Cloud and DevOps services that make releases boring and incidents short
We build the platforms your applications run on: landing zones, Kubernetes clusters, GitOps pipelines, observability and the resilience tests that prove a system will survive a bad day. Our engineers have run multi-environment GKE platforms, load-tested systems to 200,000 concurrent users and clustered live ERP servers for high availability. The same people then hand the platform to your team with runbooks they can follow.
The business challenge is friction nobody owns
Manual releases, environments that drift apart, cloud bills nobody can explain and monitoring that alerts after the customer has already called. Each problem sits between teams, so each is nobody's job. Fixing them requires coordinated changes across applications, platform, security and operations, and a plan that keeps production stable while the change happens.
The second challenge is scale mismatch. A startup pattern copied into an enterprise collapses under compliance and multi-team load; an enterprise pattern imposed on a small team buries it in process. We size the platform to your team and your regulator, and we tell you when Kubernetes is more than you need.
What are cloud and DevOps services and why do they matter?
Cloud and DevOps services cover the design and operation of the environment software runs in, and the automation that moves code from a developer's laptop to production safely. Done well, they shorten lead time, cut change failure rate and make recovery a rehearsed procedure rather than a scramble. Those are the four DORA measures we track, and they apply whether the target is Azure, AWS, Google Cloud or your own data center.
It matters because every AI model, data pipeline and application we build depends on this layer. A forecasting model with no deployment pipeline is a notebook. A document pipeline with no observability fails silently. That is why our data engineering and application teams work with the same platform engineers who deliver this service.
Our cloud engineering and DevOps services
Six services, delivered as a program or picked individually where you already have the rest.
Cloud assessment and architecture
Workload suitability, resilience targets, identity, networking and the data residency rules of your regulator, written into a target architecture with the trade-offs stated.
Cloud migration and modernization
Phased application and data migration with validation gates and rollback at each wave, including lift-and-shift where that is the honest answer and re-platforming where it pays.
CI/CD and DevOps automation
Repeatable build, test, release and deployment pipelines with approval gates, GitOps delivery through ArgoCD, and promotion across dev, test and production from one source of truth.
Containers and platform engineering
Kubernetes platforms on GKE, AKS or EKS when complexity and scale justify them, with a two-cluster topology that separates non-production from production and shared services from tenants.
Infrastructure as code
Reviewable, version-controlled infrastructure in Terraform or Bicep with reusable modules, so an environment can be rebuilt from the repository rather than from memory.
Observability, security and FinOps
Grafana and Prometheus dashboards, centralized logs and traces, access policies, recovery procedures and per-service cost visibility, so operations can see what is happening and what it costs.
Enterprise use cases drawn from our own delivery
Each pattern below describes work we have delivered, written generically. Client names are withheld by agreement.
Multi-environment Kubernetes with central observability
A dev, test and production GKE estate on a two-cluster topology, with one Grafana and Prometheus stack monitoring Cassandra, Kafka and cloud storage across all environments and ArgoCD promoting releases between them.
Load testing before a public launch
Load tests to 200,000 concurrent users against a Kubernetes platform, exposing autoscaling limits, database connection ceilings and cache behavior before customers did.
High availability for a live ERP
A two-node Hyper-V failover cluster for a production Dynamics AX application server, separated from the SQL tier, so patching and hardware faults no longer meant downtime.
Infrastructure monitoring across remote sites
A monitoring platform using Telegraf agents, EMQX MQTT ingestion, TimescaleDB storage and Zabbix proxies for sites in the GCC with constrained connectivity. Built for energy and utilities operators.
Infrastructure security hardening
Cybersecurity remediation across RHEL server estates, including SSH hardening, agent remediation and access policy clean-up, with evidence packs for the client's audit team.
Cloud spend monitoring and optimization
Per-service cost allocation, right-sizing recommendations and scheduled shutdown of non-production environments, reported monthly against a budget the finance team agreed.
How we deliver in seven steps
Every engagement begins with a scope agreement, risk assessment, architecture review and proof of value. Pilots progress to full engineering only when performance, integration and ownership are clear.
