NETCONF and YANG provide an improved way to manage IoT systems compared to SNMP. NETCONF allows retrieving and manipulating state and configuration data using XML over SSH. YANG defines data models for the configuration and state information. To manage an IoT device, a YANG model is defined, the device is configured to support NETCONF, and a manager can then send NETCONF commands to retrieve data and configure the device.
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THERE ARE SIX ELEMENTS OF TRANSPORT PROTOCOL NAMELY
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THERE ARE SIX ELEMENTS OF TRANSPORT PROTOCOL NAMELY
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A session in the DevNet Zone at Cisco Live, Berlin. YANG is a data modeling language defining device and service configuration and operations. This session will describe what YANG is (with examples), and its relationship to and how it is used in OpenDaylight. Several tools making it easier for the application developer to work with YANG will be discussed. It will conclude with a demonstration of YANGUI and YANG Visualizer, two new OpenDaylight applications that auto-generate a user interface and directed graph respectively, both based on selected YANG models.
» Read more at http://www.tail-f.com/education/what-is-netconf/
» Watch the Tail-f Why NETCONF video at
http://www.youtube.com/watch?v=H-BvpHd49-o&list=PLGSa_0wjZ-GgoReC1SNmgSHi2k4KUGPgo&index=1
NETCONF is a protocol defined by the IETF to "install, manipulate, and delete the configuration of network devices". NETCONF operations are realized on top of a Remote Procedure Call (RPC) layer using an XML encoding and provides a basic set of operations to edit and query configuration on a network device.
JMeter webinar - integration with InfluxDB and GrafanaRTTS
Watch this recorded webinar about real-time monitoring of application performance. See how to integrate Apache JMeter, the open-source leader in performance testing, with InfluxDB, the open-source time-series database, and Grafana, the open-source analytics and visualization application.
In this webinar, we will review the benefits of leveraging InfluxDB and Grafana when executing load tests and demonstrate how these tools are used to visualize performance metrics.
Length: 30 minutes
Session Overview
-------------------------------------------
During this webinar, we will cover the following topics while demonstrating the integrations of JMeter, InfluxDB and Grafana:
- What out-of-the-box solutions are available for real-time monitoring JMeter tests?
- What are the benefits of integrating InfluxDB and Grafana into the load testing stack?
- Which features are provided by Grafana?
- Demonstration of InfluxDB and Grafana using a practice web application
To view the webinar recording, go to:
https://www.rttsweb.com/jmeter-integration-webinar
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Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
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PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
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- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
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Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
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Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part “Essentials of Automation” series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
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Neuro-symbolic is not enough, we need neuro-*semantic*Frank van Harmelen
Neuro-symbolic (NeSy) AI is on the rise. However, simply machine learning on just any symbolic structure is not sufficient to really harvest the gains of NeSy. These will only be gained when the symbolic structures have an actual semantics. I give an operational definition of semantics as “predictable inference”.
All of this illustrated with link prediction over knowledge graphs, but the argument is general.
4. Limitations of SNMP
SNMP is stateless in nature and each SNMP request contains
all the information to process the request. The application
needs to be intelligent to manage the device.
SNMP is a connectionless protocol which uses UDP as the
transport protocol, making it unreliable as there was no
support for acknowledgement of requests.
MIBs often lack writable objects without which device
configuration is not possible using SNMP.
5. Limitations of SNMP
It is difficult to differentiate between configuration and
state data in MIBs.
Retrieving the current configuration from a device can
be difficult with SNMP.
Earlier versions of SNMP did not have strong security
features.
6. Network Operator Requirements
• Ease of use
• Distinction between configuration and state data
• Fetch configuration and state data separately
• Configuration of the network as a whole
• Configuration transactions across devices
• Configuration deltas
• Dump and restore configurations
7. • Configuration validation
• Configuration database schemas
• Comparing configurations
• Role-based access control
• Consistency of access control lists:
• Multiple configuration sets
• Support for both data-oriented & task oriented access control
8. NETCONF
• Network Configuration Protocol (NETCONF) is a
session-based network management protocol.
• NETCONF allows retrieving state data or
configuration data and manipulating configuration
data on network devices.
• NETCONF works on SSH transport protocol.
9.
10. NETCONF
Transport layer provides end-to-end connectivity and
ensure reliable delivery of messages.
NETCONF uses XML-encoded Remote Procedure
Calls (RPCs) for framing request and response
messages.
The RPC layer provides mechanism for encoding of
RPC calls and notifications.
NETCONF provides various operations to retrieve and
edit configuration data from network devices.
11. • The Content Layer consists of configuration and
state data which is XML-encoded.
• The schema of the configuration and state data is
defined in a data modeling language called YANG.
• NETCONF provides a clear separation of the
configuration and state data.
• The configuration data resides within a NETCONF
configuration datastore on the server.
12. YANG
• YANG is a data modeling language used to model
configuration and state data manipulated by the
NETCONF protocol
• YANG modules contain the definitions of the
configuration data, state data, RPC calls that can be
issued and the format of the notifications.
• YANG modules defines the data exchanged between
the NETCONF client and server.
13. • A module comprises of a number of 'leaf' nodes
which are organized into a hierarchical tree
structure.
• The 'leaf' nodes are specified using the 'leaf' or 'leaf-
list' constructs.
• Leaf nodes are organized using 'container' or 'list'
constructs.
14. • A YANG module can import definitions from other
modules.
• Constraints can be defined on the data nodes
Eg: allowed values.
• YANG can model both configuration data and state
data using the 'config' statement.
15. YANG Module Example
• This YANG module is a YANG version of the toaster MIB
• The toaster YANG module begins with the header
information followed by identity declarations which
define various bread types.
• ‘toaster’ container has the following Leaf node definition
‘toasterManufacturer’
‘toasterModelNumber’
'toasterStatus’
16. YANG Module Example
• Each leaf node definition has a type and optionally
a description and default value.
• The module has two RPC definitions
‘make-toast’ and ‘cancel-toast’
20. Management System : The operator uses a management
system to send NETCONF messages to configure the IoT
device and receives state information and notifications
from the device as NETCONF messages.
Management API : allows management application to
start NETCONF sessions.
Transaction Manager: executes all the NETCONF
transactions and ensures that ACID properties hold true
for the trasactions.
21. Rollback Manager : is responsible for generating all the
transactions necessary to rollback a current configuration to
its original state.
Data Model Manager : Keeps track of all the YANG data
models and the corresponding managed objects. Also keeps
track of the applications which provide data for each part of
a data model.
Configuration Validator : checks if the resulting
configuration after applying a transaction would be a valid
configuration.
22. Configuration Database : contains both configuration and
operational data.
Configuration API : Using the configuration API the
application on the IoT device can be read configuration data
from the configuration datastore and write opeartional data
to the opearational datastore.
Data Provider API: Applications on the IoT device can
register for callbacks for variousevents using the Data
Provider API. Through the Data Provider API, the
applications can report statistics and opeartional data.
23. Steps for IoT device Management with
NETCONF-YANG
1) Create a YANG model of the system that defines the
configuration and state data of the system.
2) Complete the YANG model with the ‘Inctool’ which
comes with Libnetconf.
3) Fill in the IoT device mangement code in the
TransAPImodule .
4) Build the callbacks C file to generate the library file.
24. 5) Load the YANG module and the TransAPImodule into
the Netopeer server using Netopeer manager tool.
6) The operator can now connect from the management
system to the Netopeer server using the Netopeer CLI.
7) Operator can issue NETCONF commands from the
Netopeer CLI. Command can be issued to change the
configuration data, get operational data or execute an RPC
on the IoT device.