Service · Cloud & Platform Engineering

Cloud-Native Applications Built for Real Platforms and Real Operations

PalC designs and builds cloud-native applications that run reliably on modern platforms - platform-aware microservices, REST APIs, multi-tenant control planes, and lifecycle-safe application design for Kubernetes, private cloud, and regulated environments.

Cloud-Native Application Stack - PalC Coverage
Clients / ConsumersWeb · Mobile · API · Service-to-Service
API Gateway / IngressREST · OpenAPI · Envoy · Nginx
AuthOIDC · JWT · RBAC
Microservices LayerGo · Python · gRPC · Event-Driven · Message Queues
Control PlaneMulti-tenant · Policy · Workflows
Backend & DataMongoDB · Redis · PostgreSQL · Object Storage
PlatformKubernetes · Cilium · Helm
Observability & CI/CDPrometheus · Jaeger · ArgoCD · GitHub Actions
APIOpenAPI-driven
K8sPlatform-aware
ZeroDowntime Upgrades
MicroservicesREST / gRPCKubernetesGitOps
APIOpenAPI-first
ZeroDowntime Upgrades
K8sPlatform-integrated

Cloud-native application development is not just about containers or microservices. It is about building applications that behave predictably at scale, integrate cleanly with infrastructure, and remain operable over time. PalC focuses on platform-aware cloud-native applications where application logic, networking, security, and lifecycle automation are designed together - shaped by work on sovereign and private cloud platforms, network-centric orchestration systems, and distributed multi-tenant environments.

Core Capabilities

Depth across cloud-native architecture, microservices, and platform integration

PalC builds cloud-native applications that work natively with Kubernetes, networking policies, identity systems, and observability tooling - not just applications that happen to run in containers.

01

Cloud-Native Application Architecture

Design of cloud-native application architectures using microservices, APIs, and event-driven patterns - aligned with platform constraints, scale requirements, and operational realities of Kubernetes and private cloud environments.

  • Microservices decomposition aligned with platform behaviour
  • Event-driven architecture with message queues and pub/sub
  • Domain-driven service boundary design
  • Stateful vs stateless service design decisions
  • API-first design with OpenAPI / Swagger specifications
02

Microservices & REST API Development

Development of scalable microservices and REST-based APIs that integrate cleanly with orchestration, networking, and security layers - OpenAPI-driven, versioned, and designed for platform-aware operation.

  • RESTful API development - OpenAPI 3.x / Swagger-driven
  • gRPC service development for internal service communication
  • API versioning strategies and backward compatibility
  • Service-to-service authentication - JWT, mTLS, OIDC
  • Rate limiting, circuit breaking, and retry policy design
03

Platform-Integrated Applications

Applications designed to work natively with Kubernetes, networking policies, identity systems, and observability tooling - not retrofitted for the platform after the fact.

  • Kubernetes-native service deployment and lifecycle management
  • Network policy aware application design with Cilium
  • Structured logging, metrics, and distributed tracing built-in
  • Health check endpoints - liveness, readiness, and startup probes
  • Secret management integration - Vault, Kubernetes secrets
04

Multi-Tenant & Control-Plane Applications

Development of applications that manage tenants, resources, policies, and workflows across distributed environments - cloud platform control planes, network resource management systems, and policy orchestration engines.

  • Multi-tenant resource isolation and namespace management
  • RBAC-integrated tenant and user management APIs
  • RESTful control plane APIs with OpenAPI specification
  • Policy workflow engines and approval chains
  • Audit logging and compliance trail by design
05

Lifecycle & Upgrade-Safe Design

Applications engineered for rolling upgrades, version compatibility, and controlled change - so platform upgrades and application releases do not cause unexpected disruptions to tenants or dependent services.

  • Rolling upgrade strategy design - zero downtime by default
  • API versioning and deprecation lifecycle management
  • Schema migration strategies for stateful services
  • Feature flag infrastructure for controlled rollouts
  • Canary and blue-green deployment pipeline integration
06

Observability & Operations Integration

Applications instrumented for production observability from day one - structured logging, Prometheus metrics exposition, distributed tracing, and integration with CI/CD-driven release pipelines.