- 01
Cloud assessment
Workloads, dependencies, compliance constraints and the current cost baseline.
- 02
Target architecture
Accounts, networks, identity, environments and the services each workload needs.
- 03
Landing zone
Guardrails, policies and shared services deployed from code before any workload moves.
- 04
Infrastructure automation
Terraform or Bicep modules, pipelines and GitOps delivery for every environment.
- 05
Workload migration
Wave-by-wave moves with validation, performance checks and rollback at each gate.
- 06
Resilience tests
Load, failover and recovery drills that prove the objectives on paper hold in practice.
- 07
Operations handover
Runbooks, dashboards, alert tuning and on-call training for your team.
Business outcomes and how we measure them
We track deployment frequency, lead time for changes, change failure rate and time to restore, alongside availability against your recovery objectives, incident trends and unit cost per transaction or per user. The baseline is measured in the assessment and reported after each phase, so improvement is visible rather than asserted.
Where we deliver. In India, platforms are built for RBI and SEBI cyber frameworks and the DPDP Act 2023 data residency rules. In UAE, we design for UAE PDPL and the in-country hosting that government and financial clients require. In Saudi Arabia, NCA ECC-2:2024 controls and SDAIA's PDPL shape region choice, logging and access design. In United States, we build pipelines and controls that stand up to SOC 2 audits your customers request. Our locations cover each market.
Security, governance and quality built into the platform
Least-privilege identity, approved environments, reviewable infrastructure changes and test evidence are properties of the platform, not tasks for each application team. Secrets are vaulted, images are scanned, policies are enforced at admission, and every change to production passes through the same pipeline with the same approvals.
Regulated or sensitive workloads also receive specialist legal, security and compliance review. Where cryptography is in scope, we coordinate with our post-quantum cryptography team so certificate and key management is designed for the algorithm changes regulators have already scheduled.
Why Constient for cloud and DevOps
Three habits from the engineers who run these platforms.
Platform for AI and data, not just apps
Our clusters host the model serving, feature pipelines and lakehouse jobs our own AI teams ship, so GPU scheduling and data locality are solved problems.
We test the bad day
Load tests, failover drills and recovery rehearsals are in the plan from the start, because an untested recovery objective is a guess.
Handover is the deliverable
Runbooks, dashboards and on-call training for your team are scoped and priced, not left to the last sprint.
Frequently asked questions
Which cloud provider should we choose, and are you tied to one?
We work on Azure, AWS and Google Cloud and have no commercial reason to prefer one. The choice follows your workloads, existing contracts, team skills, in-country region availability and cost. For GCC clients, local region availability and data residency usually narrow the field quickly; we write that analysis into the assessment.
Is Kubernetes always the right answer?
No. Managed container services, serverless or well-run virtual machines suit many workloads better and cost less to operate. We recommend Kubernetes when you have many services, several teams deploying independently or workloads that need the scheduling it provides. When a simpler platform fits, the assessment says so.
How does a cloud and DevOps engagement start?
With a 2 to 3 week assessment: workloads, dependencies, compliance constraints, current cost and the DORA baseline. You receive a target architecture, a migration or platform plan with waves and gates, and a fixed-price or team proposal. Contact us to schedule it.
Can migration happen gradually while we keep operating?
Yes, and we recommend it. Workloads move in waves with validation and rollback at each gate, and the landing zone is in place before the first wave so every workload lands on the same guardrails. Hybrid connectivity keeps on-premises and cloud systems talking during the transition.
Where does our data stay during and after migration?
In the region you specify, with residency confirmed in writing before the first byte moves. Logs and metrics also stay in-region where regulation requires it. For Saudi, UAE and Indian clients we default to in-country regions and design the observability stack so no telemetry leaves the jurisdiction.
What is the commercial model and what happens after handover?
Assessment is fixed-price. Platform builds and migrations are fixed-scope by wave or run as a dedicated platform team billed monthly. After handover you can run the platform yourself, keep an advisory retainer or contract managed operations with defined response times.
Build your cloud engineering and DevOps roadmap
Share your use case, operating constraints and target outcome. We will start with a focused technical and business conversation about what to migrate, what to automate and what to leave where it is.