Express YourSelf !

Canary has mode deployment time, because more iteration. 10% increase means 10 iteration. 

Blue Green has less. 

Fine tune Max Surge, Max unavailable etc. 

Traffic Mirroring is for ML load also. 

image compression, local registry etc needed because model size is big. 

There is no inter cluster redundancy by K8s. We need to use proprietary solution OR cloud. 

In telecom a component is connected with multiple. E.g vCU with vDU, EMS, 5GC

Sync Driver

GRAF framework with AI, Management Data analytics function(MDAF), policy driven 

A1 interface is better than MDAF. As MDAF is at core network. it will add latency. 

Nephio : open source project : LF + Google

Automate LCM of cloud infra and NF. Intent based declarative approach

LinkedIN : saurabhswaraj

GitOps based approach

1. N/w driver is GR aware

2. DB drive sync 2 MySQL

YAML PV and DB table synch

Each cluster has GRAPH controller

We can have several other use cases also

GRAPH is framework. We can develop our own driver. 

GRAPH f/w = Redundancy Manager at Orchestrator + GRAPH controller at each cluster

Based on CRD, different driver will be deployed at each K8s cluster.

Still GRAPH is not open source. It is in process for open source. At present it is in R&D stage.

GRAPH can work with many orchestrator including Nephio 

All DB has Replication Manager. Why do we need DB drive? DB drive is not novelty. Our novelty is framework. 

Policy based, when failed comes up again, what will happen. 

Kept has Two Operators: App LCM and for Metrics

Day1 and Day2 operation

Integrated with Argo

Metrics based scaling: HPA and Scala

works for outside K8s application

It works with DORA metrics

Multistage application delivery. 

Each pod will have local bucket and then implement leaky bucket algorithm. 

Start bucket size with big number

Learning from rate limiting journey

Service with smaller threshold has higher precision

higher threshold has upto 10% error rate

pod has its own swimlane 

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For inter+intra rate limit, need to synch API-GW and serviceMesh. 

Unified config management 

Naavik knows, where service resides (Kubecon Paris) 

Canary release pattern : First canary call, the service registry will read from DB and put it in cache. For remaining, no need to access DB. Response from cache. Canary pod can put value in S3 bucket, for further optimization, and notify all pods to read form s3 bucket

* rust based data plane is  pretty light

* We can use any Ingress Controllers (IC) with Linkerd. IC are based on (1) NGINX (2) Envoy (2) HA Proxy. NGINX IC has Mister-Minion model

* security : authz policy, mTLS 

* intra cluster URL. So no need to go to LB for intra cluster. 

* Gateway API (GW-API) integration

* 1.17 Linkerd has many new features.

* canary deployment