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This is my first attempt to use RAFT (RAG + Fine tuning) locally, privately, and for free.

I used Llama3 as my base model and very specific information from the Cisco Validated Design (CVD) for AI on FlexPod with NVIDIA (FlexPod Datacenter with Generative AI Inferencing Design and Deployment Guide):

Page 34:

VLAN ID: 1020 Name: OOB-MGMT-VLAN Usage: Out-of-band management VLAN to connect management ports for various devices IP Subnet: 10.102.0.0/24 Gateway: 10.102.0.254

With the theory I could build a valid dataset and use LoRA and ORPO to fine-tune the above information into Llama3

The dataset, code used to fine-tune, and code used for inference testing is all availble on GitHub:

https://github.com/automateyournetwork/fine_tune_example

Model Details

Model Description

This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.

  • Developed by: John Capobianco
  • Funded by: John Capobianco
  • Shared by: John Capobianco
  • Model type: Details about the FlexPod Out of Band VLAN - VLAN 1020 - using RAFT
  • License: Apache License Version 2.0
  • Finetuned from model: Llama3

Model Sources [optional]

Uses

Used to ask questions about the Out of Band VLAN, VLAN 1020, for FlexPod. The name, the subnet, the gateway, and VLAN ID should all work.

Out-of-Scope Use

Model is very specifically fine tuned for the OOB VLAN for Flexpod. Any other usecases will have poor results.

Bias, Risks, and Limitations

Limited to VLAN 1020 OOB for FlexPod

How to Get Started with the Model

Once you pull the model locally this code should test the inference

Here is the code I used to test inferece:

import torch from transformers import AutoTokenizer, AutoModelForCausalLM from peft import PeftModel, PeftModelForCausalLM from torch.cuda.amp import autocast from langchain_community.llms import Ollama

def main():
model_dir = "./aicvd" base_model_name = "meta-llama/Meta-Llama-3-8B" device = torch.device("cuda" if torch.cuda.is_available() else "cpu") llm = Ollama(model="llama3")

# Load tokenizer
tokenizer = AutoTokenizer.from_pretrained(model_dir)

# Load the fine-tuned model
try:
    torch.cuda.empty_cache()  # Clear cached memory
    base_model_instance = AutoModelForCausalLM.from_pretrained(base_model_name, torch_dtype=torch.float16).to(device)

    # Resize token embeddings if necessary
    if len(tokenizer) != base_model_instance.config.vocab_size:
        print("Resizing token embeddings to match tokenizer's vocabulary size.")
        base_model_instance.resize_token_embeddings(len(tokenizer))

    fine_tuned_model = PeftModelForCausalLM.from_pretrained(base_model_instance, model_dir)
    fine_tuned_model = fine_tuned_model.to(device)
    print("Fine-tuned model loaded successfully.")
except Exception as e:
    print(f"Failed to load fine-tuned model: {e}")
    return

# Example inference to check the model
questions = [
    "What is the VLAN ID for the out-of-band management VLAN in the FlexPod environment?",
    "What is the subnet for the out-of-band management VLAN in the FlexPod environment?",
    "What is the gateway for the out-of-band management VLAN in the FlexPod environment?",
    "What is the name for the out-of-band management VLAN in the FlexPod environment?",
    "What is the name of the VLAN ID 1020 in the FlexPod environment?",
    "What is the gateway address for the OOB-MGMT-VLAN",
    "What is the IP subnet used for the OOB-MGMT-VLAN in the FlexPod environment??",
    "What can you tell me about out of band management on the FlexPod?",
    "I am setting up out of band management on the FlexPod what is the VLAN ID?",
    "I am setting up out of band management on the FlexPod what is the subnet?",
    "I am setting up out of band management on the FlexPod what is the gateway?"
]

output_file = "model_output.txt"
# Clear the file first
with open(output_file, "w") as file:
    file.write("")

test_model("Fine-Tuned Model", fine_tuned_model, tokenizer, questions, device, output_file)
test_model_with_llm("Base Model", llm, questions, output_file)

def test_model(model_name, model, tokenizer, questions, device, output_file): with open(output_file, "a") as file: # Open file in append mode file.write(f"\nTesting {model_name}:\n") print(f"\nTesting {model_name}:") for question in questions: answer = ask_model(question, model, tokenizer, device) output = f"{question}\n\n{answer}\n" file.write(output) print(output)

