Cloud Solutions

Cloud That Serves Your Business, Not the Other Way Around

Cloud computing is the default infrastructure choice for most software products today, for good reasons: you pay for what you use rather than owning hardware, you can scale capacity up and down as demand changes, and you get access to managed services that would take significant engineering effort to run yourself. But the cloud done carelessly can be expensive, complicated, and unreliable. Cloud bills that grow faster than revenue, architectures that are hard to operate, and vendor lock-in that limits future flexibility are real and common problems.

We approach cloud architecture with a specific philosophy: use managed services where they save meaningful operational work, keep architectures as simple as the requirements allow, design for the current scale with clear paths to scale further, and avoid lock-in that would make it expensive to change direction. These principles sound obvious but they require discipline to apply when there's always a compelling new service or pattern to try.

Architecture Design

Cloud architecture design starts with understanding requirements: expected traffic and load patterns, data volume and growth rate, latency requirements, availability requirements (99.9% versus 99.99% implies very different architectures and costs), compliance requirements, and the team's operational capacity. Architecture decisions should be driven by these requirements, not by what's novel or what other companies are using at a different scale.

For most applications, the right architecture is simpler than you might expect. A load balancer, a few application servers, a managed database, a CDN for static assets, and a managed cache covers the requirements of the vast majority of web products up to significant scale. The additional complexity of microservices, event streaming, and distributed caching is justified when specific requirements demand it — not as a default starting point.

AWS Architecture

AWS is the most capable cloud platform, with managed services for almost every infrastructure need. We design AWS architectures using the appropriate services for the job: EC2 or ECS for compute, RDS or Aurora for relational databases, DynamoDB for specific NoSQL use cases, S3 for object storage, CloudFront for CDN, ElastiCache for Redis, SQS for message queuing, Lambda for serverless compute where appropriate.

IAM (Identity and Access Management) design is a critical part of any AWS architecture. Every service and every person should have exactly the permissions they need and no more. This principle — least privilege — is both a security requirement and a safety mechanism that prevents accidental access to production resources. We design IAM policies carefully and review them as part of the architecture work rather than treating them as an afterthought.

Infrastructure as Code

Infrastructure defined in code — using tools like Terraform or AWS CloudFormation — is version-controlled, reviewable, reproducible, and auditable. You can see exactly what changed and when, roll back changes if something goes wrong, and spin up identical environments quickly. Infrastructure defined manually through a console is none of these things: it's invisible to version control, impossible to review as code, and difficult to reproduce accurately.

We use Terraform for infrastructure as code because it works across cloud providers, has a large ecosystem of modules, and is the industry standard for this work. We write modules that are reusable across environments (staging and production share the same module definitions with different variable values), and we structure configurations so that the infrastructure is easy to understand even for someone who didn't write it.

Cost Optimization

Cloud cost optimization is an area where there's often significant money to be found without reducing capability. Common sources of waste: oversized instances that were provisioned with too much headroom and never resized as the application's actual resource needs became clear, instances running 24/7 for workloads that only need capacity during business hours, data transfer costs from architectures that move data between regions unnecessarily, storage costs from logs and backups that are retained longer than needed, and on-demand pricing for workloads that run predictably and would be significantly cheaper on reserved capacity.

We conduct cloud cost audits that identify specific opportunities with quantified savings. The typical outcome of an audit is a prioritized list of changes, each with an estimated monthly saving and the implementation complexity. Some changes are trivial (changing a retention policy, resizing an idle instance). Others require more work but deliver larger savings (redesigning a data pipeline to reduce cross-region transfer).

Multi-Cloud and Cloud Migration

Multi-cloud strategies — using multiple cloud providers for different workloads — are appropriate for specific situations: regulatory requirements that mandate data in certain regions where your primary provider doesn't have facilities, risk management for critical workloads, or taking advantage of specific capabilities that are stronger on one platform than another. For most products, multi-cloud adds complexity without proportionate benefit, and we say so when a client is considering it without clear requirements that justify it.

Cloud migrations — moving an existing application from on-premise infrastructure or from one cloud provider to another — require careful planning to avoid downtime and data loss. We follow a lift-and-shift approach for the initial migration (moving the existing architecture to the new platform as-is), then optimize for the new platform in a second phase. This approach reduces risk by limiting the number of simultaneous changes.

Disaster Recovery

Disaster recovery planning answers the question: if the worst happens — a region goes down, data is corrupted, a deployment goes wrong and can't be rolled back — how quickly can we restore service and how much data can we afford to lose? The answers to these questions (Recovery Time Objective and Recovery Point Objective) determine the architecture and the cost of disaster recovery.

We design disaster recovery architectures that are appropriate for your RTO and RPO requirements without over-engineering for scenarios that aren't realistic risks. This typically includes automated backups with tested restore procedures, cross-region replication for critical data, and runbooks for the most likely failure scenarios so recovery can happen quickly under pressure.

Frequently Asked Questions

Which cloud provider should we use? AWS for complex architectures, compliance requirements, or when you need the broadest selection of managed services. DigitalOcean for simpler products where the operational simplicity and lower cost is more important than AWS's depth. Google Cloud for specific use cases (BigQuery for analytics, Vertex AI for ML). Azure for organizations that are deeply in the Microsoft ecosystem. We help you evaluate based on your specific requirements.

How do we control costs as we grow? By building cost monitoring into your operations from the start — tagging resources, setting up cost alerts, reviewing the bill monthly and investigating unexpected increases. We set up this infrastructure as part of the initial architecture work.

Can you reduce our existing cloud bill? Probably yes. Start with an audit. Most organizations with a cloud bill that's been growing for a year or more have meaningful optimization opportunities.

Getting Started

Describe your current infrastructure situation or your requirements if you're starting from scratch. We'll design the right architecture for your specific needs and give you a clear picture of what it will cost to build and run.