Luma Energy
Student Information System Development for universities
800k meters streaming in near real time
Cloud
Cloud-native systems engineered for the workload, and the invoice.
We use the cloud for what it is good at, not as a rented data center, with resilience, security and cost treated as requirements from the first diagram.
Overview
Cloud-native does not mean using as many managed services as possible. It means fitting the architecture to the workload. A burst of traffic every 15 minutes suits serverless. A steady, high-volume stream suits provisioned capacity. We make that choice for each workload, using numbers, and we prefer managed services for anything that does not set you apart. Your engineers should be building your product, not looking after message brokers.
Cost is part of the architecture, not just a finance problem. Every design we propose comes with a cost model next to the throughput and latency numbers, and the trade-offs are clear. We treat resilience the same way: multi-region active-active answers a specific SLO question, it is not a default, and we will tell you plainly when one well-run region with tested backups is enough.
Security is built in from the start, not checked at the end: least-privilege IAM from the first commit, network segmentation as code, secrets in managed vaults, and an audit trail that meets the compliance standards we often build for, including SOC 2, ISO 27001, HIPAA and GDPR.
Capabilities
What goes into a cloud system built for your workload, with the cost and security work included from the start.
Architecture for the workload
Serverless, containers or provisioned capacity, chosen for each workload from measured load, not from what is fashionable.
Containers and serverless
Kubernetes platforms where you need control and density, and functions or managed runtimes where the load makes them cheaper. Often both in one system.
Resilience engineering
We design for failure and rehearse it: multi-AZ by default, multi-region when the SLO calls for it, and recovery paths that are tested, not just written down.
Cost engineering
Every architecture comes with a cost model, and we watch production spend against it as closely as latency. A surprise on the invoice is treated as a bug.
Managed data layers
PostgreSQL, Redis, Kafka and object storage run as managed services with backup and restore that we have tested. Your data is safe because we checked, not because the vendor says so.
Security by design
Least-privilege IAM, network segmentation as code, and secrets management from the first commit, with audit trails built for the compliance rules you follow.
Process
No black boxes. Each phase has explicit outputs, and you see progress weekly, in staging, not slide decks.
- 01
Workload analysis
We measure your real load: traffic patterns, data volumes, latency needs and growth. An architecture picked without measurements is picked by trend.
Outputs
- Load profile
- Growth model
- Latency requirements
- 02
Architecture and cost model
A target design with clear trade-offs and a monthly cost forecast at today's and future scale. You approve the shape of the invoice before we build what creates it.
Outputs
- Target architecture
- Monthly cost forecast
- Trade-off record
- 03
Foundation build
Accounts, networking, IAM, CI/CD and observability, all set up as code. This is the paved road every later service deploys on.
Outputs
- Infrastructure as code
- CI/CD paved road
- Observability baseline
- 04
Service delivery
Application workloads built and shipped in weekly increments on the new foundation, with SLOs and cost tracking attached from the first deploy.
Outputs
- Weekly releases
- SLO definitions
- Cost telemetry
- 05
Operate and optimize
After launch we tune performance and spend against the model, run chaos and recovery tests, and then hand over or keep running it, whichever you prefer.
Outputs
- Tuning report
- Recovery rehearsal results
- Handover or ops plan
Outcomes
The results this service is accountable for, the reasons clients keep the engagement running.
Right-sized architecture
Your design fits your measured workload, and the reasons are written down.
No invoice surprises
You approve a cost model before the build, and we track production spend against it all the time.
Recovery you have seen work
Failure drills follow your real SLOs, so you know how long recovery takes before you need it.
Compliance built in
Security and compliance controls are there from the first commit, ready for SOC 2, ISO 27001 or HIPAA evidence requests.
Engineers focused on product
Managed services, chosen with care, free your team from infrastructure work that does not set you apart.
A platform you can run
Your team can operate it with confidence, with observability and runbooks included as standard.
Stack
Chosen for your constraints, not our comfort, this is the toolkit we know deeply for this kind of work.
- Data & streaming
- PostgreSQL
- Redis
- Apache Kafka
- Cloud & infrastructure
- AWS
- Google Cloud
- Azure
- Kubernetes
- Terraform
- Docker
- Delivery & observability
- Grafana
- OpenTelemetry
FAQ
How we choose, price and run cloud development projects.