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Hi! This is the sixth article on Tungsten Fabric architecture parsing, which introduces the collection and analysis of TF, as well as deployment.

A series of articles on Tungsten Fabric architecture analysis, presented to you by the TF Chinese community, are designed to help new entrants to the TF community to answer questions. We will systematically introduce the features of TF, how it works, how to collect / analyze / deploy, how to orchestrate, how to connect to physical networks, and so on.

Collection and Analysis of Tungsten Fabric

Tungsten Fabric gathers information from the cloud infrastructure (compute, network, and storage) and the workloads running on it for operational monitoring, troubleshooting, and capacity planning.

Data is collected in a variety of formats, such as system logs, structured messages (called Sandesh), Ipfix, Sflow, and SNMP. Objects such as vRouters, physical hosts, virtual machines, interfaces, virtual networks, and policies are modeled as user-visible entities (UVE), and the properties of the UVE can come from a variety of sources in different formats.

The architecture of the analysis collection is shown in the following figure:

The IP address of the target collector or the load balancer configured for the collector can be configured for the data source. The responsibility for SNMP polling is distributed by Zookeeper on different nodes.

The analysis node formats the incoming data into a common data format and then sends it to the Cassandra database through the Kafka service.

API URL can use ha-proxy or some other load balancer for load balancing.

The responsibility for collecting UVE data is distributed among Analytics nodes using Zookeeper, so API queries for UVE data are copied by the receiving node to other Analytics nodes, and those queries that hold the data related to the request return the response to the original node, which checks the response and organizes it into the reply that the requester will receive.

The responsibility for alert generation is also distributed among nodes, so the alert generation feature subscribes to the Kafka bus in the Analyticsdb node to observe the data needed to calculate whether the alert condition is met, because this data may be collected by other nodes.

UVE hashes among multiple Kafka topics, which are distributed among Alarm Gen functions to effectively spread the load.

Deployment of Tungsten Fabric

The latest version of Tungsten Fabric (version 5. 0 and later) uses a micro-services architecture based on Docker containers. The microservices are grouped into pod, and these pod are assigned to the server during deployment according to the role.

The relationship between microservices and pod is shown in the following figure:

The architecture is combinable, which means that each Tungsten Fabric role can be extended separately with multiple pod running on different servers to support the resiliency and performance requirements of a particular deployment.

Due to the nature of the algorithm used to select active nodes in Zookeeper, the number of pod deployed in Controller and Analytic nodes must be odd, but may vary between pod types.

Nodes are logically grouped, their pod can be deployed on different servers, and servers can run pod from different node types.

API and Web GUI services can be accessed through load balancers or third-party load balancers deployed during Contrail installation. Using third-party load balancers allows pod to be on different subnets, which is a common situation where pod needs to be placed in different racks in the data center for resilience.

Control pod can increase or decrease according to the number of compute nodes in the cluster, with a maximum of 1000 nodes per control node. Additional control nodes can be deployed in specific use cases, wherein the controller node can deploy the management computing node remotely.

The number of compute nodes is adjusted as expected by the workload deployed by the choreographer. Within the compute node, the transponder function is not implemented in the container (see "deployment options for vRouter", the fifth article in this series).

The layout of Tungsten Fabric services across servers, controlled by configuration files read by the deployment tool, can be Ansible (using playbooks) or Helm (using diagrams). Sample manuals and diagrams can be used to cover simple all-in-one deployments where all services are running in the same VM, as well as examples of high availability involving multiple VM or bare metal servers. Examples are also provided where orchestrator and Tungsten Fabric run in a public cloud such as Amazon Web Services,Google Cloud Engine,Microsoft Azure, and the workload is also running there.

More details about deployment tools and how to use them

Please visit the Tungsten Fabric website (www.tungsten.io)

Chinese website (www.tungstenfabric.org.cn)

MORE

More Tungsten Fabric parsing articles

Part I: main features and use cases of TF

Article 2: how TF works

Part 3: detailed explanation of vRouter architecture

Part IV: service chain of TF

Part 5: deployment options for vRouter

About Tungsten Fabric:

The Tungsten Fabric project is an open source project protocol that is developed based on standard protocols and provides all the components necessary for network virtualization and network security. The components of the project include: SDN controller, virtual router, analysis engine, northbound API release, hardware integration functions, cloud orchestration software and extensive REST API.

About the TF Chinese Community:

TF Chinese Community is initiated spontaneously by a group of Chinese volunteers who follow and love SDN, including technology veterans, market veterans, industry experts and experienced users. It will serve as a bridge between the community and China, disseminate information, submit questions, organize activities, and unite all forces interested in the multi-cloud Internet to effectively solve the problems encountered in the process of cloud network construction.

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