Cloud Operations — a run function for your platform team
SRE-style operations, release management and reliability engineering.
- CI/CD Pipelines
- Infrastructure as Code
- Container Orchestration
- Environment Management
- Release Automation
- Observability
- 4×
- Faster deployment frequency
- 80%
- Reduction in deployment failures
- IaC -first
- All infra managed as versioned code
- 24/7
- Cloud operations coverage
Overview
Cloud Operations is ITNS-Global's fully managed cloud operations and DevOps engineering service — a monthly engagement that takes ownership of your CI/CD pipeline, Infrastructure as Code estate, container orchestration layer, environment management, and release automation, so your engineering team can concentrate entirely on building product rather than operating infrastructure.
The gap between organisations that ship software efficiently and those that struggle is rarely engineering talent — it is operational infrastructure. Teams without mature DevOps practices spend disproportionate time on manual deployment steps, environment inconsistencies, flaky pipelines, undocumented infrastructure, and production incidents caused by releases that were not adequately tested or gradually rolled out. Cloud Operations eliminates this gap.
ITNS-Global's cloud operations engineers manage your entire DevOps infrastructure layer — designing and operating CI/CD pipelines that automate testing and deployment, converting manual infrastructure management to Infrastructure as Code using Terraform or equivalent tooling, configuring and operating Kubernetes or container orchestration for application workloads, managing multiple environments (development, staging, production) with environment parity, and implementing progressive delivery strategies that reduce deployment risk.
The observable outcomes of a mature Cloud Operations practice are clear: faster deployment frequency, significantly lower change failure rates, shorter lead time from code commit to production, and dramatically faster recovery when incidents do occur. These are the four DORA metrics that distinguish elite software delivery organisations from average ones — and Cloud Operations is designed to move your team toward the elite category.
What it includes
CI/CD Pipeline Management
End-to-end CI/CD pipeline design, implementation, and ongoing operation — automated build triggers on code commit, unit and integration test execution gates, static code analysis and security scanning, containerised build environments, artifact management, and multi-stage deployment workflows with environment-specific approval gates. Pipeline reliability monitored continuously; flaky tests identified and remediated; build times optimised to keep the feedback loop tight for development teams.
Infrastructure as Code (IaC)
All cloud infrastructure defined, versioned, and managed as code using Terraform, Pulumi, or AWS CDK — eliminating manual console changes, configuration drift between environments, and undocumented infrastructure that makes onboarding and disaster recovery fragile. IaC modules structured for reusability and environment parameterisation. Infrastructure changes follow the same peer review and testing process as application code — pull request, review, plan, apply — with full audit trail of every change.
Container Orchestration
Kubernetes cluster management or AWS ECS/Fargate operations — cluster provisioning and configuration, workload deployment via Helm charts, horizontal pod autoscaling, resource requests and limits tuning, namespace isolation, ingress configuration, service mesh integration where required, and cluster upgrade management. Container image security scanning integrated into the build pipeline. Health of running workloads monitored continuously with restart and self-healing policies configured.
Environment Management & Parity
Development, staging, and production environments managed with configuration parity — eliminating the "works in staging, fails in production" class of incidents caused by environment inconsistency. IaC parameterisation ensures environment differences are explicit and intentional rather than accidental. Environment provisioning automated so new environments for feature branches or load testing can be spun up and torn down on demand without manual configuration effort from the development team.
Release Automation & Progressive Delivery
Automated release pipelines with progressive delivery strategies — canary deployments that route a small percentage of traffic to the new version, blue-green deployments enabling instant rollback, and feature flag integration for controlled feature rollouts decoupled from code deployment. Deployment risk reduced dramatically by replacing full-fleet immediate deploys with staged rollouts that expose issues at small blast radius before full production promotion. Rollback capability maintained and tested for every release.
Observability Stack Management
Full observability stack configured and operated — metrics (Prometheus, CloudWatch, Azure Monitor), logs (ELK Stack, CloudWatch Logs, Loki), and traces (Jaeger, AWS X-Ray, Datadog APM). Dashboards built for engineering team, operations team, and executive view. Alert thresholds calibrated to meaningful signals, reducing alert fatigue while ensuring genuine issues are surfaced promptly. Observability coverage reviewed quarterly to identify instrumentation gaps as the application evolves.
DevSecOps & Security Scanning
Security integrated into the pipeline rather than applied as a post-deployment audit — static application security testing (SAST) on every pull request, dependency vulnerability scanning (SCA) catching vulnerable packages before they reach production, container image scanning for OS and application vulnerabilities, Infrastructure as Code security scanning (tfsec, Checkov) catching cloud misconfiguration before apply, and secrets scanning preventing credentials from being committed to source control.
Monthly DORA Metrics & DevOps Health Report
Monthly reporting against the four DORA metrics — deployment frequency, lead time for changes, change failure rate, and mean time to recovery — plus pipeline reliability statistics, build time trends, and environment stability indicators. DORA metrics provide the industry-standard benchmark for DevOps performance, enabling your engineering leadership to track improvement objectively and compare your delivery performance against industry quartile benchmarks.
What changes for you
4 ×
Deployment Frequency
Automated pipelines with progressive delivery reduce deployment risk to the point where frequent releases become the safe choice rather than the risky one. Teams under Cloud Operations typically increase deployment frequency 3–5× within 6 months — shipping improvements to customers faster without increasing incident rate.
