Skip to main content

Build Kubernetes Platforms for Production Cloud-Native Workloads

Hero Logo

Design, migrate and operate containerized applications on Kubernetes with repeatable deployment, observability, security and platform patterns across public cloud or hybrid environments.

Kubernetes engineering team planning a production cloud-native platform

Move From Running Containers to Operating a Cloud-Native Platform

Kubernetes solves orchestration; production engineering solves everything around it.

We design Kubernetes together with application delivery, networking, configuration, secrets, observability, security and developer workflows. The goal is a platform that makes workloads easier to operate rather than a cluster that transfers infrastructure complexity to application teams.

Three benefits.

Production Architecture

Design clusters and workload patterns around availability, scale, isolation and operational needs.

Repeatable Delivery

Use IaC, Helm and GitOps/CI/CD patterns to reduce manual environment drift.

Operational Visibility

Make logs, metrics, traces, health and deployment behavior visible to engineering teams.
What We Build

What We Build

Kubernetes Application Platforms

Reusable environments for containerized services and applications.

Managed Kubernetes

EKS, AKS and GKE implementations aligned to cloud architecture.

Cloud-Native Applications

Microservices, APIs and event-driven workloads designed for container platforms.

GitOps Delivery

Git-driven application and configuration deployment patterns.

Observability Foundations

Logs, metrics, traces and operational dashboards.

AI Workload Foundations

Kubernetes infrastructure patterns for AI services and inference workloads where appropriate.

01

Kubernetes Architecture & Assessment

Kubernetes ArchitectureAssessmentRoadmapPlatform Design

Assess workloads, clusters, cloud environment and operational maturity before defining the target platform.

Kubernetes Architecture & Assessment
02

Kubernetes Platform Implementation

EKSAKSGKECluster Platform

Build managed or self-managed Kubernetes foundations with networking, ingress, storage and workload standards.

Kubernetes Platform Implementation
03

Kubernetes Migration & Containerization

MigrationDockerContainersModernization

Containerize and migrate suitable applications from VMs or legacy hosting into Kubernetes environments.

Kubernetes Migration & Containerization
04

GitOps & Kubernetes Delivery

HelmArgo CDGitOpsCI/CD

Standardize application configuration and deployment through Helm, Git and GitOps workflows.

GitOps & Kubernetes Delivery
05

Kubernetes Observability & Reliability

OpenTelemetryMetricsLogsReliability

Implement workload health, telemetry, scaling and operational patterns for production clusters.

Kubernetes Observability & Reliability
06

Kubernetes Security & Governance

RBACSecretsPolicySupply Chain

Apply identity, secrets, workload policy and supply-chain controls according to platform requirements.

Kubernetes Security & Governance
Core Capabilities

Core Kubernetes & Cloud-Native Capabilities

Capability

Kubernetes Architecture

Supporting copy

Design cluster, workload and operational patterns around application requirements.

Capability

EKS

Supporting copy

Deploy and operate Kubernetes workloads using Amazon Elastic Kubernetes Service.

Capability

AKS

Supporting copy

Build managed Kubernetes environments on Microsoft Azure using AKS.

Capability

GKE

Supporting copy

Run scalable containerized applications through Google Kubernetes Engine.

Capability

Docker

Supporting copy

Containerize applications with repeatable runtime configurations and dependency boundaries.

Capability

Helm

Supporting copy

Package and manage Kubernetes application configurations across multiple environments.

Capability

GitOps

Supporting copy

Manage cluster and application configuration through declarative, version-controlled workflows.

Capability

Argo CD

Supporting copy

Automate and continuously reconcile Kubernetes deployments from approved Git repositories.

Capability

Autoscaling

Supporting copy

Scale workloads and cluster capacity according to demand and resource usage.

Capability

Ingress & Networking

Supporting copy

Configure secure application routing, service communication and external access.

Capability

Observability

Supporting copy

Capture workload metrics, logs and traces for monitoring and troubleshooting.

Capability

Policy & Security

Supporting copy

Apply identity, secrets, image and deployment controls across Kubernetes environments.

Development Process

How We Deliver

01

Assess

Identify which workloads actually benefit from Kubernetes and map existing operational practices.

02

Design

Define cluster, tenancy, networking, storage, identity and delivery patterns.

03

Build

Implement Kubernetes foundation and reusable workload templates.

04

Migrate

Containerize and move applications in controlled stages.

05

Operationalize

Add observability, scaling, security, backup and incident procedures.

06

Enable Teams

Document golden paths and reduce day-to-day cluster complexity for developers.

Ready to Plan the Next Step?

