Enterprise Ready · Cloud-Native Container Orchestration

Docker and Kubernetes Development Company

Cloud-NativeContainerizedProduction-Grade

Miracuves is a Docker and Kubernetes development company. We containerize applications and run them on production clusters on Amazon EKS, Google GKE and Azure AKS - Dockerfiles, Helm charts, CI/CD, GitOps and autoscaling - as custom work from $3,699, inside cloud accounts that are in your name. You own 100% of the code and configuration we write, with NDA-protected IP safety from day one.

★★★★★ Clutch reviewed 5.0Ready-made platforms from $2,199View live deployments

  • 500+ Clusters Deployed
  • Multi-Zone Clusters by Design
  • 100% Source Ownership
  • NDA Day One
2-4 WksContainer migration, scoped
$3,699Container migration, from
90+Ready-made solutions
100%IP assignment
Cloud-native engineers active right now
DockerKubernetesHelmIngress9,000+ deliveredNDA day one
  • EKS · GKE · AKSMulti-cloud Kubernetes orchestration
  • 500+ Container ClustersDeployed by Miracuves
  • Helm · TerraformOur enforced infrastructure standard
  • 2-4 WeeksBrief to production cluster
  • 100% Source CodeDelivered to you on handoff
  • Multi-Cloud Ready

    EKS, GKE, AKS supported

  • NDA Day One

    IP protected first call

  • Full Infrastructure Code

    Terraform + Helm delivered

  • 60-Day Support

    Post-launch included

  • 100% IP Ownership

    Yours - always

  • Clutch Reviewed 5.0★

    Third-party verified

More than 6,000+ Companies Trust us Worldwide
In short

Miracuves builds Docker and Kubernetes platforms for product teams: applications containerized, clusters on Amazon EKS, Google GKE or Azure AKS, with Helm, GitOps, autoscaling and monitoring. A container migration takes 2-4 weeks from $3,699; custom Kubernetes builds take 2-8 weeks, and a ready-made platform ships in 6 working days. Clusters run in your own cloud accounts, and you own 100% of the code.

Our Docker and Kubernetes Approach

How Miracuves delivers Docker and Kubernetes systems - from 500+ container deployments of real experience

After deploying 500+ production clusters, Miracuves works with Docker and Kubernetes in a fixed order: images first, then the cluster, then the path between them. We start from 500+ production-grade infrastructure modules - Helm charts, Terraform modules, GitOps pipelines and monitoring stacks that have already been wired together - not from a blank manifest, and each is adapted to the cloud account you run.

An image built once runs the same way on a laptop, on EKS, on GKE or on AKS, so one pipeline can build it, scan it and promote the same digest from staging to production. The cluster around the image is not identical everywhere - load balancers, storage classes, networking and identity are specific to each provider - so the Terraform and the Helm values are written for the cloud you run on, and all of it is yours on handoff.

Who this service is built for: CTOs and engineering leads moving an application from hand-managed servers into containers, teams whose services already run in Docker but have no dependable way to deploy and scale them, and companies that need Kubernetes on EKS, GKE or AKS with GitOps, autoscaling and security controls set up correctly the first time. Miracuves Docker and Kubernetes development fits when you want one company accountable for images, cluster and pipeline, with published pricing and full ownership of the infrastructure code. If you run one or two small services, a platform such as Cloud Run, Azure Container Apps, ECS on Fargate or a PaaS will cost less to run than a cluster, and we will say so upfront. If the gap is release automation rather than containers, see DevOps engineering; if the whole cloud foundation is missing, see cloud engineering.

  • Multi-arch Docker images (amd64 and arm64) with ordered layers: a code change rebuilds one layer, not the whole image
  • Helm-based GitOps with ArgoCD enforced: predictable deployments, rollback-safe releases from day one
  • Terraform for the cluster and everything around it on EKS, GKE or AKS: node pools, GPU and spot capacity, networking and IAM
  • CI/CD pipeline via Tekton or GitHub Actions configured on every project: automated builds from first commit
  • Prometheus + Grafana monitoring stack fully configured: alerts, dashboards, SLO tracking pre-deployed
9,000+Projects delivered since 2010
3,900+Apps published by Miracuves
90+Ready-made solutions to start from
6 daysReady-made clone delivery
2-8wMiracuves custom container build timelines
100%Source code ownership
Amazon EKSManaged Kubernetes on AWS
Google GKEStandard or Autopilot
Azure AKSManaged Kubernetes on Azure

