Building a Small PaaS Platform through Process, Standardization, Automation, and Cloud‑Native Technologies

Many companies face heavy workloads for technical support roles—domain configuration, environment deployment, log analysis, firewall rules, and other tasks—that require extensive communication with developers, leading to low efficiency and bottlenecks.

Outdated system architecture that cannot meet performance and reliability needs.

Inflexible IT architecture causing high cost for new or changed business modules.

Complex, tangled system functions with tightly coupled custom code.

Numerous services built on heterogeneous technology stacks.

Insufficient handover during staff turnover, resulting in limited knowledge of deployment environments.

The remedy is to adopt process‑driven, standardized, automated, and platform‑based approaches.

Process

Proactively catalogue operational tasks, create standardized workflows—especially for multi‑person collaborations such as application releases—and embed them into a workflow platform so that every step is visible, traceable, and executed consistently.

Standardization

Define deployment standards per application type (e.g., web apps, service‑oriented .NET Core apps, micro‑services) and build deployment scripts and tooling on Kubernetes according to these conventions, reducing complexity caused by diverse application stacks.

Automation

Early ad‑hoc scripts executed via SSH quickly become unmanageable as scale grows; even after adopting tools like Puppet, SaltStack, or Ansible, the core problems persist without a unified automation layer.

Platformization

Platformization must be built on top of the previous three pillars; without clear processes and standards, a platform would merely aggregate automation tools without solving core operational challenges.

The focus here is on a PaaS solution—application‑level, not IaaS—aimed at helping developers run and manage code rather than managing raw infrastructure.

PaaS benefits include application aggregation (e.g., launching a Redis container on demand), service discovery, auto‑scaling, state management, monitoring, disaster recovery, security controls, and rapid deployment.

With Docker becoming the preferred container technology, Kubernetes was chosen as the orchestration foundation, offering resource scheduling, service discovery, self‑healing, security configuration, job support, automatic rollback, internal DNS, health checks, stateful support, monitoring, scaling, load balancing, gray‑release, disaster recovery, and HA.

Below is a minimal PaaS architecture diagram:

The top Ingress service functions like a traditional load balancer, providing request routing for external APIs (via Ocelot) and sites.

Service acts as a proxy for backend Pods, offering registration and discovery; it must be accessed through Ingress.

Pod represents the actual service instance.

Internal DNS assigns a domain name to each service after it is running.

The Kubernetes cluster runs on Tencent Cloud TKE, which enables the built‑in l7-lb-controller for HTTP/HTTPS load balancing and supports nginx‑ingress as an alternative.

Key Platform Capabilities

Continuous Application Deployment : Visual, one‑click deployment of images and components with automatic upgrade.

Application Elastic Scaling : Predictive scaling of containers and VMs based on load and resource usage.

Unified Management of Containers and Components : Centralized handling of images, containers, and all related components for global configuration, upgrade/rollback, monitoring, and fault handling.

High Reliability : Automatic container recovery and resource reallocation on node failure, ensuring near‑zero downtime.

Application Dockerization : Supports common workloads such as .NET Core, Jexus, Nginx, Redis, MongoDB, etc.

PaaS Functional Components

Implementation requires several foundational modules:

Image Management : Build runtime images from base middleware, application packages, and configuration using Visual Studio, Helm, Draft, and internal training.

DNS Management : Custom internal DNS platform for unified domain handling.

Service Management : Kubernetes Deployment templates covering Ingress, Service, and ReplicationController for scaling and lifecycle operations.

Pod Management within Services : Native Kubernetes features for pod status and log inspection.

Log Management : Forward logs to a centralized ELK platform for troubleshooting and analytics.

Monitoring Management : Stack based on cAdvisor, InfluxDB, Prometheus/Heapster, Grafana, or Zabbix (see reference link).

By adopting this lightweight PaaS on TKE, a small team can handle daily operations, dramatically reducing manual effort while maintaining scalability and reliability. For larger enterprises, additional modules such as multi‑cluster management, security, workflow, and billing would be needed.