn't automatically make software better.

Slow, anxious releases and production surprises usually come from the path between code and customer — not from the hosting provider.

1. Code
2. Manual build
3. Manual testing
4. Manual deployment
5. Production
6. Something breaks
7. Investigated by hand
8. Customer impact

1. Code
2. Automated build
3. Automated test
4. Security checks
5. Automated deployment
6. Observe
7. Alert
8. Respond
9. Improve

We don't just move applications to the cloud. We engineer the environment around how the application needs to run.

Every recommendation starts from the workload. Not every project needs every component — the right design is the one that matches how the application is used, changed and recovered.

• Workload
• Traffic patterns
• Application architecture
• Data
• Security
• Deployment frequency
• Availability
• Recovery
• Monitoring
• Cost
• Future growth
• AI workloads

Automate the path from code to production.

Select a stage — or watch a change travel through the pipeline.

1. Code
2. Build
3. Test
4. Security
5. Artefact
6. Deploy
7. Monitor
8. Feedback

Code. Every change starts in version control.

Less configuration drift. More repeatability.

The same version-controlled blueprint builds development, staging and production — so “it worked in staging” means something.

• DevelopmentMatches blueprint
• StagingMatches blueprint
• ProductionMatches blueprint

Containers, Kubernetes, serverless and microservices are used where the workload needs them — not because they are fashionable. References: Kubernetes documentation, Docker documentation.

You can't improve what you can't see.

Application health, infrastructure health, deployments, resource use and alerts in one place. Conceptual states — never invented uptime or client metrics.

• ReliabilityAttention
• DeploymentReady
• SecurityProtected
• CostControlled
• ScalingStable
• AI workloadsDeploying

One view across reliability, delivery, security, cost, scale and AI — so attention goes where it is needed.

Reliability is not a feature added after deployment. It is an architectural decision.

1. PreventFault-aware architecture, redundancy, tested backups.
2. DetectAlerts on symptoms that matter to users.
3. RespondRunbooks and clear ownership when something fails.
4. RecoverRestore from a known-good state, then verify.
5. LearnPost-incident review feeds the next improvement.

Backup strategy, recovery planning and restore testing are scoped per system; recovery times are agreed, never assumed.

Cloud growth should not mean cost growth without control.

Right-sizing, idle-resource detection, environment scheduling, storage lifecycle rules and cost allocation — balanced against performance and reliability.

• ComputeOver-provisioned
• StorageOver-provisioned
• DatabaseOver-provisioned
• NetworkOver-provisioned
• AI workloadsOver-provisioned
• EnvironmentsOver-provisioned

Provisioned Actually used — shapes, not your figures.

Capacity follows demand with headroom.

• Performance
• Reliability
• Cost

AI needs infrastructure it can actually run on.

1. User
2. AI application
3. API / application layer
4. AI services
5. Data / storage
6. Cloud infrastructure
7. Monitoring + security

Modern AI applications need scalable compute, secure data access, APIs, model services, search and vector infrastructure, background processing, workload isolation, cost controls, automated deployment and governance.

AI-assisted operations, used with care

• Monitoring that surfaces unusual behaviour.
• Log intelligence that finds patterns across large volumes.
• Incident assistance for engineers investigating issues.
• Capacity and cost signals that flag changing workloads and unusual spend.

AI-assisted, not autonomous: engineers decide what changes in production.

Move to the cloud without moving the chaos with you.

The right answer is not always the newest architecture. It is the architecture that makes business sense.

1. Assess
2. Map dependencies
3. Modernise where needed
4. Migrate
5. Validate
6. Optimise

• Rehost

  Move with minimal change where the application already works well.

  change
• Refactor

  Improve the architecture where business value justifies it.

  change
• Rebuild

  Replace components that have become a real limitation.

  change

DevOps maturity is more than having CI/CD.

Where is your environment today — and what is the next sensible step?

1. Manual
2. Automated
3. Observable
4. Reliable
5. Optimised
6. Intelligent

Manual: Servers and releases handled by hand; knowledge lives with individuals.

We optimise how the infrastructure supports the product and the business — not infrastructure in isolation.