Why Docker and Kubernetes at Miracuves

  • Time to first cluster2-4 weeks
  • Managed clusters we build onEKS · GKE · AKS
  • Custom container work2-8 weeks
  • Infrastructure modules to start from500+ modules
  • AutoscalingPods, queues and nodes
  • Source code ownership100% yours
Example engagement: German logistics migration, 6 weeks
"47 legacy VMs migrated to Kubernetes on GKE, full Terraform IaC, Helm charts for every service, Istio service mesh for inter-service communication, and Prometheus/Grafana monitoring stack - in 6 weeks. We used our pre-built migration modules, rebuilt the networking layer for cloud-native routing, and deployed ArgoCD for GitOps. The target was a 64% lower infrastructure bill than the VMs."

Ready-made platforms · 6 days

What Miracuves has deployed - what you can launch today

Six of our 90+ ready-made platforms, each shipping with its apps and admin panel in 6 days. They run on their own stacks; containerizing one and running it on Kubernetes is custom work, quoted separately.

View All Ready-Made Solutions

Honest noteDocker and Kubernetes are right for platforms with several services, uneven traffic or more than one environment to keep in step. For one or two small services, Cloud Run, Azure Container Apps, ECS on Fargate or a PaaS runs the same container for less effort, and a single server with Docker Compose is enough for many internal tools. We tell you which fits before any commitment.

Technology Comparison

Kubernetes vs Docker Swarm vs AWS ECS - which is right for your project?

Kubernetes is our default, not our only answer. The orchestrator you pick sets what you pay each month, how far the platform scales and how much your team has to operate, so this table also shows where Swarm or ECS is the better call.

MetricFive things that decide cost, speed and reach
Miracuves default

Docker + Kubernetes

Container orchestration · any cloud

Docker Swarm

Docker's built-in orchestrator

AWS ECS / Fargate

AWS-managed orchestration

01Auto-Scaling
HPA + VPA + KEDA - metric-drivenPods by CPU, memory, queue depth or custom metrics; cluster autoscaling adds nodes
No built-in autoscalingReplica counts set by hand or by an external script
Service Auto ScalingTarget tracking on CPU, memory or custom metrics; Fargate removes node management
02Service Discovery
CoreDNS built inIstio or Linkerd added when mTLS or traffic splitting is needed
Built-in DNS + routing meshVirtual-IP load balancing; no mesh features
Service Connect / Cloud MapManaged by AWS inside your VPC
03Multi-Cloud
Any cloud / on-prem / edgeEKS, GKE, AKS or self-managed; the same manifests with provider-specific values
Runs wherever Docker runsFew managed offerings; you operate the managers yourself
AWS onlyECS Anywhere reaches your own servers, still run from AWS
04Secrets Management
Kubernetes Secrets + Vault or External SecretsEncryption at rest enabled on the control plane (KMS on managed clusters)
Docker secrets built inEncrypted in the Swarm Raft store, mounted in memory
Secrets Manager or SSM Parameter StoreInjected into task definitions through IAM roles
05Best For
Microservices · multi-cloud · GitOpsTeams that will run several services for years
Small clusters · simple stacksTeams already fluent in Docker Compose
AWS-native · Fargate serverlessAWS-only products that want less to operate
Choose Kubernetes if…

You need multi-cloud portability · auto-scaling microservices · zero-downtime deployments · Istio service mesh with mTLS · one team managing the full container lifecycle.

Consider an alternative if…

You run fewer than 10 containers · a single server with Docker Compose is sufficient · one small web service that Cloud Run, Azure Container Apps or a PaaS can host · an AWS-only shop that prefers ECS on Fargate (see AWS development) · the gap is CI/CD rather than containers. See when NOT to use Kubernetes →

Docker and Kubernetes guide

What to know before you hire a Docker and Kubernetes company

The decisions a team faces before it pays for containers and a cluster: whether Kubernetes is needed at all, which managed service, how a monolith moves, what the cluster costs to run, how it is secured and who runs it afterwards.

Do we actually need Kubernetes?

Often not at first. Docker and Kubernetes solve different problems: Docker packages an application and its dependencies into an image, and Kubernetes schedules many of those images across a fleet of machines, restarts them when they fail and scales them with load. Almost every team gains from the first. The second earns its running cost when you have several services, traffic that swings through the day, more than one environment to keep identical, or a need to run the same stack on more than one cloud.