Kubernetes & Cloud-Native Engineering Technology Stack

ReviewedClutch

5.0 REVIEWS

Kubernetes

KuKubernetes
EKEKS
AKAKS
GKGKE

Containers

DoDocker
OCOCI container images

Packaging

HeHelm
KuKustomize where appropriate

GitOps

ArArgo CD
GiGit-based delivery patterns

Infrastructure

TeTerraform
clcloud IaC

Observability

OpOpenTelemetry
PrPrometheus/Grafana patterns
clcloud-native monitoring

Networking

InIngress
seservice networking
loload balancing

Security

RBRBAC
sesecrets
popolicy as code
imimage/supply-chain controls
Specialized Capability

Cloud-Native Delivery With GitOps

Declarative Config

Keep desired application/platform state versioned.

Pull-Based Delivery

Use GitOps controllers where the operating model fits.

Environment Promotion

Promote reviewed configuration between environments.

Helm Packaging

Create reusable application deployment packages.

Drift Visibility

Detect differences between declared and runtime state.

Rollback

Use version history to support controlled recovery.

Integrations & Connected Systems

Cloud

AWS EKS | Azure AKS | Google GKE

Source Control

GitHub | GitLab | Azure DevOps

CI/CD

GitHub Actions | GitLab CI | Azure Pipelines | client tooling

Observability

OpenTelemetry ecosystem | cloud monitoring | metrics/logging tools

Security

Identity | secrets | scanning | policy tooling

Platform Engineering

Backstage / developer portals | self-service workflows where required

ENGAGEMENT CHANNELS

Engagement Model

Fixed Cost Model

Defined assessment, migration phase or clearly scoped implementation.

Sprint-Based Model

Iterative engineering with prioritized outcomes and regular review.

Time & Material Model

Ongoing modernization, platform engineering or embedded specialist support.

Security & Governance

Security & Governance

Design workload identity, secrets and policy as platform capabilities rather than afterthoughts.

01

Identity & Access

Least privilege and role-aware access.

02

Secrets

Keep credentials out of code and unmanaged configuration.

03

Data Protection

Protect sensitive data according to workload requirements.

04

Environment Boundaries

Separate development, staging and production appropriately.

05

Auditability

Keep useful deployment and operational history.

06

Recovery

Plan backup, rollback and incident paths according to business impact.

Kubernetes security spans cluster access, workload permissions, images, secrets, network exposure and deployment pipelines. We apply controls according to the threat model and cloud environment, while keeping approved developer workflows usable enough that teams do not bypass them.

Why Choose Virtual Coders for Kubernetes & Cloud-Native Engineering?

Virtual Coders combines Kubernetes and cloud engineering with application development, which helps us evaluate whether workloads are actually Kubernetes-ready and design deployment patterns around how the software behaves in production. We can also connect Kubernetes to platform engineering, CI/CD, observability and AI workload requirements, giving clients a path beyond basic cluster setup toward a reusable cloud-native operating model.
Capabilities Diagram
Clients results background

"Game-Changing Custom SaaS Solutions – Highly Recommended! Working with Virtual Coders to develop our custom SaaS platform was transformative. Their team grasped our unique needs and delivered a robust solution, greatly enhancing our operations. Their attention to detail and proactive communication made the process smooth and enjoyable. Highly recommended for Australian companies seeking to enhance their software solutions!"

Rick Giesel

Rick Giesel

Owner, ICT

Logo icon watermark

Why Choose Virtual Coders for Kubernetes & Cloud-Native Engineering?

✓Full-stack application + platform engineering perspective.

✓Architecture choices connected to real product and operational requirements.

✓Cloud, DevOps, API, data and integration capability in one delivery team.

✓Incremental modernization rather than unnecessary rewrites.

✓No unsupported certification, compliance or performance claims.

Kubernetes & Cloud-Native Engineering

Frequently Asked Questions

Avatar
Avatar
Avatar

Planning a Kubernetes Migration or Platform?

They can include architecture, cluster/platform implementation, application containerization, migration, GitOps, observability, security and operational enablement.

Not always. Kubernetes is valuable when workload scale, orchestration, portability or platform standardization justify its operational complexity. Simpler managed runtimes may be better for some applications.

Yes. We can design managed Kubernetes environments across AWS, Azure and Google Cloud according to the client's cloud strategy.

Yes, after assessing application dependencies, state, networking, storage and operational readiness. Some applications may need refactoring before migration.

Yes. GitOps can be used to make Kubernetes configuration and deployment declarative and reviewable, using tools such as Argo CD where appropriate.

Yes. We can implement metrics, logs, traces, health checks and alerting using cloud-native and OpenTelemetry-compatible patterns.

Yes. CNCF research shows Kubernetes is increasingly used for production AI workloads, but AI infrastructure also introduces GPU, model-serving, data and observability requirements.

Security typically includes RBAC, workload identities, secrets, image and dependency controls, network exposure, policy and secure delivery pipelines according to the environment.

Contact Us

SEND US A MESSAGE.

Productive Team collaborating

READY TO ACCELERATE YOUR TECH JOURNEY?

Partner with our expert engineers to transform your ideas into scalable, high-performance solutions tailored to your business needs.