Iniksha Technologies plans and runs cloud migrations across AWS, Azure and Google Cloud, then manages what we moved. Assessment before migration, a cutover plan with a rollback path, and monitoring from day one. Infrastructure should be the least interesting part of your week.
Hardware is ageing, the AMC is due, and one power event away from a very bad week.
Nobody can point to which workload is responsible. Cloud cost optimisation typically recovers a meaningful share of spend within the first quarter.
Manual steps, a nervous engineer, and a window on Saturday night. That is a CI/CD problem with a known fix.
No monitoring, no alerting, no dashboards.
An untested backup is a belief, not a backup.
Consider it a pre-mortem. Cheaper than the post-mortem.
We inventory what you run, map dependencies, and classify each workload: rehost, replatform, refactor, retire. Output is a written cloud migration strategy with sequencing, effort, projected monthly run cost and identified risk, before anything moves.
Landing zone and account structure, VPC and networking, EC2, ECS and EKS, RDS and Aurora, S3 with lifecycle policies, IAM least-privilege design, and cost controls set up at the start rather than after the first shocking invoice.
Subscription and resource group design, Azure VMs and App Service, AKS, Azure SQL, Entra ID integration, networking and private endpoints, and Azure Monitor configured against real alert thresholds.
Project and IAM structure, Compute Engine, Cloud Run and GKE, Cloud SQL, Cloud Storage, VPC design, and Cloud Monitoring wired to the services that actually matter.
Containerising applications that were never designed for it, cluster setup and hardening, autoscaling, resource limits, and Helm-based deployments. Where Kubernetes is overkill, we say so and use something simpler.
Automated build, test and deployment pipelines in GitHub Actions, GitLab CI or Jenkins. Infrastructure as code with Terraform. Environment parity between development, staging and production, so "it worked locally" stops being a sentence anyone says.
Grafana, Prometheus, CloudWatch and Sentry configured to page a human when something is genuinely wrong, and to stay quiet otherwise. Alert fatigue is a reliability risk in its own right.
Automated backups with defined retention, documented RPO and RTO targets, cross-region copies where the risk justifies them, and restore drills. We test the restore. That is the whole point.
Least-privilege IAM, network segmentation, secrets management, encryption at rest and in transit, patching policy, and audit logging that will survive a customer's security questionnaire.
Right-sizing, reserved and spot capacity where the workload suits it, storage tiering, orphaned-resource cleanup, and per-team cost tagging so spending has an owner. Findings come with rupee figures and the trade-off spelled out.
Monthly management of what we built or inherited: patching, capacity review, cost review, incident response and a monthly report you can forward to your board without editing.
Every server, service, database, cron job and forgotten dependency catalogued, including the one machine under a desk that turns out to run payroll.
Target architecture, migration sequence, projected monthly cost, and a rollback plan for each wave. Delivered as a written document you can circulate internally.
Accounts, networking, identity, security baseline and monitoring set up properly before any workload lands. Retrofitting this later is where migrations go wrong.
One low-risk workload moves first. It proves the approach, exposes the surprises and calibrates the estimate while the stakes are low.
Remaining workloads move in planned waves, each with validation, a defined cutover window and a rollback path. Business hours are protected.
Post-migration tuning, cost review, documentation, runbooks and knowledge transfer to your team, plus an ongoing management retainer if you want one.
Cloud engagements are quoted against the inventory from discovery: workload count, data volume, integration complexity and how much of the stack needs refactoring rather than rehosting.
Two things worth knowing before you budget:
A single application typically moves in 2-4 weeks including testing. A full data-centre exit with dozens of workloads usually runs 3-6 months in waves. Discovery gives you a sequenced plan with dates rather than an estimate.
For most workloads, minutes rather than hours, and scheduled. Where zero downtime is a requirement, we use replication and cutover patterns that achieve it, at higher complexity and cost. You decide which trade-off you want after we price both.
It depends on your existing stack, your team's skills, your compliance requirements and the commercial terms on offer. If you already run Microsoft identity and licensing, Azure usually wins on total cost. If you need breadth of managed services, AWS usually wins. We are not a reseller for any of them, so the recommendation follows your situation.
Often, yes. A cost optimisation review is a standalone engagement: we analyse usage, identify savings, and give you a prioritised list with rupee figures and the risk of each change. You can implement it yourself or have us do it.
Yes. IT infrastructure management services on a monthly retainer: monitoring, patching, incident response, capacity and cost review, with defined response times and a monthly report.
Infrastructure is defined as code and documented, so you are not architecturally trapped. Where a managed service creates genuine lock-in, we flag it during design and price the alternative.
Before anything moves, you get an inventory, a target architecture, a projected run cost and a risk list. If the assessment says stay where you are, that is what it will say.