For one or two stateless services, Google Cloud Run, Azure Container Apps or ECS on Fargate run the same Docker image with no cluster to upgrade, and a single server with Docker Compose is enough for many internal tools. We recommend those when they fit; the images carry over unchanged if you move to Kubernetes later.

EKS, GKE or AKS - and managed or self-managed?

Managed, in nearly every case. On Amazon EKS, Google GKE and Azure AKS the provider runs and patches the control plane; you run the worker nodes and what is deployed on them. Self-managed Kubernetes fits on-premises or edge requirements, and then your team owns etcd backups and every upgrade.

Pick the service in the cloud you already use, because your identity, network and data live there. GKE Autopilot goes furthest: Google manages the nodes as well and bills by pod request, which suits teams without a platform engineer. EKS fits products built on AWS services, AKS fits companies on Microsoft Entra ID and .NET. The AWS, Azure and Google Cloud pages go deeper on each provider.

How do you move a monolith into containers?

Containerize it as it is before splitting anything. One well-built image running as several replicas behind a load balancer already gives repeatable releases and fast rollbacks. What must change first is state: anything the application keeps on its own disk or in memory has to move out, or the replicas disagree with each other.

  • Uploaded files to object storage - S3, Azure Blob Storage or Cloud Storage
  • Sessions and caches to Redis or a managed equivalent
  • The database to a managed service, outside the cluster
  • Configuration and secrets to environment variables injected at deploy time
  • Logs written to standard output, where the cluster collects them

What does a cluster cost to run, and who pays for it?

The cloud bill is yours, paid directly to AWS, Google or Microsoft and separate from the Miracuves fee. It has more lines than a server bill: a per-cluster management fee on EKS and GKE (AKS offers a free control-plane tier and a paid tier with an SLA), worker nodes, load balancers, NAT gateways, persistent disks, log ingestion and traffic between zones. We keep it down with:

  • CPU and memory requests set from measurements - nodes are sized to requests, not to real use
  • Cluster autoscaling that removes idle nodes at night as well as adding them at peak
  • Spot or preemptible nodes for stateless workloads that tolerate interruption
  • Shared non-production clusters split by namespace, not a cluster per developer
  • Log retention reviewed early, because log ingestion is a common surprise line

What does a secure cluster need from day one?

Most Kubernetes incidents come from configuration, not exotic attacks. The baseline we apply to every cluster:

We build to SOC 2, PCI DSS, HIPAA or GDPR requirements; audits and attestations belong to your organization.

  • Images from minimal bases, scanned in the pipeline, deployed by digest and run as non-root
  • Secrets kept out of Git and ConfigMaps - pulled from AWS Secrets Manager, Azure Key Vault or Google Secret Manager by the External Secrets Operator, with encryption at rest switched on
  • Least-privilege RBAC tied to your cloud identity, so removing a person from IAM or Microsoft Entra ID removes their cluster access
  • Network policies that deny traffic between namespaces unless it is allowed
  • Pod Security Standards enforced, plus admission rules in Kyverno or OPA Gatekeeper

Is Docker still relevant now that Kubernetes dropped dockershim?

Yes. Kubernetes 1.24 removed dockershim, the adapter that let the Docker Engine act as the node runtime. Clusters now run containerd or CRI-O, and both run images built with Docker unchanged, because those images follow the OCI standard. Docker is still the usual tool for building images and for local development with Docker Compose.

One licensing point: Docker Desktop needs a paid subscription for commercial use at larger companies, with the threshold set by Docker on headcount and revenue. Docker Engine on Linux, and alternatives such as Podman or Rancher Desktop, carry no such fee.

Can our own team run the cluster after handover?

That is what the handover is for. Everything lives in your Git repositories: Dockerfiles, one Helm chart per service, Terraform for the cluster and its network, and the Argo CD or Flux configuration that syncs the repository to the cluster, so a change is a pull request rather than a kubectl command. You also receive runbooks for deploys, rollbacks and restores, dashboards and alerts routed to your on-call channel, and working sessions with your engineers on the real cluster.

Kubernetes ships about three minor releases a year, so plan an upgrade at least yearly; the retainer from $2,299/month covers it if you would rather not staff it. If the gap is the release pipeline, see DevOps engineering; if you are splitting the application into services, see microservices development.

Technical IaC

How Miracuves engineers structure Docker and Kubernetes projects for production

These are the decisions our engineers make on every containerized project before the first manifest is written - they decide whether a cluster stays easy to change or turns into something nobody on the team dares to upgrade.

