Cooperation case-谐云

Communication Industry Solutions

Operators are still the largest industry customers of HarmonyCloud in terms of O&M volume and cluster scale. The hundreds of millions of visits in a single day and the scale of a single cluster with over 1,000 physical machines show that HarmonyCloud has a lot of production experience and considerable operation level in the telecom operator industry.

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Communications Industry Solution Architecture

Solve Pain Points

01
High Availability
02
Network Structure
03
Monitoring Requirements
04
Service Port
05
Development Language

Program Advantages

Floating point IP

Through ingress + custom probes, realize VIP switching ability in multiple scenarios such as pod exceptions and process exceptions.

Multi-network Card Solution

Dual CNI solution (Calico+Macvian) is used to realize dual network card access and differentiate between internal and external network access traffic.

Monitoring and Packet Capture

Start the monitoring agent container through daemonset to capture TCP and UDP network packets.

Multi-Port listening

Enhance the nginx customization window of the ingress component to provide the ability to configure multiple service ports.

Multi-language Compatibility

Optimized CI pipeline, support for a variety of development languages to build the environment, support for war packages, jar packages and other image building methods, and support for scripting the construction of the image.

Products Involved

HarmonyCloud Container Platform

Support customers to smoothly complete containerization migration transformation and large-scale production.

Microservices Governance

Complete Service Governance for Istio-based Mesh Solutions

Cloud Native Middleware Platform

A middleware management and provisioning platform for fully automated operations and maintenance based on the Kubernetes system.

Application Scenarios

Large-scale High-performance Middleware Cloud

Cloud-Network Collaboration

The Operator Dual-center Disaster Recovery

Harmonycloud provides adaptive cluster planning, resource scheduling policies,

mixing deploy short and long tasks, and elastic expansion policies according to customer specific big data platform construction needs.