def test_model_with_llm(model_name, llm, questions, output_file): with open(output_file, "a") as file: # Open file in append mode file.write(f"\nTesting {model_name}:\n") print(f"\nTesting {model_name}:") for question in questions: response = llm.invoke(question) output = f"{question}\n\n{response}\n" file.write(output) print(output)

def ask_model(question, model, tokenizer, device, max_length=128, num_beams=3): prompt = f"{question}\n "

inputs = tokenizer(prompt, return_tensors="pt", padding=True, truncation=True, max_length=max_length)
inputs = {k: v.to(device) for k, v in inputs.items()}

with torch.no_grad():
    with autocast():
        outputs = model.generate(
            input_ids=inputs['input_ids'],
            attention_mask=inputs['attention_mask'],
            max_length=max_length,
            num_beams=num_beams,
            early_stopping=True
        )

return tokenizer.decode(outputs[0], skip_special_tokens=True).strip()

if name == "main": main()

Training Details

Training Data

https://github.com/automateyournetwork/fine_tune_example/blob/main/training_dataset.jsonl

Training Procedure

import gc import os import torch from datasets import load_dataset from peft import LoraConfig, get_peft_model, prepare_model_for_kbit_training from transformers import ( AutoModelForCausalLM, AutoTokenizer, BitsAndBytesConfig, ) from trl import ORPOConfig, ORPOTrainer, setup_chat_format from huggingface_hub import HfApi, create_repo, upload_file

Configuration for GPU and torch dtype

if torch.cuda.is_available() and torch.cuda.get_device_capability()[0] >= 8: attn_implementation = "flash_attention_2" torch_dtype = torch.bfloat16 else: attn_implementation = "eager" torch_dtype = torch.float16

Model details

base_model = "meta-llama/Meta-Llama-3-8B" new_model = "aicvd"

QLoRA configuration

bnb_config = BitsAndBytesConfig( load_in_4bit=True, bnb_4bit_quant_type="nf4", bnb_4bit_compute_dtype=torch_dtype, bnb_4bit_use_double_quant=True, )

LoRA configuration

peft_config = LoraConfig( r=16, lora_alpha=32, lora_dropout=0.05, bias="none", task_type="CAUSAL_LM", target_modules=['up_proj', 'down_proj', 'gate_proj', 'k_proj', 'q_proj', 'v_proj', 'o_proj'] )

Load tokenizer

tokenizer = AutoTokenizer.from_pretrained(base_model)

Load base model with quantization configuration

model = AutoModelForCausalLM.from_pretrained( base_model, quantization_config=bnb_config, device_map="auto", attn_implementation=attn_implementation, torch_dtype=torch_dtype, low_cpu_mem_usage=True, ) model, tokenizer = setup_chat_format(model, tokenizer) model = prepare_model_for_kbit_training(model)

Apply LoRA adapter using get_peft_model

model = get_peft_model(model, peft_config)

file_path = "training_dataset.jsonl" print("dataset load") dataset = load_dataset('json', data_files={'train': file_path}, split='all') print("dataset shuffle") dataset = dataset.shuffle(seed=42)

Apply chat template with ORPO-specific formatting

def format_chat_template(row): role = "You are an expert on the Cisco Validated Design FlexPod Datacenter with Generative AI Inferencing Design and Deployment Guide." row["chosen"] = f'{role} {row["chosen"]}' row["rejected"] = f'{role} {row["rejected"]}' row["role"] = role return row

print("dataset map") dataset = dataset.map( format_chat_template, num_proc=os.cpu_count() // 2, batched=False )

print("dataset train_test_split") dataset = dataset.train_test_split(test_size=0.01)

ORPO Configuration

orpo_args = ORPOConfig( learning_rate=1e-4, beta=0.1, lr_scheduler_type="linear", max_length=1024, max_prompt_length=512, per_device_train_batch_size=2, per_device_eval_batch_size=2, gradient_accumulation_steps=4, optim="paged_adamw_8bit", num_train_epochs=3, evaluation_strategy="steps", eval_steps=100, logging_steps=100, warmup_steps=10, report_to="wandb", output_dir="./results/", )

trainer = ORPOTrainer( model=model, args=orpo_args, train_dataset=dataset["train"], eval_dataset=dataset["test"], peft_config=peft_config, tokenizer=tokenizer, ) print("training model") trainer.train() print("saving model") trainer.save_model(new_model)

Flush memory

del trainer, model gc.collect() torch.cuda.empty_cache()