80 %
Fewer Deployment Failures
Pipeline quality gates, security scanning, canary deployments, and automated rollback consistently reduce change failure rates by 70–85%. Organisations that deploy manually, without testing gates or progressive rollout, carry 5–10× the deployment failure rate of teams with mature CI/CD practices.
IaC -first
No Configuration Drift
All infrastructure defined as code eliminates the configuration drift that causes "works in staging, fails in production" incidents. Every environment is reproduced from the same Terraform modules — differences are explicit, versioned, and intentional rather than accumulated through manual console changes that no one documented.
↓ MTTR
Faster Incident Recovery
Blue-green deployments and canary strategies mean rollback is a 30-second operation, not a 2-hour reversal of manual changes. Full observability with distributed tracing reduces time to root cause identification during incidents — engineers see exactly where an error originated rather than trawling through logs manually.
0 toil
Engineering Time Reclaimed
Manual deployment steps, environment setup tasks, and infrastructure provisioning that consume engineering time are automated entirely. DORA research shows elite engineering teams spend less than 20% of time on toil; average teams spend 40–50%. Cloud Operations moves your team toward the elite end of that distribution.
✓ sec
Security Shifted Left
Security vulnerabilities caught in the CI pipeline at pull request stage cost a fraction of what they cost to remediate after deployment. DevSecOps integration means your development team receives security feedback in their normal workflow — not as a separate audit that arrives weeks after the code was written and the context forgotten.
Pricing
Indicative pricing, shown so you can judge fit before talking to anyone. Final scope and cost are confirmed in writing after a short discovery call.
Operations Retainer
Monthly retainer
€3,200 per month
- Release and change management
- SLO definition and error budgets
- Capacity and performance engineering
- Incident command and postmortems
- Runbook and documentation ownership
- Monthly reliability review
Prices exclude applicable taxes and any third-party licence fees, which are billed to you directly by the vendor so you keep ownership and visibility.
Where it has been used
Client outcome
8× deployment frequency — 4hr manual to 12min automated
Client outcome
0 environment-difference incidents in 60 days post-IaC implementation
Client outcome
CVSS 9.1 auth bypass vulnerability caught in pipeline — pre-production
Client outcome
5% blast radius — canary auto-rolled back before full-fleet impact
How delivery runs
-
01
Code Commit
Developer pushes code; CI pipeline triggered automatically
-
02
Build & Scan
Build, test, SAST, SCA, container scan — gates enforced
-
03
Staging Deploy
Automated staging deployment; integration tests; approval gate
-
04
Canary Release
Production canary at 5–10%; metrics monitored; auto-rollback ready
-
05
Full Promotion
Traffic shifted 100%; observability confirms health; release closed
Specifications
| CI/CD Platforms | GitHub Actions GitLab CI Jenkins CircleCI AWS CodePipeline Azure DevOps |
|---|---|
| IaC Tooling | Terraform Pulumi AWS CDK — IaC module library; peer review enforcement; state management |
| Container Orchestration | Kubernetes (EKS/AKS/GKE) AWS ECS/Fargate — Helm chart management; autoscaling; cluster upgrades |
| Progressive Delivery | Canary deployments; blue-green deployments; feature flags (LaunchDarkly, AWS AppConfig compatible); automated rollback |
| DevSecOps Scanning | SAST (Semgrep, SonarQube); SCA (Snyk, Dependabot); container scanning (Trivy, Snyk); IaC scanning (tfsec, Checkov); secrets (GitGuardian) |
| Observability Stack | Metrics: Prometheus/Grafana, CloudWatch, Datadog. Logs: ELK, Loki, CloudWatch Logs. Traces: Jaeger, AWS X-Ray, Datadog APM |
| Environment Management | Dev, staging, production parity via IaC parameterisation; on-demand ephemeral environments for feature branches |
| DORA Metrics Tracked | Deployment frequency; lead time for changes; change failure rate; mean time to recovery — monthly benchmark reporting |
| Cloud Platforms | AWS, Azure, GCP — single-cloud and multi-cloud environments; hybrid on-premise/cloud supported |
| Reporting | Monthly: DORA metrics, pipeline reliability, deployment log, security scan summary, environment health, cost optimisation actions |
| Engagement Scoping | Scoped per number of pipelines, services, environments, and container workloads; toolchain onboarding included |
| Cloud Costs | Cloud infrastructure costs billed directly by provider; Cloud Operations fee covers engineering operations only |
Questions people ask
How is this different from Managed Cloud?
Managed Cloud keeps the infrastructure healthy. Cloud Operations takes on the run function for the application platform itself — releases, service level objectives, capacity planning and incident command. It suits teams shipping frequently to production.
Do you replace our engineers?
No. It complements an engineering team by taking operational load off them so they can build. Most clients keep product engineering in-house and outsource the run function.
What reliability targets do you work to?
Service level objectives are defined jointly per service, with error budgets that govern release pace. Targets are set from what the business actually needs, not a blanket number.
How are incidents handled?
A defined incident command process with severity levels, a communications path, and a blameless postmortem with tracked actions after every significant incident.
Is there a minimum term?
Three months, because reliability work takes at least one full cycle before improvements are measurable.