Architecture that holds under load and under audit.
Cloud infrastructure should scale with the business — not outrun its budget, and not require the person who built it to be reachable at 2am.
Yes — JANNEX provides cloud and AWS engineering: architecture design and review, migration from on-premises or another provider, modernisation to serverless and containers, infrastructure as code, CI/CD, observability, cloud security and cost optimization.
Where cloud programmes come apart
Usually a lift-and-shift that moved the problem into a place where it costs more per month and is harder to see.
- Infrastructure created by hand, reproducible only by memory
- One account holding production, staging and someone's experiment
- No tagging, so cost cannot be attributed to anything
- Monitoring that alerts on CPU but not on the thing customers feel
- A disaster recovery plan that has never been executed
How we approach AWS
Well-architected in the literal sense: reliability, security, performance, cost and operations weighed against each other, deliberately.
Landing zone first
Account separation, identity, network boundaries, logging and guardrails before workloads move.
Everything as code
Infrastructure defined, reviewed and versioned. Environments are rebuilt, not repaired.
Observe what users feel
Service-level objectives on latency and errors, with alerts tied to those rather than to hosts.
Cost as an architectural property
Pricing model chosen alongside the design, with tagging and budgets in place from day one.
What this covers
Architecture
- Well-architected reviews
- Multi-account landing zones
- Network design
- High availability and failover
- Disaster recovery design and testing
Migration & modernisation
- Assessment and wave planning
- Database migration
- Re-platforming to containers
- Serverless decomposition
- Cutover and rollback planning
Platform
- Infrastructure as code
- CI/CD pipelines
- Container orchestration
- Secrets and configuration
- Environment provisioning
Operate
- Metrics, logs and traces
- Service-level objectives
- Alerting and on-call design
- Backup and restore drills
- Cost monitoring
A reference shape, read top to bottom
Not a template to be applied unchanged. It is the set of decisions every AWS design has to make, in the order they constrain each other.
Caching and protection at the boundary, so origin capacity is spent on work that cannot be cached.
Compute model chosen per workload shape — serverless for spiky, containers for steady, dedicated for sustained throughput.
Primary store, cache and object storage with lifecycle rules and retention set at design time.
Asynchronous boundaries so a slow dependency degrades the system rather than stopping it.
Everything defined in code, with account separation as a hard boundary for cost and for security.
Metrics, traces, detection and tested restore — the parts that decide how long a bad day lasts.
Technology
The working set for this capability. Choices are made per engagement, against your constraints and your team's skills.
Where it is typically applied
Patterns we see repeatedly, described generically. Your version will differ in the details, and the details are the work.
On-premises to AWS
Planned in waves, with the riskiest dependency identified first and a tested rollback for each wave.
Monolith to containers
Packaged, orchestrated and given a real deployment pipeline before any decomposition is attempted.
Serverless for spiky workloads
Event-driven processing that costs nothing at idle and absorbs a peak without capacity planning.
Recovery you have actually tested
Backup, restore and failover documented and executed on a schedule, with the time it took recorded.
How the engagement runs
The same seven stages, scoped to the size of the problem.
Understand
We start with the constraint, not the feature list. What breaks today, who it affects, what it costs.
Define
A written scope with the trade-offs made explicit — what is in, what is deferred, what we will measure.
Design
Interfaces, data models and system boundaries designed together, because they constrain each other.
Build
Short cycles against a working environment. Reviewed code, tests where they earn their keep.
Launch
Staged rollout with monitoring in place before traffic, not after the first incident.
Learn
Instrumented usage read against the thing we said we would measure at Define.
Scale
Performance, cost and operations tuned once real load has told us where the pressure is.
Questions we are asked
Is AWS the right choice for us?
Frequently, but not automatically. The question is workload shape, existing skills, data residency and commercial terms. If another provider or a hybrid arrangement fits better, that is the answer we will give.
Should we go serverless?
For event-driven, variable and bursty workloads it is usually the cheaper and simpler answer. For sustained, predictable, high-throughput compute it often is not. It is a per-workload decision.
Can you work with our existing AWS estate?
Yes. That normally starts with a review: architecture, security posture, reliability and cost, with findings ranked by risk and by effort to fix.
Do you provide ongoing operations?
Yes, as a defined engagement with agreed response expectations — or we set the platform up and train your team to run it. Both are legitimate; the choice is yours.
Related reading
AWS cost optimization: where cloud bills go wrong
The recurring causes, roughly in the order we find them, and why the biggest number on the invoice is usually not the biggest opportunity.
Read AWS · 7 min readHow to build a cost-efficient AWS architecture from day one
The decisions taken in the first fortnight determine most of what you will pay in year two.
Read Software Engineering · 7 min readMonolith vs microservices: what actually makes sense?
Service boundaries are an organisational decision with a technical bill attached. Most teams pay the bill before they need the benefit.
ReadHave something worth building?
Tell us the constraint you are working against. If we are not the right people for it, we will say so.
Or write to connect@jannex.in