Cloud & DevOps
AWS, Azure, GCP guidance. CI/CD pipelines, containerization, Kubernetes, and infrastructure as code.
About this service
Transform your infrastructure with modern cloud and DevOps practices. We help you leverage AWS, Azure, or GCP to build reliable, scalable, and cost-effective infrastructure that accelerates your development cycles.
Modern Infrastructure for Modern Software Teams
Cloud Migration Strategy — The 7 R's
Not every workload migrates the same way. We evaluate each application against seven migration strategies and recommend the one that balances speed, cost, and risk.
| Strategy | Description | When to Use |
|---|---|---|
| Rehost | Lift and shift to cloud VMs with minimal changes | Quick wins, datacenter exits, legacy apps with tight deadlines |
| Replatform | Lift and reshape — minor optimizations during migration | Database migrations to RDS, switching to managed services |
| Repurchase | Replace with a SaaS or cloud-native equivalent | Legacy CRM to Salesforce, on-prem email to cloud-hosted |
| Refactor | Re-architect for cloud-native patterns (containers, serverless) | Core revenue apps, high-scale workloads, competitive differentiators |
| Retire | Decommission applications no longer needed | Redundant systems, unused tools, end-of-life software |
| Retain | Keep on-premises for now, migrate later | Compliance restrictions, hardware dependencies, pending EOL |
| Relocate | Move to cloud without changes using VMware Cloud or similar | VMware-heavy environments, hybrid cloud strategies |
CI/CD Pipeline Architecture
A well-designed pipeline is the backbone of rapid, reliable delivery. Every commit flows through automated quality gates before reaching production.
Example: GitHub Actions CI/CD Pipeline
name: Deploy Pipeline
on:
push:
branches: [main]
jobs:
build-and-test:
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/setup-node@v4
with:
node-version: '20'
- run: npm ci
- run: npm run lint
- run: npm run test -- --coverage
- run: npm run build
security-scan:
needs: build-and-test
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- run: npx audit-ci --critical
- uses: aquasecurity/trivy-action@master
with:
scan-type: 'fs'
severity: 'CRITICAL,HIGH'
deploy-staging:
needs: security-scan
runs-on: ubuntu-latest
environment: staging
steps:
- run: aws ecs update-service --force-new-deployment
deploy-production:
needs: deploy-staging
runs-on: ubuntu-latest
environment:
name: production
url: https://app.example.com
steps:
- run: aws ecs update-service --force-new-deploymentContainer Orchestration
The journey from Docker Compose on a single server to managed Kubernetes at scale. We help you choose the right level of orchestration for your team size and workload.
| Service | Best For | Complexity | Cost Model |
|---|---|---|---|
| Docker Compose | Dev environments, single-server deployments, small teams | Low | EC2/VPS hosting cost only |
| Amazon ECS | AWS-native teams, simpler orchestration needs | Medium | Per-task pricing, no control plane cost |
| Amazon EKS | Large-scale production, multi-team environments, portability | High | $0.10/hr control plane + node costs |
| AWS Fargate | Serverless containers, variable workloads, no node management | Low | Per vCPU/memory per second |
Our recommendation path:
Start with Docker Compose for development and single-server production. Move to ECS + Fargate when you need auto-scaling and zero-downtime deployments. Graduate to EKS only when you have the team size and multi-service complexity to justify it.
Infrastructure as Code Comparison
Infrastructure as Code eliminates configuration drift and makes your infrastructure reproducible. Here is how the major tools compare.
| Feature | Terraform | AWS CDK | Pulumi | CloudFormation |
|---|---|---|---|---|
| Language | HCL (domain-specific) | TypeScript, Python, Java, Go | TypeScript, Python, Go, C# | YAML / JSON |
| State Management | Remote backends (S3, Terraform Cloud) | CloudFormation manages state | Pulumi Cloud or self-managed | AWS-managed automatically |
| Multi-cloud | Excellent | AWS only | Excellent | AWS only |
| Learning Curve | Medium (new language) | Low (if you know TypeScript) | Low (familiar languages) | Medium (verbose YAML) |
| Community | Largest | Growing fast | Moderate | Mature but static |
We use AWS CDK (TypeScript) for this platform.
CDK lets us define infrastructure with the same language as our application code, enabling shared types, unit tests, and IDE autocomplete for cloud resources.
Observability Stack — The Three Pillars
You cannot improve what you cannot see. A mature observability practice combines three complementary pillars to give full visibility into system behavior.
Discrete events that tell you what happened.
- ELK Stack (Elasticsearch, Logstash, Kibana)
- AWS CloudWatch Logs
- Fluentd / Fluent Bit
Numeric measurements that tell you how things are performing.
- Prometheus + Grafana
- AWS CloudWatch Metrics
- StatsD / Datadog
Request paths that tell you where time is spent.
- OpenTelemetry (vendor-neutral)
- AWS X-Ray
- Jaeger / Zipkin
Integration: How the three pillars connect
Application Code
|
+-- stdout/stderr ------> Fluent Bit --> CloudWatch Logs --> Kibana
| |
+-- metrics endpoint ----> Prometheus --> Grafana Dashboards <--+ (correlated)
| |
+-- trace context -------> OpenTelemetry --> X-Ray / Jaeger <----+
Collector
|
All three link via
trace_id / request_idCost Optimization Strategies
Cloud bills grow silently. We implement a continuous cost optimization practice that typically reduces cloud spend by 25-40% without sacrificing performance.
| Strategy | Description | Typical Savings |
|---|---|---|
| Right-sizing | Analyze CPU/memory utilization and downsize over-provisioned instances | 20-30% |
| Reserved Instances / Savings Plans | Commit to 1-3 year usage for predictable workloads | 30-60% |
| Spot / Preemptible Instances | Use interruptible compute for batch jobs, CI/CD, and stateless workers | 60-90% |
| Auto-scaling | Scale in during low-traffic periods, scale out for peak demand | 15-25% |
| Storage Tiering | Move infrequently accessed data to S3 Glacier, Infrequent Access tiers | 40-70% |
| CDN Caching | Serve static assets from CloudFront edge locations, reduce origin load | 10-20% |
Our approach:
- Set up AWS Cost Explorer and budget alerts on day one
- Tag every resource for cost attribution by team and project
- Review cost reports weekly during the first quarter, monthly after
- Automate unused resource cleanup with Lambda-based sweepers
The Key Insight
DevOps is not a team or a tool — it's a culture of shared responsibility between development and operations that accelerates value delivery.
Ready to modernize your infrastructure and accelerate delivery? Contact admin@innosaid.com to discuss your cloud and DevOps needs.
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