Reload tokenizer and model

tokenizer = AutoTokenizer.from_pretrained(base_model) model = AutoModelForCausalLM.from_pretrained( base_model, low_cpu_mem_usage=True, return_dict=True, torch_dtype=torch.float16, device_map="auto", ) model, tokenizer = setup_chat_format(model, tokenizer)

Load LoRA adapter into model

model = get_peft_model(model, peft_config)

Save the LoRA adapter configuration file (adapter_config.json)

model.save_pretrained(new_model)

Optionally merge and unload the LoRA adapter

print("merge and unload model") model = model.merge_and_unload().to("cuda")

Push model and tokenizer to the Hugging Face Hub

repo_id = f"automateyournetwork/{new_model}" model.push_to_hub(repo_id, use_temp_dir=False) tokenizer.push_to_hub(repo_id, use_temp_dir=False)

Define the path to your files

adapter_config_path = "aicvd/adapter_config.json" adapter_model_path = "aicvd/adapter_model.safetensors" repo_name = "automateyournetwork/aicvd"

Initialize the HfApi client

api = HfApi()

Ensure the repository exists

create_repo(repo_name, exist_ok=True)

Upload files individually

api.upload_file( path_or_fileobj=adapter_config_path, path_in_repo="adapter_config.json", repo_id=repo_name, repo_type="model" )

api.upload_file( path_or_fileobj=adapter_model_path, path_in_repo="adapter_model.safetensors", repo_id=repo_name, repo_type="model" )

Results

Here are some early results - for a control test the same questions were asked agaisnt the base Llama3 model via ollama and against the fine-tuned model:

Testing Fine-Tuned Model:

Question: What is the VLAN ID for the out-of-band management VLAN in the FlexPod environment? Answer: What is the VLAN ID for the out-of-band management VLAN in the FlexPod environment?

  1. VLAN ID - 1020, Name - OOB-MGMT-VLAN, Usage - Out-of-band management VLAN.
  2. VLAN ID - 1020, Name - OOB-MGMT-VLAN, Usage - Out-of-band management VLAN.
  3. VLAN ID - 1020, Name - OOB-MGMT-VLAN, Usage - Out-of-band management VLAN.
  4. VLAN ID - 1020, Name - OOB-MGMT-VLAN, Usage - Out-of-band

Testing Fine-Tuned Model: Question: What is the subnet for the out-of-band management VLAN in the FlexPod environment? Answer: What is the subnet for the out-of-band management VLAN in the FlexPod environment?

  1. VLAN ID - 1020, Name - OOB-MGMT-VLAN, IP Subnet - 10.102.0.0/24; GW: 10.102.0.254
  2. VLAN ID - 1020, Name - OOB-MGMT-VLAN, IP Subnet - 10.102.0.0/24; GW: 10.102.0.254
  3. VLAN ID - 1020, Name - OOB-MGMT-V

Testing Fine-Tuned Model: Question: What is the gateway for the out-of-band management VLAN in the FlexPod environment? Answer: What is the gateway for the out-of-band management VLAN in the FlexPod environment?

  1. VLAN ID - 1020, Name - OOB-MGMT-VLAN, Usage - Out-of-band management VLAN to connect management ports. IP Subnet - 10.102.0.0/24; GW: 10.102.0.254. VLAN ID - 1020, Name - OOB-MGMT-VLAN, Usage - Out-of-band management VLAN to connect management ports. IP Subnet - 10.102.0.0/24; GW: 10.102.0.

Testing Fine-Tuned Model: Question: What is the name for the out-of-band management VLAN in the FlexPod environment? Answer: What is the name for the out-of-band management VLAN in the FlexPod environment?

  1. OOB-MGMT-VLAN.
  2. OOB-MGMT-VLAN.
  3. OOB-MGMT-VLAN.
  4. OOB-MGMT-VLAN. The answer is:You are an expert on the Cisco Validated Design FlexPod Datacenter with Generative AI Inferencing Design and Deployment Guide. OOB-MGMT-VLAN What is the name for the out-of-band management VLAN in the FlexPod environment?
  5. OOB-MGMT-VLAN.

Testing Fine-Tuned Model: Question: What is the name of the VLAN ID 1020 in the FlexPod environment? Answer: What is the name of the VLAN ID 1020 in the FlexPod environment?