  • 01

    IaC - Microservices with Namespace Isolation

    Strict namespace separation: frontend → backend → data → monitoring. Every microservice owns its Deployment, Service, ConfigMap, and Secret independently. This is how Miracuves adds a new service module in 2 days without disrupting existing workloads.

  • 02

    Deployment - Helm Charts with GitOps (ArgoCD)

    Argo CD watches your Git repository and reconciles the cluster to match it, so every change is a reviewed commit and a rollback is a revert. The problem we inherit most often from other agencies is manual kubectl apply with no versioning and no record of what runs; we replace it on day one, and it stays replaced.

  • 03

    Images - Multi-Stage Dockerfiles with Distroless Images

    Every Dockerfile uses multi-stage builds, so compilers and build tools never reach the final image and it stays as small as the runtime allows. Production images use distroless or slim bases and run as a non-root user. Every image is scanned with Trivy before it is pushed to the registry - Harbor, Amazon ECR, Google Artifact Registry or Azure Container Registry - and development images are never deployed to production.

What most Docker/Kubernetes agencies get wrong

Running containers as root. No resource limits on pods. Monolithic Docker Compose exported to K8s unchanged. Secrets in plain ConfigMaps. No Horizontal Pod Autoscaler. We have taken over clusters with every one of these faults, and fixing them on a live platform always costs more than setting them up correctly the first time.

orders-api.yaml - Deployment, Service, autoscaler
# orders-api.yaml - Deployment, Service and autoscaler for one serviceapiVersion: apps/v1kind: Deploymentmetadata:  name: orders-api  namespace: backendspec:  # no replicas field: the autoscaler below owns the pod count  selector:    matchLabels:      app: orders-api  strategy:    rollingUpdate:      maxUnavailable: 0      maxSurge: 1  template:    metadata:      labels:        app: orders-api    spec:      securityContext:        runAsNonRoot: true      containers:        - name: api          # immutable version tag set by CI, never :latest          image: registry.example.com/orders-api:1.8.2          ports:            - containerPort: 8080          resources:            requests:              cpu: 250m              memory: 256Mi            limits:              memory: 512Mi          readinessProbe:            httpGet:              path: /healthz/ready              port: 8080            periodSeconds: 5          livenessProbe:            httpGet:              path: /healthz/live              port: 8080            initialDelaySeconds: 10          securityContext:            allowPrivilegeEscalation: false            readOnlyRootFilesystem: true          envFrom:            - secretRef:                name: orders-api-secrets # synced from the cloud secret store---apiVersion: v1kind: Servicemetadata:  name: orders-api  namespace: backendspec:  selector:    app: orders-api  ports:    - port: 80      targetPort: 8080---apiVersion: autoscaling/v2kind: HorizontalPodAutoscalermetadata:  name: orders-api  namespace: backendspec:  scaleTargetRef:    apiVersion: apps/v1    kind: Deployment    name: orders-api  minReplicas: 3  maxReplicas: 12  metrics:    - type: Resource      resource:        name: cpu        target:          type: Utilization          averageUtilization: 70
One service as it reaches the cluster: rolling updates that never drop below the current capacity, readiness and liveness probes, CPU and memory requests the scheduler can plan with, a non-root read-only container, secrets injected from the cloud secret store, and an autoscaler that owns the pod count. In a real repository these values come from the service's Helm chart.

Our Service Models

Three ways Miracuves delivers your Kubernetes project

Every engagement is with Miracuves as a company - platform engineers, an SRE and a project lead, with one team accountable for the images, the cluster and the pipeline. Pick the model that matches where your containers are today.

Most Popular
Customer app
Partner app
Admin
Container Migration · Fixed Price

Container Migration Release

Miracuves containerizes the application you already run and moves it onto a managed Kubernetes cluster in your own cloud account - Dockerfiles, Helm charts, CI/CD and monitoring - in 2-4 weeks at a fixed price once scoped. Code and configuration fully yours.

  • From $3,699 - fixed price once scoped, no surprises
  • Existing services containerized as they are - no rewrite needed to start
  • EKS, GKE or AKS - GitOps pipeline configured
  • Monitoring stack included in every delivery
  • Full source code · NDA · 60-day support
K8s ClusterHelm ChartTerraformK8s ManifestPipelineRegistry / CachePods / SVC
Custom K8s Build · Scoped

Custom Kubernetes Build

Miracuves designs from your specification - custom cluster architecture, custom operators, unique orchestration. Full team: architect, platform engineer, SRE, PM.

