GitHub Actions
Terraform
AWS CloudFormation
Docker
Kubernetes
Google Cloud
Cloudflare
Prometheus
Grafana“Our business went from local to national thanks to Hoop. They completely transformed our e-commerce platform and helped us expand our customer base 5x. The results speak for themselves.”
Cloud & DevOps Services
Cloud & DevOps Services — ship faster, break less.
We build CI/CD pipelines, Kubernetes clusters, Terraform IaC, and GitOps workflows — so your team deploys multiple times per day with zero downtime and infrastructure that costs less as it scales.
Trusted by 2,000+ businesses worldwide
973×Elite teams deploy more often (DORA 2024)
$66BDevOps market by 2033
75%of enterprises run containers in production
81%of GitOps adopters report higher reliability
Overview
Infrastructure that ships your product, not your engineers.
Engineering teams spend 20–30% of their time on manual infrastructure tasks — provisioning servers, debugging deployment failures, fixing environment mismatches, and waiting on release approvals. That time is lost product velocity. Every hour spent on infrastructure toil is an hour not spent building features your customers pay for.
We design and implement the DevOps infrastructure that eliminates that toil: CI/CD pipelines with automated testing and container builds, Infrastructure as Code with Terraform so every environment is reproducible from a git commit, Kubernetes orchestration for auto-scaling and zero-downtime deployments, and GitOps workflows with ArgoCD so infrastructure changes go through the same review process as application code.
We also implement DevSecOps (security embedded in pipelines via Trivy, Snyk, and Vault), observability (Prometheus, Grafana, Datadog), and FinOps (cloud cost governance so your bill scales with revenue, not waste). Every engagement is measured against DORA metrics: deployment frequency, lead time for changes, MTTR, and change failure rate.
- Greenfield setup
- Full DevOps stack from scratch for new products and teams.
- CI/CD modernisation
- Replace Jenkins, manual deployments, or broken pipelines.
- Cloud migration
- Move from on-premise or single-cloud to cloud-native.
- Cost optimisation
- FinOps audit and right-sizing to cut cloud bills 30–50%.
4 DevOps pillars we implement.
Each pillar addresses a different dimension of delivery speed, reliability, security, and cost.
Foundation · Always First
CI/CD & Automation
CI automatically runs tests on every commit; CD ships tested code to staging or production without manual steps. Together they cut lead time from days to minutes. Elite teams deploy 973× more frequently and recover 6,570× faster, per Google’s DORA 2024 research. We build pipelines in GitHub Actions, GitLab CI/CD, or CircleCI — with automated testing, Docker builds, registry pushes, and deployment to Kubernetes or cloud.
GitHub ActionsGitLab CI/CDCircleCIDockerAutomated testingDeployment gates
Reproducibility
Infrastructure as Code (IaC)
IaC defines every server, network, database, load balancer, and security group in code — versioned, reviewed, and applied automatically rather than clicked through a console. Terraform is the standard, working across AWS, GCP, and Azure. It eliminates configuration drift, makes environment reproduction trivial, and enables disaster recovery — a full environment rebuilt in minutes from code, not hours from memory.
TerraformAWS CloudFormationPulumiAnsibleNo config drift
Scale & Reliability
Kubernetes & Orchestration
Kubernetes manages containerised workloads at scale — auto-scaling pods on CPU or custom metrics, restarting failed containers, distributing traffic across healthy instances, and rolling out updates without downtime. We set up clusters on EKS, GKE, or AKS with Helm charts for deployments, ArgoCD for GitOps updates, and Horizontal Pod Autoscaler for traffic-responsive scaling.
Kubernetes (K8s)DockerHelmEKS / GKE / AKSArgoCDHPA
Visibility & Cost
Observability & FinOps
Observability covers metrics, logs, and traces — the three signals that explain why a system behaves unexpectedly, not just whether it is up. We implement Prometheus and Grafana, ELK or Loki for logs, and OpenTelemetry for tracing. FinOps applies DevOps practices to cloud cost — right-sizing instances, capping auto-scaling, tagging, and budget alerts. Cloud bills frequently drop 30–50% after a FinOps engagement.