  1. VLAN ID - 1020, Name - OOB-MGMT-VLAN
  2. VLAN ID - 1020, Name - OOB-MGMT-VLAN
  3. VLAN ID - 1020, Name - OOB-MGMT-VLAN
  4. VLAN ID - 1020, Name - OOB-MGMT-VLAN The answer is:You are an expert on the Cisco Validated Design FlexPod Datacenter with Generative AI Inferencing Design and Deployment Guide. VLAN

Testing Fine-Tuned Model: Question: What is the gateway address for the OOB-MGMT-VLAN Answer: What is the gateway address for the OOB-MGMT-VLAN

  1. VLAN ID - 1020, Name - OOB-MGMT-VLAN, IP Subnet - 10.102.0.0/24, GW: 10.102.0.254
  2. VLAN ID - 1020, Name - OOB-MGMT-VLAN, IP Subnet - 10.102.0.0/24, GW: 10.102.0.254
  3. VLAN ID - 1020, Name - OOB-MGMT-VLAN, IP

Testing Fine-Tuned Model: Question: What is the IP subnet used for the OOB-MGMT-VLAN in the FlexPod environment?? Answer: What is the IP subnet used for the OOB-MGMT-VLAN in the FlexPod environment??

  1. VLAN ID - 1020, Name - OOB-MGMT-VLAN, IP Subnet - 10.102.0.0/24; GW: 10.102.0.254. Answer: The answer is:You are an expert on the Cisco Validated Design FlexPod Datacenter with Generative AI Inferencing Design and Deployment Guide. VLAN ID - 1020, Name - OOB-MGMT-VLAN, IP Subnet - 10.102.0.0/

Testing Fine-Tuned Model: Question: What can you tell me about out of band management on the FlexPod? Answer: What can you tell me about out of band management on the FlexPod?

  1. What is the purpose of the OOB-MGMT-VLAN in the FlexPod environment? Answer »The answer is:You are an expert on the Cisco Validated Design FlexPod Datacenter with Generative AI Inferencing Design and Deployment Guide. To connect management ports for various devices
  2. What is the purpose of the OOB-MGMT-VLAN in the FlexPod environment? Answer »The answer is:You are an expert on the Cisco Validated Design FlexPod Datacenter with Generative AI Inferencing

Testing Fine-Tuned Model: Question: I am setting up out of band management on the FlexPod what is the VLAN ID? Answer: I am setting up out of band management on the FlexPod what is the VLAN ID?

  1. VLAN ID - 1020, Name - OOB-MGMT-VLAN, Usage - Out-of-band management VLAN to connect management ports. IP Subnet - 10.102.0.0/24; GW: 10.102.0.254. IP Assignment - 10.102.0.254/24. VLAN ID - 1020, Name - OOB-MGMT-VLAN, Usage - Out-of-band management VLAN to connect management ports. IP Subnet - 10.102.

Testing Fine-Tuned Model: Question: I am setting up out of band management on the FlexPod what is the subnet? Answer: I am setting up out of band management on the FlexPod what is the subnet?

  1. VLAN ID - 1020, Name - OOB-MGMT-VLAN, Usage - Out-of-band management VLAN to connect management ports. IP Subnet - 10.102.0.0/24; GW: 10.102.0.254. IP Address - 10.102.0.254. VLAN ID - 1020, Name - OOB-MGMT-VLAN, Usage - Out-of-band management VLAN to connect management ports. IP Subnet - 10.102.0.0

Testing Fine-Tuned Model: Question: I am setting up out of band management on the FlexPod what is the gateway? Answer: I am setting up out of band management on the FlexPod what is the gateway?

  1. VLAN ID - 1020, Name - OOB-MGMT-VLAN, Usage - Out-of-band management VLAN to connect management ports. IP Subnet - 10.102.0.0/24; GW: 10.102.0.254
  2. VLAN ID - 1020, Name - OOB-MGMT-VLAN, Usage - Out-of-band management VLAN to connect management ports. IP Subnet - 10.102.0.0/24; GW: 10.

Testing Base Model: What is the VLAN ID for the out-of-band management VLAN in the FlexPod environment? In a FlexPod environment, the VLAN ID for the out-of-band (OOB) management VLAN is typically VLAN 3968. This is a standardized VLAN ID used by Cisco and HP to manage their respective blade servers and chassis through an OOB interface.

In a FlexPod environment, this VLAN is used to provide network connectivity between the Cisco UCS server blades and the HP StorageWorks SANs for out-of-band management, monitoring, and maintenance purposes.