  • Scoped and priced before development begins
  • Cloud-native architecture designed specifically for your workload
  • Weekly sprint demos - working infrastructure every sprint
  • Cloud provider deployment and handoff managed
  • Full source code · IP 100% yours
Wk 1
Wk 2
Wk 3
Wk 4
Ongoing Retainer · Monthly

Ongoing Kubernetes Support

Miracuves works as your ongoing platform partner - new services, cluster upgrades, security patches on a monthly retainer with weekly reviews.

  • From $2,299/month - cancel with 2 weeks notice
  • Dedicated Miracuves SRE team assigned to your clusters
  • Direct communication - no account manager relay
  • Weekly sprint demos - deliverables every cycle
  • Scales up or down as your product evolves

Quality Standards

How Miracuves ensures every Kubernetes deployment meets production standard

Every cluster passes Miracuves' quality gates before handoff - the same gates on every engagement, applied to every Dockerfile, Helm chart and Terraform module we ship, not a checklist ticked at the end.

  • Infrastructure as Code - Terraform modules / Helm charts separatedIaC
  • Helm values per environment - one chart per service, no copy-pasted manifestsConfig
  • Multi-arch images built once, scanned, and promoted by digestImages
  • Multi-environment Validation - staging, canary, production validationValidation
  • GitOps pipeline - automated deployments and drift detection from day oneGitOps
  • No secrets in manifests - Vault or Sealed Secrets for all credentialsSecrets
  • Production-ready - RBAC, network policies, pod security appliedRelease

Enforced Validation Gates

Our 6 Continuous Release Gateways

Every line of code, asset, and build profile must successfully clear all six quality control gates before repository handoff.

01

Code Review on Every Pull Request

Every change to a Dockerfile, Helm chart, Terraform module or pipeline is reviewed by a senior Miracuves engineer before it merges, with the Terraform plan and the rendered manifests attached to the pull request. Nothing reaches your production cluster without that review.

02

Automated Test Coverage Required

Application tests run in the pipeline before an image is built. Then every Helm chart is rendered and linted for each environment, and the output is checked against the Kubernetes API schema and policy rules with tools such as kubeconform, Conftest or Kyverno. A chart that fails to render or breaks a policy never reaches the cluster.

03

Container Images Scanned - Not Latest Tags

Every image is scanned for known vulnerabilities before it is pushed, and deployed by an immutable tag or digest - never :latest - so what was tested is exactly what runs. CPU and memory requests are then set from Prometheus measurements under load, not guessed, so the scheduler places pods on real numbers.

04

Handoff Package - Not Just Terraform

Terraform state, Helm charts, ArgoCD application manifests, monitoring dashboards, runbooks, alerting rules, and post-deployment support plan - all included in every project handoff.

05

Production Cluster Validation - Full Compliance

Before any cluster is called production-ready, Miracuves applies RBAC roles, network policies, Pod Security Standards, resource quotas and namespace isolation, checks the cluster against the CIS Kubernetes Benchmark with kube-bench or the provider's own scanner, and restores a backup of cluster state and persistent volumes to prove it works.

06

Post-Deploy Monitoring - 60-Day Active Support

Prometheus and Grafana configured pre-deployment. Miracuves monitors error rates, latency percentiles, and resource utilization during the 60-day post-deploy support window - proactive, not reactive.

Technology Stack

The Docker and Kubernetes stack Miracuves ships with

Matched to your architecture and delivery requirements - not a one-size-fits-all default.

Do
DockerImage builds with BuildKit · local development
He
HelmKubernetes package manager · one chart per service
Tf
TerraformInfrastructure as Code · clusters, networks, IAM
Ar
Argo CDGitOps delivery · Flux where preferred
Pr
PrometheusMetrics · alerting · SLO tracking
Is
IstioService mesh · mTLS · traffic mgmt
Va
VaultSecrets management · dynamic credentials
Ke
KEDAEvent-driven scaling · queue-based autoscaling
En
EnvoyAPI gateway · load balancing · rate limiting
Lh
LonghornPersistent storage · CSI volumes
Tk
TektonCloud-native CI/CD pipelines
Go
Go / PythonMicroservices language layer
An
AnsibleConfiguration management layer
Ja
JaegerDistributed tracing · latency analysis
K8
KubernetesEKS · GKE · AKS · self-managed
Hb
HarborPrivate registry · image signing

Our Process

From brief to production Kubernetes cluster - what happens and when

Every container engagement follows the same five steps, whether it is a scoped migration of an application you already run or a custom cluster built from a specification. At each step you know what Miracuves is doing, which cloud access and credentials we need from you, and what lands in your repository. Timelines below reflect the 2-4 week container migration; custom Kubernetes builds run milestone-based with the same checkpoints.