PrometheusGrafanaDatadogOpenTelemetryAWS Cost ExplorerFinOps
9 Cloud & DevOps services we deliver.
Every layer of modern infrastructure and delivery automation — built and operated.
CI/CD pipeline design & build
End-to-end pipeline: a commit triggers automated unit and integration tests, Docker build, container security scan, staging deploy, and production release — with approval gates and automatic rollback on failure.
Infrastructure as Code (Terraform)
Full cloud environment in Terraform — VPCs, subnets, compute, RDS databases, load balancers, S3, IAM roles, and security groups — version-controlled, peer-reviewed, and applied via automated pipelines.
Kubernetes setup & management
Production cluster on EKS, GKE, or AKS — Helm chart deployment, ArgoCD GitOps, HPA auto-scaling, cluster networking, RBAC, and pod security policies.
DevSecOps integration
Security embedded in the pipeline: SAST with Snyk or SonarQube, image scanning with Trivy, secrets management with HashiCorp Vault or AWS Secrets Manager, and SBOM generation for supply-chain compliance.
Observability & monitoring
Prometheus metrics, Grafana dashboards for SLI tracking, distributed tracing with OpenTelemetry, log aggregation with Loki or ELK, and PagerDuty or incident.io alerting.
Cloud cost optimisation (FinOps)
AWS or GCP cost audit, instance right-sizing, reserved-instance and savings-plan analysis, auto-scaling tuning with cost caps, tagging strategy, and monthly spend dashboards — typically cutting cloud bills 30–50%.
Cloud migration
Migrate on-premise or legacy cloud architectures to modern cloud-native setups on AWS, GCP, or Azure — with containerisation, managed database migration, DNS cutover planning, and zero-downtime switchover.
SRE & reliability engineering
SLO definition, error-budget management, chaos engineering tests, incident response playbooks, blameless postmortems, and on-call rotation design — Google SRE practices applied to your product.
GitOps implementation
ArgoCD or Flux setup so infrastructure and config are managed entirely through Git pull requests — every change auditable, every rollback a git revert, and no one SSH-ing into production to make changes.
6 deployment strategies — when to use each.
Each reduces a different type of deployment risk — blast radius, rollback time, or traffic exposure.
Blue-Green Deployment
Two identical environments run at once — one active (blue), one idle (green). The new version deploys to green, traffic switches instantly via the load balancer, and reverts in seconds on failure. Zero-downtime, instant rollback. Best for monoliths; doubles infrastructure cost during the deploy window.
Rollback: seconds · Downtime: 0msCanary Release
The new version receives a small share of traffic — 1%, 5%, or 10% — while the old version serves the rest. If canary metrics stay healthy, traffic shifts progressively to 100%; if they degrade, the canary is pulled. Kubernetes Argo Rollouts implements this natively.
Traffic: 1% → 10% → 100%Rolling Update
Kubernetes’ default — old pods are replaced with new pods one batch at a time until all run the new version. No extra infrastructure cost, slightly slower rollback. Best for stateless apps tolerant of brief mixed-version operation during the update window.
Cost: no extra · 2–5 minFeature Flags
Deploy code to 100% of users but activate features only for specific segments — by percentage, geography, plan tier, or user ID. LaunchDarkly, Flagsmith, or Unleash manage flag state. Decouples deployment from release and allows an instant kill-switch without redeploying.
Release: decoupled from deployShadow Deployment
The new version receives a copy of all live traffic alongside the current version, but its responses are discarded — users only see the old version. Tests the new version under real production traffic patterns with zero user impact, catching regressions before the switch.
User impact: 0 · Real traffic testRecreate Deployment
All old pods terminate simultaneously, then new pods start — a brief 30–90s downtime window. The right choice for apps that cannot run two versions at once (schema migrations, licensing, incompatible stateful data). Never for public-facing production.
Downtime: 30–90s · staging onlyProof, not promises.
A complete infrastructure rebuild that cut server costs 40% and eliminated platform downtime.