  • Prometheus metrics instrumentation - custom application metrics
  • Distributed tracing with OpenTelemetry and Jaeger
  • Structured JSON logging with correlation IDs
  • CI/CD pipeline integration - GitHub Actions, GitLab CI
  • Configuration-as-code with environment-driven settings

Technical Deep Dive

Proven engineering across microservices, APIs, and platform integration

PalC engineers build applications that feel native to the platform - OpenAPI-first APIs, Kubernetes health probe design, Prometheus metrics, and multi-tenant control plane patterns used in production deployments.

REST API - OpenAPI-first Design

OpenAPI 3.x specification-driven API development

API schema defined first in OpenAPI - server stubs and client SDKs generated automatically, ensuring API and implementation stay in sync across versions.

# OpenAPI 3.x - tenant provisioning endpoint
paths:
  /api/v1/tenants:
    post:
      summary: Create tenant
      security: [{ bearerAuth: [] }]
      responses:
        "201":
          description: Tenant created
SpecOpenAPI 3.xCode-genGo · Python · TSAuthBearer / OIDCVersioningURI path / v1/v2

Kubernetes - Platform-native Service Design

Health probes, graceful shutdown, and resource limits

Kubernetes-aware deployment manifests - liveness and readiness probes, SIGTERM-handled graceful shutdown, and topology spread constraints for resilient placement.

# Kubernetes deployment - platform-native design
containers:
  - name: tenant-api
    image: registry/tenant-api:v1.4.2
    resources:
      requests: {cpu: 100m, memory: 128Mi}
      limits: {cpu: 500m, memory: 512Mi}
    livenessProbe:
      httpGet: {path: /healthz, port: 8080}
ProbesLiveness + ReadinessShutdownGraceful SIGTERMResourcesRequests + LimitsUpgradeRollingUpdate

Observability - Prometheus Metrics

Custom application metrics with Prometheus client

Application-level Prometheus metrics exposed at /metrics - API request latency histograms, business operation counters, and queue depth gauges for NOC-ready dashboards.

# Prometheus instrumentation - Go service
var (
  apiLatency = prometheus.NewHistogramVec(
    prometheus.HistogramOpts{Name: "api_request_latency_seconds"},
    []string{"method","status"},
  )
)
ProtocolPrometheus / OTelTracingJaeger / TempoLoggingStructured JSONDashboardGrafana

Multi-tenant Control Plane - RBAC Design

Role and resource scoping for multi-tenant APIs

RBAC model integrated into the application's control plane - roles scoped per tenant, resource-level permission checks, and audit logging on every privileged operation.

# RBAC middleware - tenant-scoped permission check
func RequirePermission(resource, action string) Middleware {
  return func(next Handler) Handler {
    return func(ctx Context) error {
      if !can(ctx.User, resource, action) { return ErrForbidden }
      return next(ctx)
    }
  }
}
ScopePer-tenant RBACAuditEvery access loggedIdentityOIDC / JWT claimsPolicyResource-level

Technology Stack

Application, platform, and operations tooling

PalC builds cloud-native applications using open-source toolchains that are portable, observable, and tightly integrated with the Kubernetes platform layer.

Cloud-native application layers - PalC engineering coverage
Client & API GatewayEnvoy · Nginx · Kong · API Gateway patterns
MicroservicesGo · Python · gRPC · REST · Event-driven (Kafka / NATS)
AuthOIDC · JWT · mTLS
Control Plane & WorkflowsMulti-tenant APIs · RBAC · Policy engines · Audit trail
Backend & DataMongoDB · Redis · PostgreSQL · Object Storage (S3-compatible)
MessagingKafka · NATS · RabbitMQ
PlatformKubernetes · Cilium · Helm · ArgoCD · Kustomize
IaCTerraform · Ansible
Observability & CI/CDPrometheus · Grafana · Jaeger · OTel · GitHub Actions · GitLab CI

Application & Platform

  • OrchestrationKubernetes · Docker
  • ArchitecturesMicroservices · Event-driven
  • APIsREST (OpenAPI) · gRPC
  • LanguagesGo Python Typescript
  • PackagingHelm Kustomize

Backend & Data

  • Document DBMongoDB
  • Cache / StateRedis
  • RelationalPostgreSQL
  • MessagingKafka NATS
  • Object StorageS3-compatible

Automation & Observability

  • CI/CDGitHub Actions · GitLab CI
  • GitOpsArgoCD · Flux
  • MetricsPrometheus · Grafana
  • TracingJaeger Tempo
  • LoggingStructured JSON · Loki

Our Approach

A structured approach to cloud-native application delivery

From platform alignment and architecture design through development, integration, and production operations - PalC manages the full engagement.

