Cloud infrastructure
Cloud infrastructure built around your workload
Infrastructure decisions are specific. The right answer depends on where your users are, what your application actually does under load, what it must comply with, and how much room it needs to grow. We start there rather than with a product page.
Decision factors
What actually shapes an infrastructure decision
These twelve factors come up in almost every engagement. Most poor infrastructure outcomes can be traced back to one of them being skipped.
Location
Where the workload physically runs determines the baseline for everything else — latency, resilience options, regulatory exposure and often cost.
Latency
The distance between users and infrastructure sets a floor on response time that no amount of optimisation removes. Interactive applications feel this first.
Compute requirements
How much processing the workload genuinely needs, including whether it is sustained or bursty, single-threaded or parallel.
Memory requirements
Many applications are memory-bound rather than CPU-bound. Sizing on processor count alone is one of the most common and expensive mistakes.
Storage
Capacity, throughput, input/output patterns and durability requirements. Databases, file workloads and archives each want something different.
Bandwidth
Data transfer volume and direction, including egress patterns that can quietly become a significant part of a monthly bill.
Traffic
Average load, peak load, the shape of the peaks and how predictable they are. Seasonal and campaign-driven traffic changes the calculation.
Scalability
Whether growth is handled by resizing, by adding instances, or by a change of architecture — and how much notice each option needs.
Availability
How much downtime the business can tolerate, and what redundancy is proportionate to that tolerance rather than to a marketing target.
Budget
A real constraint, treated as one. It is usually better to run a well-sized system within budget than an oversized one that gets cut back later.
Security
Access control, network exposure, encryption, patching responsibility and any data residency or regulatory considerations that apply.
Application architecture
Monolithic, containerised, serverless or hybrid — the shape of the application constrains which infrastructure patterns are sensible.
Infrastructure planning
From requirement to deployed environment
Cloud deployment covers more than provisioning a server. It includes deciding what runs where, how components communicate, what happens when one of them fails, how the environment is reached by the people who administer it, and how the whole arrangement changes as demand grows.
We work through that sequence deliberately, and we document the decisions so that the next person to look at the environment can understand why it is shaped the way it is.
- Workload placement — which components sit in which region, and why.
- Resource planning — compute, memory, storage and bandwidth sized to observed behaviour.
- Redundancy strategy — proportionate to the availability requirement, not to a default template.
- Network design — exposure, access paths, and separation between environments.
- Growth path — the specific steps available when the system needs more capacity.
- Cost model — what the environment costs at current load and at planned load.
Regional deployments
Access infrastructure across major global cloud regions
Deployment options across leading international cloud regions, selected around latency, availability, compliance and workload requirements.
Singapore & Southeast Asia
A strategic regional location for Southeast Asian workloads, regional businesses, SaaS platforms, web applications, APIs and low-latency services serving nearby markets. Singapore is well connected to the rest of the region and is frequently the sensible default for teams whose users sit across SEA.
Typical use: regional customer-facing applications, APIs serving SEA traffic, business systems for regional teams.
Asia Pacific
Locations including Tokyo, Seoul and Australian regions support workloads serving Japan, Korea and Oceania, along with organisations that need a second APAC location for redundancy or for audience-specific performance.
Typical use: market-specific deployments, APAC redundancy, latency-sensitive services for North Asian users.
East Asia & South Asia
Hong Kong and Mumbai serve as useful points of presence for East Asian and Indian audiences, and for organisations distributing workloads across a wider Asian footprint.
Typical use: regional expansion, audience-specific performance, distributed Asian deployments.
Europe
Frankfurt, London, Amsterdam and Paris cover most European requirements, including deployments where data residency within the region is part of the decision.
Typical use: European user bases, EU-focused business systems, residency-driven placement.
North America
Virginia, California and Toronto support workloads serving United States and Canadian users, and are common choices for organisations whose customers or partners are concentrated there.
Typical use: North American audiences, cross-Atlantic redundancy, partner-facing systems.
Australia & global
Sydney and Melbourne serve Australian users directly, and additional international cloud regions are available where a workload calls for them. Multi-region arrangements are planned deliberately rather than assumed.
Typical use: Australian deployments, multi-region architectures, global distribution.
ADOBEVN does not claim to own physical data centres. We plan and deploy workloads using infrastructure available through established cloud providers, and regional availability may vary by service, provider, configuration and technical requirements.
Region selection
Choosing the right region
Region selection is an architectural decision with commercial consequences. It is worth an hour of analysis before deployment and expensive to revisit afterwards.
We work through the question with you rather than defaulting to whichever location happens to be nearest to us. The factors below usually settle it, and where two options are genuinely close we will say so and explain what would tip the balance.
- User location
- Where the majority of requests originate, and whether that concentration is stable or shifting as the business grows.
- Application requirements
- How sensitive the workload is to round-trip time, and whether parts of it can be separated from the latency-critical path.
- Regulatory considerations
- Data residency, sector-specific rules and contractual obligations that constrain where information may be processed or stored.
- Performance goals
- The response times the business is actually targeting, expressed as a requirement rather than an aspiration.
- Redundancy strategy
- Whether a second region is needed, what it is protecting against, and how failover would work in practice.
- Cost
- Regional price differences, data transfer between regions, and the operational overhead of running in more than one place.
Redundancy & availability
Proportionate resilience
Every additional layer of redundancy adds cost and operational complexity. The right amount is the amount your business case justifies.
01
Single-region, single-instance
Appropriate for development environments, internal tools and workloads where a short recovery window is acceptable. Backups and a documented restore procedure carry most of the weight here.
02
Single-region, redundant components
Multiple instances behind a load balancer, separated storage and managed database options. Handles the most common failure modes without the cost of a second region.
03
Multi-region
A deliberate architecture for workloads where regional failure or wide geographic distribution genuinely matters. It changes how data is written, synchronised and read, so it is planned rather than added.
We do not publish uptime guarantees on this website. Availability characteristics depend on the architecture chosen, the infrastructure provider involved and the service terms that apply to a specific deployment, and they are discussed in the context of an actual engagement.
Workloads
What we commonly deploy
Web applications
Customer-facing sites and applications where response time and reliability directly affect the business.
APIs and backend services
Service infrastructure supporting mobile apps, integrations and internal systems.
Business systems
Internal platforms, administrative tools and line-of-business applications.
Development environments
Development, staging and testing infrastructure that mirrors production closely enough to be useful.
Data processing
Batch processing, transformation pipelines and analytical workloads with defined throughput requirements.
Automation
Scheduled jobs, integration workers and operational automation that needs somewhere reliable to run.
Remote workloads
Systems accessed by distributed teams, where access paths and regional placement both matter.
Internal tools
Team-facing applications where access control and cost efficiency usually outweigh raw performance.
Plan infrastructure around what your system actually needs
Bring us the workload, the audience and the constraints. We will help you decide where it should run, how it should be sized and what the growth path looks like.