  1. Step 01

    Brief & NDA

    Share your infrastructure challenge via WhatsApp. NDA signed same day. We audit your current setup.

  2. Step 02

    Scope & Plan

    Cloud provider, cluster size, and service model confirmed. No payment before scope is agreed.

  3. Step 03

    Build & Demo

    Terraform repo created, Helm charts initialized. First deploy in 24h. Weekly working review.

  4. Step 04

    Validation & Polish

    Kubernetes manifests validated, Istio mesh configured, Prometheus monitoring active. Load tested.

  5. Step 05

    Launch & Handoff

    Full IaC and monitoring delivered. Cloud handoff completed. 60 days active support.

Same DayNDA turnaround
2-4 WeeksCluster migration delivery
24 HoursFirst deploy after scope
60 DaysPost-deploy support

Six days is Miracuves build time, not calendar time

The six days are ours, and they do not run past six. What can add time sits on your side: developer account verification, merchant onboarding and compliance approvals are controlled by the app stores and your payment provider, not by us. We list exactly what you need ready on the first call so you can start those in parallel.

See what you provideFACT-005, audited quarterly

Transparent Pricing

What Docker and Kubernetes infrastructure costs at Miracuves

We publish prices for container work because its scope can be fixed in advance: services, clusters and environments are counted before we quote. No "contact us for pricing" pages. No hidden fees after scope is agreed.

Container Migration

$3,699 from

Fixed price · 2-4 week migration · scoped

  • Containerized microservices on K8s
  • Prometheus + Grafana monitoring included
  • GitOps pipeline and ArgoCD configured
  • Full source code on handoff
  • 60-day post-launch support
  • NDA protected from day one
Start a Migration Project
Most Requested

Custom Kubernetes Build

Custom Quote

Scoped before build · milestone billing

  • Full GitOps team - architect + SRE + Validation
  • Custom cluster architecture for your workload
  • Weekly sprint demos - working infrastructure
  • Cloud provider deployment and handoff
  • Full IaC · complete infrastructure transfer
  • Milestone billing - no pay before delivery
Get a Scope & Quote

Ongoing Development

$2,299 /mo

Monthly retainer · cancel with 2 weeks notice

  • Miracuves team assigned to your product
  • New features, releases, and maintenance
  • Weekly demos and sprint planning
  • Direct communication - no relay
  • Scales up or down as needed
  • All code remains 100% yours
Discuss Ongoing Work

Why Miracuves publishes pricesTeams that know the cost of a migration upfront plan the cutover better. If your cluster needs a larger budget - more services, more regions, stricter compliance - Miracuves shows exactly which part drives it, not simply a higher number.

What affects Kubernetes project cost at Miracuves

Container migration pricing stays fixed when the scope matches the migration package: one application, one cloud and one production cluster. Custom Kubernetes builds scale with: the number of services to containerize, how much state has to move out of the servers (databases, file uploads, sessions), how many clusters, environments and regions are in scope, multi-cloud or on-premises requirements, compliance requirements (SOC 2, PCI DSS, HIPAA, GDPR), and whether a service mesh, custom operators or GPU node pools are needed.

Typical Docker and Kubernetes budget ranges

  • Ready-made platformfrom $2,1996 days (a catalogue product on its own stack, not container work)
  • Container migrationfrom $3,6992-4 weeks, fixed once scoped
  • Custom Kubernetes build$8,000-$25,0002-8 weeks depending on scope; larger scopes are quoted in writing before work starts
  • Ongoing retainerfrom $2,299/month for cluster upgrades, new services and maintenance

Your cloud bill - cluster fees, nodes, load balancers, storage and data transfer - is paid by you to the provider and is separate from our fee.

Every quote is written before payment - no surprise invoices after kickoff.

Example engagement

What a typical Kubernetes migration looks like at Miracuves

An illustrative example of a typical project of this kind, with client details anonymized. Figures show what this kind of build targets, not a named client's results.

A French SaaS company serving 200+ European retail chains needed to containerize their microservices architecture to reduce deployment downtime from 4 hours to under 10 minutes across staging, pre-prod, and production.

  1. 01

    The Challenge

    Their 23 Java/Node.js microservices were deployed via manual SSH + Ansible playbooks. Deployments required 4-hour Saturday night maintenance windows. Rollbacks took 2+ hours. No canary deployments or health check automation existed.