Cloud Infrastructure · FastAPI · Docker · Auto-scaling · Multi-vendor Marketplace
BeesApp: an infrastructure rebuild delivered 99.9% uptime, 74% faster load, and 40% lower server costs
BeesApp's original infrastructure was a fragile mix of PHP, Django, and Vue on servers that broke under load. We rebuilt the platform on containerised FastAPI and Next.js, deployed on auto-scaling cloud infrastructure with automated deployment pipelines, health checks, and load balancing. It now absorbs traffic spikes without manual intervention, deploys without downtime, and runs at 40% lower monthly cost — serving a multi-vendor marketplace across Saudi Arabia at 99.9% uptime.
Read the case study99.9%Platform uptime
74%Faster load time
40%Lower server costs
Why Build With Hoop
DevOps that ships product, not slides.
Most DevOps engagements produce documentation, architecture diagrams, and tool installations. We produce working pipelines, measured against DORA metrics, that your team can operate from day one.
- 01
DORA metrics set as targets upfront
Deployment frequency, lead time, MTTR, and change failure rate are defined as success criteria before any tool is installed. If the engagement does not move these metrics, it has not succeeded — no matter how many pipelines we built.
- 02
Security in the pipeline, not after it
SAST, container scanning, secrets detection, and dependency checks run on every commit — not in a quarterly audit. A vulnerability found in a pipeline takes 15 minutes to fix; one found in production takes days and a post-mortem.
- 03
GitOps: everything through version control
No SSH to production. No console changes that leave no trace. Every infrastructure change is a pull request — reviewed, approved, applied automatically, and revertible in 60 seconds if it causes an incident.
- 04
Your team runs it after we're done
We document every runbook, train your engineers on the tools and workflows, and structure the systems so your team owns them — not us. You should not need us to restart a pod or rotate a secret.
How we build your DevOps stack.
A 5-phase process from infrastructure audit to a team-owned, monitored production stack.
01
Audit & DORA baseline
Measure current deployment frequency, lead time, MTTR, change failure rate, and cloud cost per environment — the baseline against which all improvements are measured.
Baseline metrics first02
IaC & environment design
Terraform modules for every environment (dev, staging, prod), VPC architecture, compute and database sizing, IAM roles, and security-group rules — all code-reviewed before apply.
No manual provisioning03
CI/CD & container setup
Pipeline stages — build, test, scan, push, deploy. Docker images for all services. Kubernetes with Helm and ArgoCD. Deployment strategy chosen (canary, blue-green, rolling) per service.
Zero-downtime from here04
Observability & FinOps
Prometheus + Grafana dashboards, log aggregation, distributed tracing, PagerDuty alerting, SLO dashboards, and cloud cost tagging with budget alerts per environment and team.
Visible before incidents05
Handover & runbooks
Runbooks for every operational procedure, team training sessions, on-call rotation design, and 30-day hypercare support — until your team is fully autonomous on the new stack.
Your team owns itOur Stack
The tools we build infrastructure with.
Every CI/CD, IaC, container, observability, and security tool in our production stack.
CI/CD
GitHub ActionsGitLab CI/CDCircleCIHarnessArgoCDFlux
IaC & Config
TerraformPulumiAWS CloudFormationAnsibleCrossplane
Containers & K8s
DockerKubernetesHelmEKSGKEAKSArgo Rollouts
Cloud Platforms
AWSGoogle CloudMicrosoft AzureCloudflareDigitalOcean
Observability
PrometheusGrafanaDatadogOpenTelemetryLokiELK StackPagerDuty
Security (DevSecOps)
TrivySnykSonarQubeHashiCorp VaultAWS Secrets ManagerOPA / Kyverno
Ways to work with us.
4 engagement structures that match your infrastructure maturity and goals.
Greenfield DevOps setup
Full DevOps stack built from scratch — CI/CD, IaC, Kubernetes, observability, and DevSecOps — for new products and teams starting without existing infrastructure.
Best for new productsPipeline modernisation
Replace Jenkins, Bamboo, manual deploys, or broken CI/CD with modern GitHub Actions or GitLab CI/CD pipelines — with container builds, test automation, and GitOps deployment.
