IDOWS Apex builds and runs workloads on AWS - architecture, migration, and the operational work that follows. Our recommendations come from what we have had to keep running in production: the IAM policy that was too broad, the instance family that was wrong for the workload, the bill that grew without anyone deciding it should.
IDOWS Apex builds and runs workloads on AWS - architecture, migration, and the operational work that follows. Our recommendations come from what we have had to keep running in production: the IAM policy that was too broad, the instance family that was wrong for the workload, the bill that grew without anyone deciding it should.
Solving complex industry challenges with AWS
We build high-security, compliant financial platforms on AWS, ensuring data privacy and high-speed transaction processing, backed by our DevSecOps practices at every deployment stage.
Enabling global scale with auto-scaling architectures and high-performance content delivery networks (CloudFront).
Cloud architecture designed around HIPAA safeguards for patient data, with database administration tuned for auditability and uptime.
Multi-tenant architectures built for infinite scalability and reliable performance across global regions.
Low-latency video streaming and large-scale asset management using AWS Media Services and S3.
Helping government agencies modernize legacy infrastructure with secure cloud services, supported by our cloud infrastructure teams for on-premise to cloud handoffs.
Why brands trust us with their cloud infrastructure
Auto-scaling groups and managed services adjust capacity to real-time demand instead of provisioning for peak.
Multi-layered security controls built on AWS-native services, configured with your compliance requirements in mind.
Pay only for what you use with advanced cost-saving strategies and automated scheduling.
Deploy your applications in minutes across multiple AWS regions for low-latency user experiences.
Resilient architectures with automatic failover and data redundancy across Availability Zones.
Focus on your core business while we handle the complexity of cloud management and tools.
How the work actually runs, from first conversation through to what happens after launch.
Assessment of existing infrastructure and business goals for cloud transformation.
Developing a tailored AWS roadmap focusing on security, scalability, and cost.
Designing robust, multi-AZ architectures using AWS Best Practices and Well-Architected Framework.
Staged migration with a tested rollback path, on infrastructure provisioned from code rather than by hand.
Fine-tuning performance and optimizing costs through automated resource management.
Continuous automated monitoring, security updates, and ongoing technical support.
Built on AWS managed services, engineered through the same cloud development and DevOps practices we apply across every cloud engagement.
Serverless, containers, or instances is the decision that shapes cost, operational burden, and how portable the result is. Most production estates end up using more than one, matched to the workload rather than chosen as a house style.
Use when: Event-driven work, spiky or unpredictable traffic, and glue between services. You pay per invocation and there is no instance to patch.
Trade-off: Cold starts, execution time limits, and a debugging story that is harder than a long-running process.
Use when: Long-running services, teams already working in Docker, and workloads that need consistent runtime behaviour across environments.
Trade-off: EKS brings Kubernetes power and Kubernetes operational overhead. ECS is simpler and less portable off AWS.
Use when: Software that expects a conventional server, licensing tied to instances, or a lift-and-shift where re-architecting is not yet justified.
Trade-off: You own patching, scaling configuration, and capacity planning.
Storage choices are harder to reverse than compute choices, because migrating data is harder than redeploying code. We settle these during architecture.
Managed PostgreSQL or MySQL where transactional integrity matters. We size for real query patterns and set up automated backups and a restore that has been tested rather than assumed.
Predictable single-digit latency at scale, provided the access patterns are designed up front. DynamoDB rewards deliberate key design and punishes treating it as a relational database.
Assets, backups, data-lake storage, and static hosting, with lifecycle rules so infrequently accessed data moves to cheaper storage classes automatically.
Caching at the edge for static assets and API responses that tolerate it, which is often the cheapest available performance improvement.
Ongoing tuning, backup strategy, and query performance for these databases is covered by our database administration practice.
There are three honest routes onto AWS, and choosing between them per workload matters more than picking one for the whole estate. A migration that rehosts the urgent things and refactors the valuable ones usually beats a programme that insists on a single approach.
Move the workload substantially as-is onto EC2. Fastest route off a data centre and the least disruptive, but it inherits the existing architecture and usually the existing cost profile.
Move with targeted changes - a self-managed database onto RDS, a file share onto S3 - taking the managed-service wins without a rewrite. This is where most engagements land.
Re-architect around AWS-native services. The largest gain and the largest risk, so we scope it per bounded subsystem rather than as a single programme.
We plan cutovers in phases with a rollback path at each stage. Where the source is an aging on-premise system that cannot be changed safely, legacy modernization comes before the migration rather than during it. For the platform-neutral view of this work, see our cloud engineering guide.
Most AWS problems we are called into are operational rather than architectural - an environment nobody can reproduce, an alert nobody trusts, or a bill nobody can attribute.
Environments defined in Terraform or CloudFormation and applied through a pipeline, so staging genuinely resembles production and changes are reviewable before they are applied.
CloudWatch metrics, structured logs, and alerting tied to conditions that actually indicate a problem, so on-call attention goes to signal rather than noise.
Right-sizing, storage lifecycle policies, and commitment planning where usage is stable enough to justify it. Savings depend entirely on your starting configuration - we report what we find rather than promising a figure in advance.
AWS Organizations with production separated from staging and development, plus VPC design and segmentation, so a mistake in one environment cannot reach another.
The pipeline and automation side of this is our DevOps practice; the connectivity underneath it is DevOps engineering.
AWS operates on a shared responsibility model: Amazon secures the infrastructure, and everything you configure on top of it is yours. In practice the incidents that matter come from that second half - over-broad IAM policies, a storage bucket opened for a one-off and never closed, credentials in a repository, security groups that accumulate rules nobody can justify.
We work to least privilege on IAM roles, keep production network paths explicit rather than permissive, hold secrets in a managed secrets store, and enable encryption at rest and in transit by default. Where an organization needs to satisfy a specific framework, we map infrastructure controls to its requirements as part of the design.
To be direct about the boundary: we are not an AWS Partner Network member, we hold no company certification, and we do not offer certified compliance, guaranteed uptime, or guaranteed cost savings. What we offer is engineering that takes those requirements seriously, and a direct conversation about your data residency, access control, and audit requirements during scoping rather than a checklist after the fact.
This page covers AWS specifically. If you have not settled on a provider yet, the platform-neutral view is cloud development - we build on Azure and Google Cloud as well, and the right answer depends on your workloads, existing licensing, and where your team's experience already sits. Where the application itself is being built rather than only hosted, that work is custom software development, and connecting it to systems outside AWS is integrations.
Deep technical analysis, architectural case studies, and strategic perspectives from our senior development teams.
Agile works beautifully for small teams. When the enterprise gets involved, scaling agile isn't about doing more agile - it's a different problem.
Choosing the wrong development partner is an expensive mistake. Here's how to approach the selection process in a way that actually predicts success.
Every growing business faces the same decision: buy off-the-shelf or build custom? It's a strategic choice with massive consequences for your bottom line.
Related work that often sits alongside this one in the same engagement.