Different Data types i.e YAML,XML,JSON has been already discussed in below blogs :
JSON : https://knowpackets.com/2020/03/11/json/
XML: https://knowpackets.com/2020/02/28/xml/
YAML: https://knowpackets.com/2020/02/26/yaml/
Here you will find the comparison between all the three mentioned data types in one page:
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JSON(Java Script Object Notification) is another data type apart from XML and YAML ,It’s easy for human and machine to understand than XML.
As usual, lets start with json example:
anurudh@anurudh:~/newfolder$ cat ex1_js.json
{
"hostname": "Router1",
"vendor": "cisco",
"users": {
"admin": 15,
"storage": 10
},
"vlans": [
{
"vlan_name": "VLAN10",
"vlan_id": 10
},
{
"vlan_name": "VLAN20",
"vlan_id": 20
}
]
}
We like to put few point :
Working with JSON in Python
anurudh@anurudh:~/newfolder$ cat ex1_js.py
# Module need to be imported to use json
import json
# File is open and stored in varible dat
with open("ex1_js.json") as f:
data = f.read()
# json.loads places json data into json_out (dictionary)
json_out = json.loads(data)
# print output
print(json_out)
# Lets check the data type 'json_out'
print("The Json document loaded as type {0}\n".format(type(json_out)))
# Method json.dumps will convert python object back json string
json_out1 = json.dumps(json_out)
#print output
print(json_out1)
# Lets check the data type 'json_out1'
print("The Json document loaded as type {0}\n".format(type(json_out1)))
anurudh@anurudh:~/newfolder$ OUTPUT
anurudh@anurudh:~/newfolder$ python3 ex1_js.py
{'hostname': 'Router1', Continue reading
There is a law in the United States that consists of twenty-six words: “No provider or user of an interactive computer service shall be treated as the publisher or speaker of any information provided by another information content provider.” Otherwise known as Section 230 of the Communications Decency Act (CDA), it has been characterized as the law that “created the Internet.”
Only part of this statement is true. Section 230 did not actually create the Internet because the Internet was created through the collaboration of a diverse set of people around the world. What is true, however, is that the intermediary liability regime has undergirded the Internet as we know it. It has been responsible for three primary features of the Internet:
Kubernetes is making a lot of noise in the infrastructure world. Day Two Cloud co-host Ethan Banks spent three days taking a deep-dive course on the orchestration platform, and on today's show aims to provide Kubernetes fundamentals as they apply to your infrastructure.
The post Day Two Cloud 039: Kubernetes Fundamentals For Infrastructure appeared first on Packet Pushers.
In this inaugural episode of Network to Code on Network Collective, Jeremy Stretch, John Anderson, Rick Sherman, and Jordan Martin meet up around the virtual roundtable to discuss what a source of truth is, how it can play a critical role in your network automation efforts, and how the open source project Netbox might fill that role in your network.
Outro Music:
Danger Storm Kevin MacLeod (incompetech.com)
Licensed under Creative Commons: By Attribution 3.0 License
http://creativecommons.org/licenses/by/3.0/
The post NtC – Source Of Truth appeared first on Network Collective.
Cloudflare Access, part of Cloudflare for Teams, replaces legacy corporate VPNs with Cloudflare’s global network. Using your existing identity provider, Access enables your end users to login from anywhere — without a clunky agent or traffic backhaul through a centralized appliance or VPN.
Today, we are open sourcing a plugin that continues to improve that experience by making it easier for teams to use Cloudflare Access with one of the software industry’s most popular engineering tools, Sentry.
Sentry is an application that helps software teams find and diagnose errors in their products. We use Sentry here at Cloudflare. When you encounter an error when using a Cloudflare product, like our dashboard, we log that event. We then use Sentry to determine what went wrong.
Sentry can categorize and roll up errors, making it easy to identify new problems before investigating them with the tool’s event logging. Engineering managers here can use the dashboards to monitor the health of a new release. Product managers often use those reports as part of prioritizing what to fix next. Engineers on our team can dig into the individual errors as they release a fix.
Sentry is available in two forms: Continue reading
An open videoconference to be nice to each other, blow the Corona blues away.
The post Invitation: Packet Pushers Virtual Happy Hour – March 2020 appeared first on EtherealMind.
Another interesting question I got from an ipSpace.net subscriber:
Assuming we can simplify the physical network when using overlay virtual network solutions like VMware NSX, do we really need datacenter switches (example: Cisco Nexus instead of Catalyst product line) to implement the underlay?
Let’s recap what we really need to run VMware NSX:
Another interesting question I got from an ipSpace.net subscriber:
Assuming we can simplify the physical network when using overlay virtual network solutions like VMware NSX, do we really need datacenter switches (example: Cisco Nexus instead of Catalyst product line) to implement the underlay?
Let’s recap what we really need to run VMware NSX:
Read more ...Characterizing, modeling, and benchmarking RocksDB key-value workloads at Facebook, Cao et al., FAST’20
You get good at what you practice. Or in the case of key-value stores, what you benchmark. So if you want to design a system that will offer good real-world performance, it’s really useful to have benchmarks that accurately represent real-world workloads. In this paper, Facebook analyse three of their real-world RocksDB workloads and find (surprise!) that they all look quite different. More interesting, is that there are important differences between the way these real-world workloads behave, and workloads generated by the venerable YCSB benchmark.
Therefore, using the benchmarking results of YCSB as guidance for production might cause some misleading results… To address this issue, we propose a key-range based modelling and develop a benchmark that can better emulate the workloads of real-world key-value stores. This benchmark can synthetically generate more precise key-value queries that represent the reads and writes of key-value stores to the underlying storage system.
The tracing, replay, and analysis tools developed for this work are released in open source as part of the latest RocksDB release, and the new benchmark is now part of the db_bench benchmarking tool.
TL;DR Continue reading
I recently used AWS DataSync as part of a lab I was building. These are my notes for using DataSync to replicate an Amazon Elastic File System (EFS) share from one region to another.
AWS DataSync is a managed service that enables replication of data between AWS services and from on-prem to AWS. It automates the scheduling of transfer activities, validates copied data, and uses a purpose-built network protocol and multi-threaded architecture to achieve very high efficiency on the wire.
The use case I needed to tackle was replicating an Amazon EFS share in one region to an EFS share in a different region (a one-way replication). (DataSync can also connect to Amazon S3 and Amazon FSx for Windows File Server)
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Tuning The FPGA For Clouds And Comms was written by Timothy Prickett Morgan at The Next Platform.