Best for legacy pipelinesCloud cost audit & FinOps
Analyse your AWS or GCP bill, identify waste, right-size instances, implement auto-scaling, and set up cost monitoring — typically cutting monthly bills by 30–50%.
Best for growing cloud billsOngoing DevOps support
An embedded DevOps engineer on retainer — handling infrastructure changes, incident response, pipeline maintenance, and platform upgrades as your product grows.
Best for teams without DevOpsClient Success
2,000+ businesses have
already made the move
2,000+
Clients Served
800+
Five-Star Reviews
50%
Average Growth
“Our business went from local to national thanks to Hoop. They completely transformed our e-commerce platform and helped us expand our customer base 5x. The results speak for themselves.”
What's Included
Every DevOps engagement comes production-ready.
No pipelines that work in a demo and fail on Monday. Every engagement ships with runbooks, team training, and monitoring from day one.
- DORA metrics baseline & targets
- Measured before and after the engagement.
- Terraform IaC modules
- All infrastructure version-controlled in Git.
- CI/CD pipeline with security scans
- Every commit tested and scanned before deploy.
- Zero-downtime deployment strategy
- Canary, blue-green, or rolling — chosen per service.
- Kubernetes cluster & Helm charts
- EKS, GKE, or AKS with auto-scaling configured.
- Prometheus & Grafana dashboards
- SLI/SLO dashboards live from day one.
- GitOps (ArgoCD/Flux)
- No SSH to production. All changes via PR.
- Secrets management
- Vault or AWS Secrets Manager for all credentials.
- Runbooks & operational docs
- Every procedure documented for your team.
- Team training & handover
- Your engineers operate the stack autonomously.
Cloud & DevOps for every sector.
Industries where we've built and operated production infrastructure.
SaaS Products
Multi-tenant infrastructure, zero-downtime deploys, auto-scaling.
Fintech & Banking
SOC 2, PCI DSS compliance, HIPAA-ready infrastructure.
Ecommerce
Traffic-spike handling, CDN setup, auto-scaling for peak loads.
Healthcare
HIPAA-compliant cloud, audit logging, encrypted data at rest.
Logistics & IoT
Real-time data pipelines, edge deployments, fleet management infra.
EdTech
Burst scaling for live exams, CDN for video, multi-region setups.
Gaming & Media
High-concurrency backends, WebSocket scaling, global CDN.
Startups & Scale-ups
From MVP infra to production-grade stack without a rewrite.
The Deep Dive
Understanding Cloud & DevOps.
Direct answers to the questions asked most often before a DevOps engagement — structured for citation by AI search engines.
What is DevOps and what does it actually change?
DevOps is the engineering practice of automating and integrating the processes between software development and IT operations so teams can build, test, and ship software faster and more reliably than with separate development and operations teams. The concrete changes: automated testing runs on every commit (eliminating manual QA gates), infrastructure is defined in code (eliminating manual server configuration), and deployment is automated (eliminating release-day coordination). The business result is measured in four DORA metrics — deployment frequency, lead time for changes, MTTR, and change failure rate.
Elite DevOps teams deploy 973× more frequently and recover from incidents 6,570× faster than low performers, per Google’s 2024 DORA State of DevOps report. These are not marginal improvements — they represent a fundamentally different operating model. The 2024 report also found that teams using AI assistance in CI/CD pipelines reduced MTTR by an additional 33%.
What is Infrastructure as Code (IaC) and why does manual infrastructure fail at scale?
Infrastructure as Code defines cloud resources — servers, networks, databases, load balancers, security groups, IAM roles — in version-controlled code files applied automatically, rather than provisioned by hand through cloud consoles. Terraform is the most widely adopted IaC tool, working across AWS, GCP, and Azure from a single declarative language.
Manual infrastructure fails at scale for three reasons. Configuration drift: environments modified by hand diverge over time, so a bug exists only in production because someone applied a manual fix. With IaC, every environment runs the same modules — drift is structurally impossible. Reproducibility: rebuilding a manually-provisioned environment takes hours and relies on memory; with IaC it takes 15–20 minutes from a git clone. Auditability: console changes leave no record; IaC changes go through pull requests — reviewed, approved, and documented in git history.