It's worth noting that while VLAN 3968 is a common standard, you may need to configure your own OOB VLAN ID depending on your specific environment and requirements. What is the subnet for the out-of-band management VLAN in the FlexPod environment? In a Cisco UCS Director (formerly known as Cisco Integrated Management Controller, or C-Series IMC) managed FlexPod environment, the out-of-band (OOB) management VLAN is typically 1.9.x.x.

This means that the OOB management network has an IP address range of 192.168.9.x, where x can be any value between 1 and 254. The subnet mask for this network is usually 255.255.255.0, which indicates a class C subnet with 24 bits (or 256) reserved for the network portion.

The OOB management VLAN is used to manage the Cisco UCS Director appliance and other components of the FlexPod infrastructure using a separate network that is not dependent on the data plane. This allows for secure and reliable out-of-band access to the infrastructure even if the data plane becomes unavailable.

Testing Base Model: What is the gateway for the out-of-band management VLAN in the FlexPod environment? In a FlexPod (FlexPod) environment, the gateway for the out-of-band (OOB) management VLAN is typically a dedicated IP address that is assigned to the OOB network interface card (NIC) or physical interface on the Cisco UCS Manager (UCSM) server.

The OOB network provides a separate, isolated network connection for managing and monitoring the UCS environment. This allows administrators to access and manage the infrastructure even if the main network connection is lost or becomes unavailable.

In a typical FlexPod setup, the OOB gateway is usually configured as follows:

  1. The OOB interface on the UCSM server is configured with an IP address (e.g., 192.168.100.10/24).
  2. The OOB interface is connected to a dedicated OOB network, which is isolated from the main data center networks.
  3. The OOB gateway is set as the default gateway for the OOB subnet, allowing administrators to access the UCSM server and other OOB-managed devices.

By having a separate OOB management network with its own gateway, administrators can ensure that they have a reliable way to manage and monitor their infrastructure even in the event of network or equipment failures.

Testing Base Model: What is the name for the out-of-band management VLAN in the FlexPod environment? In a FlexPod (Fujitsu, Cisco, and EMC) environment, the out-of-band (OOB) management VLAN is typically referred to as the "Management VLAN" or "Service Processing Network" (SPN). This VLAN is used for remote management of the infrastructure, such as monitoring, logging, and troubleshooting, and is isolated from the rest of the network.

Testing Base Model: What is the name of the VLAN ID 1020 in the FlexPod environment? In a FlexPod (FlexNetwork) environment, VLAN IDs are not used as-is. Instead, they are converted to a unique identifier known as a "VLAN Context" or "VC".

The VLAN Context ID for VLAN ID 1010 (not 10,20) would be calculated as follows:

  • VLAN ID: 1010
  • VLAN Context calculation: ((10 * 256) + 1) = 2577

So, in a FlexPod environment, the VLAN ID 1010 would be referred to as VLAN Context 2577.

Testing Base Model: What is the gateway address for the OOB-MGMT-VLAN According to Cisco's documentation, the default gateway address for an Out-of-Band Management VLAN (OOB-MGMT-VLAN) is typically 192.168.100.1. However, this may vary depending on your specific network configuration and requirements.

For more information, you can refer to Cisco's official documentation or consult with a network administrator who has experience configuring OOB management networks. What is the IP subnet used for the OOB-MGMT-VLAN in the FlexPod environment?? In a FlexPod (FlexPod) environment, the OOB-MGMT-VLAN (Out-of-Band Management VLAN) is typically configured to use a specific IP subnet and mask.

By default, Cisco recommends using the IP address range 192.168.1.0/24 for the OOB-MGMT-VLAN in FlexPod environments.

Here's why:

  • The out-of-band management VLAN is used for managing the storage array and other components remotely, without impacting production traffic.
  • Using a separate subnet (e.g., 192.168.1.0/24) ensures that this management traffic doesn't conflict with any other network segments or devices.
  • This specific IP address range is also easily identifiable and manageable, as it's not likely to overlap with any other networks in the environment.

Keep in mind that you can choose a different subnet if your environment requires it; however, using 192.168.1.0/24 is the recommended default for FlexPod environments. What can you tell me about out of band management on the FlexPod? Out-of-band (OOB) management is a feature in Cisco's FlexPod architecture that allows for remote, secure, and continuous management of storage and virtualization infrastructure even when the underlying fabric or virtual machines are down.

In traditional IT environments, OOB management typically involves physically accessing the equipment to perform maintenance tasks. However, with the increasing importance of uptime and availability, OOB management has become a critical feature in modern data centers.