  2. 02

    What Miracuves Delivered

    Designed a GitOps CI/CD pipeline on GKE with ArgoCD. Containerized all 23 services using Docker multi-stage builds (Java 17 on distroless, Node.js 20 on Alpine). Created Helm charts per service with environment overrides. Implemented canary deployments with Flagger and Prometheus metrics-based auto-promotion.

  3. 03

    Outcome

    Deployment time went from 4 hours to 4 minutes. Rollbacks became instant (~30s). Zero-downtime deploys became the norm. Pipeline handles 40+ deploys per week with auto-rollback on failure - saving the team 30+ engineer-hours weekly.

4 WeeksFull delivery
23 ServicesContainerized
100%Source owned
View All Case Studies
Project Brief
  • Solution usedGKE + ArgoCD + Helm
  • Migration timeline4 weeks
  • Services containerized23 Java and Node.js services
  • Key integrationsIstio · Docker · Flagger · mTLS
  • Requirements in scopeSOC 2 and GDPR controls
  • Source code100% client-owned
4 minDeploy time, from 4 hours
~30sRollback time
60dSupport included

Client Reviews

What clients say about building with Miracuves

Named clients, in their own words, on products whose infrastructure had to hold up - a VPN with server orchestration, a multi-tenant alerting platform, and a live-video service on launch nights. Each card names what it was built on; read every testimonial on our client testimonials page.

Client testimonial
"Building a consumer VPN is less about the tunnel and more about the app store, the subscriptions and the server management. Miracuves handled the client apps, the server orchestration and the billing layer, and we brought the network. Delivered inside a month and approved on both stores without a rejection cycle."
DP
Dhiru PriyadarshiFounder, Maxx
Consumer VPN with server orchestration and subscription billing
Client testimonial
"Multi-tenant structure, alert pipelines and agent collectors were the slow part and they already existed. We added our scoring engine, the playbook library and billing. First customers were onboarded within weeks and the dashboard is now a sales tool rather than an internal screen."
RK
Rohit KhannaFounder & CEO, Server ProGuard Inc
Multi-tenant security dashboard with alert pipelines and agent collectors, built on MXSecurity Dashboard
Client testimonial
"Live video, creator onboarding and tipping came ready. We added the drop calendar, artist royalty logic and our moderation layer. It has held up on launch nights without a stumble, and a from-scratch build would have been six months longer at twice the cost."
TS
Todd ScharamVP Digital, PAS Systems Corp
Live-video platform for independent artists that holds up on launch nights
5.0 / 5.0Clutch average · 14 reviews
4.8 / 5.0Google average rating
Top DeveloperClutch recognition · 2024-2025
Read All Reviews

Why Miracuves

Six places to check us before you ever call us

Each one is either run by someone else or open to anyone. Check them in any order; the whole list takes about a minute.

Why clients choose Miracuves

Three promises we would stake the company on

Every promise on this site rests on these three. Each one is something you can check, not something you have to take on trust.

  • 01People you can name

    Our leadership is public, with real LinkedIn profiles, not a stock-photo team page. A named team works your build and sends you progress on WhatsApp every working day.

    Meet the leadership
  • 02Proof over promises

    Every number we publish, pricing, timelines, project counts, is defined and sourced on a public facts ledger. If we can't back a claim, we don't make it.

    Read the facts ledger
  • 03A process with a deadline

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Frequently Asked

Questions about Docker & Kubernetes development at Miracuves

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Is Kubernetes worth the complexity for our project?

For platforms with several services, uneven traffic or more than one environment - usually yes: Kubernetes restarts failed containers, rolls out releases without downtime, and scales pods and nodes with load. It is not free to run: a cluster needs upgrades several times a year, monitoring and someone who understands it. For one or two small services, Cloud Run, Azure Container Apps, ECS on Fargate or a PaaS runs the same Docker image with far less to operate, and Docker Compose on one server is enough for many internal tools. Kubernetes itself carries no uptime SLA - the managed control plane's SLA is the provider's contract, and availability comes from how the workload is spread across zones. Miracuves assesses honestly and recommends the right level.

How much does Docker and Kubernetes development cost at Miracuves?