Phase 01

Application & Platform Alignment

Understanding how applications interact with infrastructure, networking, security, and orchestration.

Phase 02

Design & Development

Building microservices, APIs, and workflows using cloud-native design principles and OpenAPI-first patterns.

Phase 03

Integration & Validation

Integrating applications with platform services and validating behaviour under scale, load, and failure conditions.

Phase 04

Deployment & Operations Support

Supporting production deployment, monitoring, rolling upgrades, and long-term application and platform reliability.

Application StackGo / PythonREST / gRPCOpenAPI 3.xKubernetesMongoDB / RedisKafka / NATSPrometheus / GrafanaArgoCD / GitHub Actions

Deployment Scenarios

Where this is applied

Proven patterns for cloud platform control systems, network-centric applications, regulated environments, and AI data platforms.

Cloud Platform Control Systems

Applications that manage cloud resources, tenants, policies, and orchestration workflows - REST APIs over Kubernetes-based control planes for private cloud and hybrid infrastructure.

Network-Centric Platforms

Applications tightly coupled with networking, load balancing, traffic control, and observability systems - where application logic and platform behaviour are co-designed.

Enterprise & Regulated Environments

Cloud-native applications designed for compliance, auditability, and operational control - RBAC-integrated, policy-driven deployments with zero-downtime upgrades.

AI & Data Platforms

Applications supporting AI pipelines, data ingestion workflows, and distributed processing environments - with real-time instrumentation and object storage integration.

Multi-Tenant SaaS Platforms

Applications with per-tenant data isolation, RBAC, usage metering, and self-service provisioning APIs - designed for reliable scaling and operational clarity.

Telco & Network Orchestration Systems

Control plane applications for network resource management - VNF lifecycle, service chain orchestration, and multi-platform network lifecycle management.

Business Outcomes

What organisations achieve with PalC-built cloud-native applications

Applications that scale reliably with platform growth

Designed for horizontal scaling and platform evolution - stateless service design and resource budgeting prevent contention growth.

Reduced operational friction during upgrades and change

Rolling upgrades and compatibility by design - schema migration, API versioning, and feature flag infrastructure keep releases stable.

Stronger alignment between applications and infrastructure

Platform-aware design means applications fit the platform and avoid retrofit failures.

Improved observability and troubleshooting

Prometheus metrics, distributed tracing, and structured logging built in from day one.

Faster delivery without compromising stability

Controlled release automation and GitOps-driven canary deployments accelerate delivery while reducing incidents.

Compliance-ready from day one

RBAC and audit logging are built into the application architecture - not bolted on later.

Application Operations

Applications that are operable in production - not just deployed

PalC builds application observability and operational tooling alongside the application itself - Prometheus metrics, distributed tracing, and CI/CD delivery pipelines integrated from the first release.

  • Prometheus metrics from first release - custom application metrics instrumented during development.
  • Distributed tracing across service boundaries - OpenTelemetry trace propagation and full request path visibility.
  • ArgoCD-driven controlled releases - GitOps-based delivery with Argo Rollouts for canary and blue-green strategies.
  • Runbooks for application failure scenarios - restart storms, DB pool saturation, queue backpressure, and certificate expiry.
Alerting & On-callAlertManager · PagerDuty · Slack
Dashboards & SLOsGrafana · SLO dashboards · Error budgets
Metrics · Tracing · LogsPrometheus · Jaeger · Loki · OTel
Delivery & RolloutsArgoCD · Argo Rollouts · GitHub Actions
Application LayerMicroservices · APIs · Kubernetes
ObservabilityGitOps-drivenZero-downtime

Ready to build platform-native cloud applications?

Whether building a new cloud-native control plane, migrating a monolith to microservices, or adding observability and lifecycle safety to existing services - PalC engineers can accelerate your delivery.

Get in touch

Discuss your infrastructure goals with our experts.

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