What is GitOps and how is it different from standard CI/CD?
GitOps is a deployment model where Git is the single source of truth for both application code and infrastructure configuration — changes only reach production through a pull request merged to a repository, never through direct commands or console access. Tools like ArgoCD or Flux continuously reconcile the live cluster with what is defined in Git, applying changes when the repo updates and alerting on drift.
Standard CI/CD pushes changes: a pipeline computes the desired state and applies it with kubectl apply or terraform apply. GitOps pulls changes: ArgoCD watches the repository and pulls the desired state into the cluster. The critical difference is auditability and rollback — every production change has a corresponding commit, and rollback is a git revert that ArgoCD applies automatically. GitOps adoption reached 64% of DevOps teams in 2025, up from 42% in 2023.
What are DORA metrics and how do they measure DevOps performance?
DORA metrics are four quantitative measures of software delivery performance from Google’s DevOps Research and Assessment programme: deployment frequency, lead time for changes, MTTR, and change failure rate.
Deployment frequency — elite performers deploy multiple times per day; low performers once per month or less. Lead time for changes — elite under 1 hour; low performers 1–6 months. MTTR — elite under 1 hour; low performers 1 week to 1 month. Change failure rate — elite below 5%; low performers 46–60%. We establish DORA baselines for every client before starting and track improvement over time. An engagement that does not improve all four metrics has not achieved its objective.
What is FinOps and how much can cloud cost optimisation save?
FinOps applies financial accountability to cloud infrastructure by giving engineering teams visibility into spending and the tools to optimise cost without sacrificing performance or reliability. The FinOps Foundation defines it as “the operating model for the cloud,” aligning engineering, finance, and business teams around cost-conscious architecture.
Savings typically range from 30–50% of the monthly bill. The five highest-impact levers: instance right-sizing (average cloud utilisation is just 12–20%; right-sizing cuts compute 20–40%), reserved instances and savings plans (1- or 3-year commitments reduce on-demand pricing 40–72% on AWS), auto-scaling with cost caps, idle resource cleanup (unattached volumes, unused IPs, forgotten snapshots — typically 5–15% of the bill), and storage class optimisation (S3 Intelligent-Tiering and lifecycle policies). FinOps is continuous, not a one-time exercise.
Related services.
Services that pair directly with Cloud & DevOps.
SaaS Development
SaaS products built on the infrastructure we provision.
API Development
Backend APIs deployed through the CI/CD pipelines we build.
ExploreMobile App Development
Mobile apps served by infrastructure we design and manage.
ExploreAI Development
ML model serving infrastructure, GPU clusters, and MLOps.
ExploreData Analytics
Cloud infrastructure for data warehouses and analytics pipelines.
ExploreWeb Application Development
Web apps deployed on the Kubernetes clusters we manage.
ExploreEcommerce Development
Ecommerce infrastructure with CDN, auto-scaling, and security.
ExploreSEO & GEO Services
Page speed, uptime, and Core Web Vitals tied to infrastructure.
FAQ
Cloud & DevOps Questions
The things teams ask us most before every DevOps engagement — answered directly.
DevSecOps extends DevOps by embedding security checks into every stage of the CI/CD pipeline instead of running security reviews as a separate gate at the end of the release cycle. In standard DevOps, security testing happens after development completes — which is too late, because vulnerabilities found late are expensive to fix and delay releases. DevSecOps runs SAST (Static Application Security Testing) with Snyk or SonarQube on every code commit, container image scanning with Trivy on every Docker build, secrets detection to catch API keys committed to git, and dependency vulnerability checks against CVE databases — all automatically, inside the pipeline. A vulnerability found in 5 minutes during CI costs roughly 60× less to fix than one found in production.