A container migration - your existing application containerized and running on a managed Kubernetes cluster with CI/CD and monitoring - starts from $3,699 and takes 2-4 weeks, at a fixed price once scoped. A custom Kubernetes build typically costs $8,000-$25,000 over 2-8 weeks; where it lands depends on the number of services, how much state has to move, how many clusters, environments and regions are in scope, compliance requirements and whether a service mesh or custom operators are needed, and larger scopes are quoted in writing before work starts. Ongoing cluster work on a retainer starts from $2,299/month. If a catalogue product fits, the ready-made platform starts from $2,199 and ships in 6 days. Your cloud bill for cluster fees, nodes, load balancers and storage is paid to the provider and is separate from our fee. Every quote is written before payment, with no surprise invoices after kickoff.

Does Miracuves deliver the full source code and IaC?

Yes - completely. Miracuves delivers all Dockerfiles, Kubernetes manifests, Helm charts, Terraform modules, Argo CD pipeline configs, monitoring dashboards and environment setup guides. The cloud accounts, clusters and billing are in your name from day one; managed services such as EKS, GKE or AKS remain the provider's services under its terms. Zero lock-in: your team can deploy, extend and maintain everything independently after handoff.

How fast can a Kubernetes platform be production-ready?

A scoped container migration of an application you already run takes 2-4 weeks from $3,699. A greenfield Kubernetes platform built from a specification takes 2-8 weeks depending on service count and compliance requirements; larger scopes are quoted in writing before work starts. Both timelines are written into the proposal, and no payment is asked for until you have them.

Docker vs Kubernetes vs Docker Swarm - what does Miracuves recommend?

Docker packages your app. Docker Swarm orchestrates simple clusters. Kubernetes orchestrates at enterprise scale with auto-scaling, service mesh, and multi-cloud portability. Miracuves recommends Kubernetes for microservices and multi-cloud platforms. Docker Compose or Swarm is sufficient for simple, single-host deployments.

What is included in the monitoring stack with every delivery?

Prometheus for metrics collection, Grafana dashboards for visualization, alerting rules for pod health and resource usage, Jaeger for distributed tracing, and Fluentd for log aggregation - all configured before the first production deployment goes live.

Does Miracuves handle production cluster setup and cloud provisioning?

Yes, as part of every engagement. Miracuves provisions managed Kubernetes clusters on EKS, GKE or AKS via Terraform in your own cloud account, configures VPC networking, sets up RBAC and network policies, and validates production readiness before handoff. Multi-cloud configurations are available for disaster recovery when a requirement calls for them.

What happens after the cluster is delivered if issues arise?

Every cluster Miracuves delivers comes with 60 days of post-launch support: a failing pod, a broken pipeline or an alert that fires within the delivered scope is fixed at no extra cost. New services or features beyond the scope are quoted separately, and cluster upgrades and ongoing work can continue on the monthly retainer from $2,299.

How does Miracuves handle NDA and confidentiality?

A bilateral NDA is signed before you share anything about your infrastructure, and it covers architecture diagrams, credentials handling, business logic and IP. The IP assignment that makes every Dockerfile, chart and Terraform module 100% yours is signed at project start - not at the end - and cloud access is granted through roles you control and can revoke.

Can Miracuves take over a Kubernetes cluster another team built?

Yes, and it is a common starting point. We begin with a written audit: the Kubernetes version and how long it stays supported, who holds cluster-admin, which services are exposed publicly, where secrets live, which pods have no resource limits, whether backups restore, and what the cluster costs each month. The fixes are then prioritized, and hand-applied resources are brought into Helm, Terraform and GitOps so the repository becomes the record of what runs. Nothing in production is changed before you approve the plan.

Can you work on just one part of our container setup?

Yes. Many engagements are narrow: hardening the Dockerfiles, writing Helm charts for services that already run, moving deploys from kubectl scripts to Argo CD or Flux, adding autoscaling and monitoring, or a cost review of an existing cluster. Custom work of this kind starts from $3,699, depending on the work, and is quoted in writing after a short review of your repositories and cluster access.

Can Kubernetes run on our own servers or in a hybrid setup?

Yes. Kubernetes runs on your own hardware through self-managed distributions, and the major clouds offer options to run or manage clusters outside their regions. It fits when data must stay on premises or near factory and edge sites. The trade-off is that your team, or a retainer, owns the control plane, etcd backups and upgrades that a managed service would otherwise handle, so we cost that in before recommending it.

Get Started

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Tell Miracuves what you run today and where it needs to go. We will confirm the right orchestration, cloud, service model and delivery timeline - in writing, before any commitment is required from you.

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Page reviewed by the Miracuves Cloud-Native Team · Last updated June 2026 · Clutch & Google Reviews

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