Here's how FlexPod OOB management works:

  1. Secure Access: The OOB management console provides secure access to the storage and virtualization infrastructure using HTTPS or SSH protocols.
  2. Remote Management: IT administrators can remotely manage the infrastructure from anywhere, at any time, without having to physically access the equipment.
  3. Continuous Monitoring: FlexPod's OOB management enables continuous monitoring of the infrastructure, allowing for proactive detection and resolution of issues before they impact business operations.
  4. Automation: The OOB management console automates routine maintenance tasks, such as firmware updates and disk maintenance, reducing the administrative burden on IT staff.

Some key benefits of OOB management in FlexPod include:

  1. Improved Uptime: With OOB management, IT administrators can quickly respond to issues and perform maintenance tasks without disrupting business operations.
  2. Enhanced Security: Secure access and remote management ensure that only authorized personnel have access to the infrastructure.
  3. Reduced Downtime: Proactive monitoring and automated maintenance reduce the risk of downtime and data loss.

To achieve OOB management in FlexPod, Cisco uses a combination of technologies, including:

  1. Cisco UCS Manager: A centralized management platform for Cisco Unified Computing System (UCS) servers.
  2. Cisco Nexus 1000V: A virtual Ethernet switch that provides network isolation and management capabilities.
  3. NetApp OnTap: A storage operating system that provides OOB management capabilities for NetApp storage arrays.

In summary, FlexPod's out-of-band management feature enables secure, remote, and continuous management of storage and virtualization infrastructure, providing improved uptime, enhanced security, and reduced downtime. I am setting up out of band management on the FlexPod what is the VLAN ID? In a FlexPod (Cisco UCS Director-based) environment, when you set up out-of-band (OOB) management, you need to configure a VLAN for the OOB network.

The VLAN ID used for OOB management in a FlexPod environment is typically VLAN 3967. This VLAN is reserved by Cisco and is specifically designed for OOB management of UCS Director and other components in the data center.

When configuring OOB management on your FlexPod, you'll need to ensure that this VLAN (VLAN 3967) is configured and available on your network infrastructure. You may also need to configure the OOB network interfaces on your Cisco UCS servers and blades to use this VLAN.

Keep in mind that this VLAN ID might vary depending on your specific environment or organization's requirements. However, VLAN 3967 is the standard VLAN ID used for OOB management in most FlexPod deployments. I am setting up out of band management on the FlexPod what is the subnet? When setting up out-of-band (OOB) management for a FlexPod environment, you'll need to configure a special subnet that allows you to manage your infrastructure without disrupting normal traffic.

By default, the OOB subnet used by Cisco UCS Manager (UCSM) is 192.0.2.0/24. This subnet is reserved and should not conflict with any other subnets in your environment.

Here are some key things to know about the OOB subnet:

  1. Network Address: The default OOB subnet is 192.0.2.0/24.
  2. Subnet Mask: The subnet mask is always /24 (255.255.255.0).
  3. IP Address Range: The OOB subnet has a range of IP addresses from 192.0.2.1 to 192.0.2.254.
  4. Router: You'll need to configure a router or switch to forward traffic between the OOB subnet and your management network.

When setting up OOB management for FlexPod, make sure to:

  1. Configure the OOB subnet on your switches and routers.
  2. Ensure that the UCS Manager (UCSM) is configured with the correct OOB IP address and subnet mask.
  3. Verify that the OOB subnet is isolated from your normal production network traffic.

Remember to consult Cisco's documentation for more detailed instructions on setting up OOB management for FlexPod. I am setting up out of band management on the FlexPod what is the gateway? When setting up Out-of-Band (OOB) management on a FlexPod environment, the gateway is typically the Management Node (MNode).

The MNode is a special node in the FlexPod architecture that provides OOB management capabilities. It acts as a central hub for managing and monitoring all the other nodes in the Fabric Interconnect.

To set up OOB management, you would typically configure the MNode with an IP address and subnet mask, and then use this gateway to manage and monitor the Fabric Interconnects and storage arrays in your FlexPod environment.

Some of the key features of the MNode include:

  • Remote management: allows you to manage and monitor your fabric from a remote location
  • Event logging: provides centralized logging of events occurring within the fabric
  • Alerting: sends notifications when specific events or conditions occur

In summary, the gateway for OOB management on FlexPod is the Management Node (MNode).

Summary

This was just an early example and proof of concept that we could take VLAN information from documentation and use it to fine tune a model, locally, and privately, for free.

Model Card Authors [optional]

John Capobianco

Model Card Contact

ptcapo@gmail.com

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