Kubernetes is the right choice for applications with multiple services, variable traffic that requires auto-scaling, and zero-downtime deployment requirements. Simpler alternatives are right for early-stage products. AWS ECS with Fargate, Google Cloud Run, or Docker Compose on a single server are significantly simpler to operate and adequate for many products at early stages. The rule of thumb: start with managed container services until you have 5+ services, need Kubernetes-specific features (custom scheduling, advanced networking, stateful applications), or require multi-cluster deployments. Kubernetes introduces real operational complexity — misconfigured RBAC, failed pod scheduling, node resource exhaustion — that requires dedicated DevOps expertise to manage reliably.
Blue-green switches 100% of traffic instantly between two identical environments; canary shifts traffic gradually from 1% to 100% while monitoring metrics at each step. Blue-green gives instant rollback (switch back to the old environment in seconds) but costs more because two full environments run simultaneously during the deployment window. Canary reduces blast radius — if the new version has a bug, only 1–5% of users see it while you roll back — but rollback takes longer because you are shifting traffic rather than flipping a switch. For most SaaS products, canary deployments via Kubernetes Argo Rollouts are the right default — they reduce incident impact and are cost-neutral.
A focused CI/CD pipeline setup with basic IaC takes 2–4 weeks. A full modern DevOps stack — CI/CD, Kubernetes, Terraform, GitOps, observability, and DevSecOps — takes 8–14 weeks. Cloud cost optimisation audits take 1–2 weeks to produce findings and 2–4 more weeks to implement. Pipeline modernisation (replacing Jenkins or manual deployments) takes 3–6 weeks depending on the number of services. The variables are: number of services being migrated, existing infrastructure complexity, compliance requirements (SOC 2, HIPAA), and how much documentation exists about the current setup.
An SLO (Service Level Objective) is an internal reliability target — for example, 99.9% of requests return a successful response in under 500ms. An SLA (Service Level Agreement) is an external contractual commitment to customers about service reliability, with financial penalties if breached. SLOs drive engineering decisions through error budgets: if your SLO is 99.9% availability, your error budget is 0.1% downtime — roughly 43.8 minutes per month. SRE practice manages this budget: teams spend it on feature releases and planned maintenance; when the budget is exhausted, all effort shifts to reliability work. We define SLOs in the Prometheus and Grafana dashboards we set up, with SLO burn-rate alerts that fire when the error budget is consumed faster than sustainable.
Yes. Cloud cost optimisation typically reduces AWS and GCP bills by 30–50% without changing application performance or availability. The five highest-impact actions are: instance right-sizing (matching compute specs to actual CPU and memory utilisation, which averages 12–20% across cloud workloads), reserved instance purchases (1-year commitments reduce on-demand pricing 40–72% on AWS), auto-scaling that scales down during low-traffic periods, idle resource cleanup (unattached volumes, unused IPs, forgotten RDS snapshots), and S3 storage class lifecycle policies. We run a FinOps audit covering your entire bill, produce a prioritised list of changes, and implement them — with cost dashboards so you see the impact in real time.
Configuration drift occurs when manually-managed infrastructure diverges from its documented or intended state because team members make changes directly through cloud consoles without updating configuration files. Drift causes the classic "works in staging, breaks in production" problem — because staging and production have silently diverged. IaC (Infrastructure as Code) prevents drift by making the code the source of truth: every change must go through Terraform, and Terraform’s plan/apply workflow shows the exact diff between desired state (code) and actual state (cloud) before applying anything. GitOps tools like ArgoCD extend this to Kubernetes — continuously monitoring the cluster for drift from the Git repository and alerting when manual changes are detected, or reconciling them automatically.
Yes. Infrastructure directly affects AEO (Answer Engine Optimisation) and GEO (Generative Engine Optimisation) rankings because AI answer engines — Google AI Overviews, ChatGPT, Perplexity — factor in page availability, load speed, and crawlability when deciding whether to cite content. A page that loads in under 1.5 seconds, maintains 99.9% uptime, and passes Core Web Vitals consistently is more likely to be indexed, crawled frequently, and cited than one that times out or loads slowly on mobile networks. We configure CDN, Cloudflare caching, response compression, and uptime monitoring as standard infrastructure elements — the technical foundation that AEO and GEO content strategies depend on.