AWS development services for teams that need the broadest cloud platform — without drowning in its complexity. Graviton for 40% better price-performance. Lambda that doesn't cold-start on the critical path. EKS configured for your workload, not copied from a blog post. We build on AWS with the cost discipline and operational maturity that separates a cloud-native product from an expensive VM rental.
Why Entalogics for AWS
30–40% of cloud spend is wasted on idle resources, over-provisioned instances, and zombie assets nobody remembers creating. The AWS estates we audit always have the same problems — on-demand instances running 24/7 without Savings Plans, S3 buckets in the wrong storage tier, and EKS node pools sized for peak and paying for it around the clock.
Graviton4 for 40% better price-performance on sustained compute. Spot for stateless workloads. Savings Plans covering 60–70% of baseline. We implement FinOps tagging, budget alerts, and Compute Optimizer recommendations before the first bill surprise.
Lambda for event-driven spikes. Fargate for containers without node management. EKS only when orchestration complexity is genuinely justified. EC2 only when nothing else fits. Every service choice justified by workload pattern — not by what someone deployed last time.
S3 Standard for hot data, Intelligent-Tiering for unpredictable access, Glacier for archives. Lifecycle policies moving data automatically. No petabyte sitting in Standard because nobody configured the policy.
Every resource in Terraform or AWS CDK, stored in git, deployed via GitHub Actions or CodePipeline. No manual console changes surviving past a PR. Drift detection enabled. The infrastructure is auditable because it's version-controlled.
When AWS, when not
AWS has the broadest service catalogue and the deepest ecosystem. It also has the steepest learning curve and the most ways to spend money accidentally. We'll tell you on the first call if AWS is the right fit — or if Azure or GCP serves your workload better.
PICK AWS WHEN
CONSIDER AZURE WHEN
WE SAY NO WHEN
What we build on AWS
The shapes of AWS cloud development we deliver most. Each deployed with cost controls and observability from day one.
Kubernetes with Graviton node groups, Karpenter autoscaling, Spot for non-critical workloads, and ArgoCD for GitOps deployments. EKS used deliberately — not as a default.
Event-driven compute with Lambda on Graviton2, API Gateway, SQS, EventBridge. Consumption-based pricing for variable workloads where cold starts are managed.
Control Tower, Organizations, SCPs, GuardDuty, SecurityHub. The governance foundation before the first workload — not an afterthought at audit time.
RDS, Aurora, DynamoDB, S3, Redshift, Glue. Data architecture that separates transactional and analytical workloads with cost tiering matching access patterns.
On-prem to AWS, Azure to AWS, or legacy AWS to modern AWS. Workload by workload using AWS Migration Hub with cost modelling layered on top.
GitHub Actions with AWS deployment targets, CodePipeline, or ArgoCD on EKS. Build, test, and deploy infrastructure and applications from one pipeline.
The playbook
AWS patterns from real production deployments — not re:Invent slide decks.
P01
Every resource in Terraform modules. State in S3 with DynamoDB locking. No console changes. Drift detection via Terraform Cloud or Spacelift.
P02
Graviton4 for EC2, EKS node groups, RDS, ElastiCache. ARM container images in CI. x86 only when a dependency genuinely requires it. 20–40% savings from a config change.
P03
Every resource tagged with cost centre, environment, owner. Budget alerts per account. Compute Optimizer and Trusted Advisor reviewed monthly.
P04
Karpenter provisions the right instance for the workload — not the instance you preconfigured in a node group. Spot and on-demand mixed automatically. Bin-packing that saves real money.
P05
Threat detection and security posture from day one. Not added after the first incident. Findings aggregated, prioritised, and actionable.
P06
Dev → staging → production with approval gates, canary analysis, and automated rollback. No YOLO deploys to production. No "it worked in dev."
Signature case
A B2B SaaS platform on AWS — $67k/mo, all on-demand x86 instances, EKS node groups sized for peak load 24/7, S3 Standard for everything including three-year-old logs, and no Savings Plans. Migrated to Graviton4, implemented Karpenter with Spot, applied Savings Plans to baseline, and configured S3 lifecycle policies in 8 weeks. Monthly spend dropped 43%.
Before
$67k/mo · all on-demand x86 · static EKS node groups · S3 Standard for everything · no tagging
After
$38k/mo · Graviton4 + Spot · Karpenter autoscaling · S3 lifecycle policies · full FinOps dashboard
Engagement shape
A typical AWS development engagement. We deploy workload by workload — the current infrastructure stays live while we work.
Two senior AWS architects. Cost analysis, security posture review, resource tagging audit, Compute Optimizer review. A ranked, dollarized RFC.
Terraform landing zone deployed, SCPs enforced, first production workload live with monitoring and cost tagging. Real cost data in your dashboard.
Each workload deployed or migrated with Graviton, right-sized compute, proper storage tiering, and GuardDuty enabled. Your product keeps running.
FinOps dashboard live. Security posture green. Runbook handed to your team — or we stay on retainer.
Stack
Our default AWS cloud development stack — picked for production, not certification exams.
Engagement
No hourly retainer that bills for "thinking time." Pick a lane that matches your stage; everything is fixed-quote or transparently rated.
A defined scope, a fixed price, a senior-only team. From landing zone to production workloads in 8–14 weeks.
$15k–$30k
FIXED SCOPE
Embedded engineers in your Slack, your standups. Senior cloud architects and DevOps engineers. Pause, resize, end with 30 days' notice.
$5k / eng / mo
PER ENGINEER
A long-term partner for enterprise cloud — landing zone governance, cost optimisation, security posture, migration roadmap, hiring help.
custom
PROCUREMENT-FRIENDLY
Founder-direct
Thirty minutes with the founder. We'll bring a senior AWS architect, the relevant playbook, and a candid read on whether AWS is the right cloud — or whether Azure or a multi-cloud approach fits your workload better.
