AI for your business
For businesses that want AI to solve a real problem and need to know what is feasible and how to deploy it safely.
Capability
Run your applications on a cloud foundation you can trust
We build and modernize the infrastructure and deployment environments needed to operate applications, data platforms and AI workloads.
In short
Cloud and platform engineering is the foundation your software runs on: environments, networks, deployment, monitoring, security, backup and cost control. Nexstella designs and automates that foundation on AWS, Microsoft Azure or Google Cloud, so changes are repeatable and the platform is observable.
Last updated
01 When it matters
When does your cloud foundation need attention?
Infrastructure has grown organically and needs stronger deployment, security, monitoring and cost controls. The applications, data and AI workloads that depend on it need a more controlled and repeatable operating environment.
Cloud architecture should balance managed-service benefits, portability, operational simplicity, security and commercial constraints, so we start from your workloads rather than a preferred platform.
A business runs applications, data and AI workloads on infrastructure that now needs a more controlled and repeatable way to be deployed, secured, monitored and paid for.
We would assess the cloud architecture, design separate environments and network boundaries, put infrastructure and releases under code, and add monitoring, backup and recovery, and cost controls.
02 Services
What does this include?
- Cloud architecture and workload assessment
- AWS, Microsoft Azure and Google Cloud implementation
- Cloud landing zones and environment design
- Infrastructure as Code
- Network architecture and secure connectivity
- Containerization and Kubernetes deployments
- CI/CD pipeline development
- GitOps and configuration automation
- Application and platform deployment automation
- Developer environments and reusable platform templates
- Monitoring, logging, metrics and distributed tracing
- Infrastructure security and secrets management
- Backup, recovery and disaster recovery planning
- Reliability engineering and incident investigation
- Cloud resource optimization and FinOps
- Hybrid-cloud and application migration
03 Applications
Where does this usually apply?
- Establishing a secure cloud foundation for a growing SaaS business
- Automating the deployment of applications across development, staging and production
- Standardizing infrastructure provisioning through reusable templates
- Deploying containerized AI inference services
- Improving observability and reliability across data pipelines and applications
- Reducing unnecessary cloud expenditure through workload analysis and optimization
04 Technology
How do we choose the technology?
- Docker
- Kubernetes
- Helm
- Terraform
- OpenTofu
- Terragrunt
- Ansible
- GitHub Actions
- GitLab CI/CD
- Jenkins
- Argo CD
- Prometheus
- Grafana
- OpenTelemetry
Cloud and tooling choices balance managed-service benefits, portability, operational simplicity, security and commercial constraints, and follow your workloads rather than a preferred platform.
05 Deliverables
What do you get?
- Cloud architecture diagrams and technical specifications
- Infrastructure as code and automated deployment pipelines
- Separate development, testing, staging and production environments
- Monitoring configuration, runbooks and backup validation
- Handover documentation and a known-issues register
06 Needs
Which needs does this serve?
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Growing technology
For growing businesses whose infrastructure, data and releases need to keep pace with more users and complexity.
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Modernizing systems
For businesses with systems that are costly to maintain, hard to scale or poorly integrated with each other.
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Idea to product
For founders with a product idea who need a technical plan, a first version and a foundation that can grow.
07 Questions
What do people usually ask?
We implement on AWS, Microsoft Azure and Google Cloud. Platform choice balances managed-service benefits, portability, operational simplicity, security and commercial constraints, and hybrid arrangements are possible where on-premises systems must coexist with the cloud.
Depending on requirements, it may include cloud landing zones, private networking, separate development, testing, staging and production environments, infrastructure as code with peer-reviewed changes, centralized secrets management, monitoring and audit trails, and backup and restoration controls.
Security checks, dependency scanning, secret detection, infrastructure validation and release approvals are integrated into the delivery process at appropriate points, from planning and design through deployment and observation.
Solutions
Which solutions do we build for this?
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MVP to production
We help translate a product concept into a technically sound, production-ready first version, on a foundation that can evolve as your business develops.
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Real-time data
We build streaming pipelines that ingest and process high-volume events, so people and systems can act on current information.
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Cloud foundation
We set up the accounts, networks, environments and controls that applications, data and AI workloads run on, so infrastructure is repeatable rather than improvised.
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DevOps automation
We automate how code and infrastructure are built, tested, scanned and deployed, with approvals and rollback, so releases rely less on manual steps.
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Cloud cost optimization
We make cloud costs visible by workload, set baselines, and then optimize resources and queries without weakening performance, security or reliability.
If this sounds like you: Fewer outages, faster answers, a calmer on-call week