1. Business-first infrastructure

   Technology decisions follow business requirements, not popularity.

2. Architecture before migration

   Dependencies and workloads are understood before anything moves.

3. Automation as a default

   Repeated technical work becomes repeatable automation where practical.

4. AI-ready thinking

   Environments designed with AI and intelligent automation workloads in mind.

5. Security from the beginning

   Access, secrets, monitoring and governance are part of the architecture.

6. Cost-aware engineering

   Scale and performance without uncontrolled spend.

7. Transparent ownership

   Your code, configuration and documentation stay yours, as agreed.

8. Built to be maintained

   Infrastructure that stays understandable after the first release.

Selected technologies, based on what the workload requires.

• AWS

  Scalable infrastructure, application deployment, storage, networking, monitoring and automation.

• Microsoft Azure

  Cloud environments for business workloads, identity-aware architectures and application hosting.

• Google Cloud

  Application infrastructure, data-intensive workloads and cloud-native services.

Containers

DockerKubernetesServerless

Delivery

CI/CD pipelinesRelease workflowsInfrastructure as Code

Observe

LogsMetricsAlertsTracing

Security

IAMSecretsEncryptionNetwork controls

Applications

ReactNext.jsNode.jsPythonPHP / Laravel

Mobile

FlutterReact Native

Platform names describe experience with these technologies; no partner status or certification is implied.

Where infrastructure decisions carry the most weight.

Capability examples, not claims about specific clients.

• ManufacturingERP, operations, analytics and connected devices
• RetailE-commerce, payments, inventory and peak traffic
• Financial ServicesApplications, APIs, security and data
• HealthcareAvailability, access control and data protection
• EducationPortals, seasonal load and content delivery
• MediaStreaming, publishing and traffic spikes
• TelecommunicationsPlatforms, provisioning and observability
• Information TechnologySaaS platforms, multi-tenant scale and CI/CD

Cloud & DevOps services: common questions

Related: API development & integration, AI & automation, software testing & QA, cybersecurity and application maintenance.

• What are Cloud & DevOps Services?

  The architecture, automation and operations that let software run reliably in the cloud: environments, CI/CD pipelines, monitoring, security controls, backup and cost management.

• Can you migrate an existing application to AWS, Azure or Google Cloud?

  Yes.

  Migration starts with dependencies, data and downtime requirements, then moves the application with minimal change or modernises the parts where that is worth it.

• Can you improve the cloud environment we already have?

  Yes.

  An infrastructure review looks at architecture, deployments, monitoring, security and spend, and recommends the changes with the clearest business value.

• Do you set up CI/CD and deployment automation?

  Yes — automated build, test, security checks and deployment, so releases become routine rather than risky manual events.

• Can you help control cloud costs?

  Yes.

  Right-sizing, idle-resource clean-up, environment scheduling, storage lifecycle rules and cost visibility keep spend aligned with real workload needs; we do not promise a fixed saving.

• Can the infrastructure support AI applications?

  Yes.

  AI workloads need scalable compute, secure data access, APIs, background processing, monitoring and cost controls, and these can be designed in from the start.

• Do you provide backup and disaster recovery planning?

  Yes — backup strategy, recovery planning and restore testing, scoped to the recovery needs you agree for each system.

• Can you work alongside our existing development team?

  Yes.

  Pipelines, infrastructure code and documentation are set up so your team can own and extend them.

Build the infrastructure your next stage of growth needs.

Tell us where releases slow down, what keeps you up during deployments and where the cloud bill surprises you. We'll map the environment and the changes worth making first.

• Architecture and dependency review
• CI/CD and release automation plan
• Monitoring, backup and recovery gaps
• Cost and right-sizing opportunities

Plan My Cloud Architecture

A few short questions about your platform and the infrastructure challenge help us recommend the right next step.

• Reply within one working day
• No obligation
• Clear, practical next steps

Prefer to talk first? Let's talk

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• Software Testing & QAAutomated tests inside the pipeline.
• Cybersecurity ServicesCloud security reviews and hardening.
• Application Maintenance & SupportKeep production applications healthy.
• Custom Software DevelopmentSoftware designed for its environment.