Self-service MQTT latency testing

We have created a SaaS lab at https://mqttlab.iotsim.io/mqttlatency to test real-time round-trip latency to/from your internet-accessible MQTT broker.

This 4-minute Youtube video shows how easy it is by measuring latency for 3 publically accessible MQTT brokers. To add your own would be a minute more.

Self-service online MQTT Lab up to 10,000 sensors available on AWS Marketplace

We have recently added a 10k size for our online, self-service MQTT
labs on the AWS Marketplace, designed for development, testing,
proof-of-concept, training of large IoT applications. The affordable
prices are

Lab                                                   Hourly       Annual

MIMIC MQTT Lab - 10 sensors         $0.10        $ 300.00

MIMIC MQTT Lab - 100 sensors       $0.30        $ 600.00

MIMIC MQTT Lab - 1000 sensors     $0.90        $2000.00

MIMIC MQTT Lab - 10000 sensors   $1.80        $4000.00

(all + AWS usage fees)

For details check

https://aws.amazon.com/marketplace/seller-profile?id=b654d165-74ca-4af3-b597-07b3cf484b91

and

https://mqttlab.iotsim.io/

For custom pricing (size, duration) contact us.

Here is a 2-minute video of 1000 sensors publishing to the EMQX broker
running in a separate EC2 instance:

https://www.youtube.com/watch?v=JUu6nvW6pcE

insight.tech: Avoid IoT Project Failure with Better Simulators

MIMIC IoT Simulator is featured in this Intel insight.tech article

"Proper network simulation is essential to a successful scale-up.
...
Rather than attempting to simulate physical hardware, Gambit simulates
the traffic that IoT devices generate when they communicate across
the network.
...
When end users can model their network and sensors, they can determine
resource requirements before deploying a single device.  "

Check out MIMIC IoT Simulator on the Intel Marketplace to
get your IoT Simulation on the right track.

MIMIC Simulator: Simulated heterogeneous network

When you want to test your network management application
customizations, nothing beats running against your production network.
But, when you cannot impact your production environment with your
experimentation, you need to run in a lab, with a facsimile of your network.

In that case, an SNMP Simulator like MIMIC Simulator allows you to record

parts of your network to simulate in your lab. Once everything works in the

lab, you can deploy changes on your production network.

For capacity planning or training, you might need sample networks that
represent features that you currently have not deployed, and are planning
to implement. In that case, a MIMIC SNMP Simulator can simulate the
network you need.

Figure 1 - Auvik

MIMIC ships with various sample networks, including this heterogeneous
network which represents a current, multi-vendor, multi-function, multi-site
environment containing many features to be managed.

The network has two interconnected sites of 25 devices in total, namely,
New York City and London. This network has a variety of devices from
different vendors. It contains Routers, Switches, Firewalls, Storage devices,
Wireless Controllers, Wireless Access Points, Phones, Printers and Windows
Servers from vendors Cisco, Juniper, Fortigate, PaloAlto, Aruba, NetApp, HP,
Avaya and Microsoft.

In our lab, the topology is mapped by various common NMS applications,
such as Auvik, Entuity, OpenNMS, Spectrum, etc.

Figure 2 - Entuity

New York has 13 devices starting with Cisco ASR-9000 as Edge router with
2 Firewalls connected to core router Cisco ASR-1000 that connects to the
inside network. London has 12 devices starting with Juniper MX960 as
Edge router with one Firewall connected to core router Juniper T4000 that
connects to the inside network.

Figure 3 - OpenNMS

This network can be customized with all other advanced MIMIC features,
such as

• random interface statistics,
• CPU/memory statistics,
• SNMP link/down for root cause analysis,
• CBQOS,
• IPSLA,
• IOS configuration management
• NetFlow
• Topology Wizard

For example, this network was augmented to 1000 agents:

Figure 4 - Augmented network

MIMIC Simulator accelerates testing and training by providing relevant, 

customizable, scalable, dynamic, reproducible network scenarios in your

lab.

Figure 5 - OpsRamp

WebNMS Simulation Toolkit: End of Life

WebNMS has announced end-of-life for the WebNMS Simulation Toolkit as
detailed on their site as of December 31, 2019.

For customers requiring the latest features of an SNMP simulator we offer half off
on an upgrade to the latest version of MIMIC Simulator (ie. 50% discount)
until March 31, 2020.

Take advantage of a first-class simulation environment geared towards large-scale,
custom, rapid development, testing, prototyping, demonstration of network management
applications. For more details, see the videos on our Youtube channel or contact us at
sales@gambitcomm.com .

MIMIC MQTT Simulator integrates with Alibaba IoT Platform

We have added MIMIC MQTT Simulator integration with the
Alibaba IoT Platform for getting started, evaluation, development,
testing and proof-of-concept on this platform.

Here a simulated sensor is updating its device shadow:

Dynamic, real-time, predictable testing of Amazon Greengrass

Efficient testing of Amazon IoT Greengrass with lots of devices is difficult to
achieve, unless you use simulation techniques as everywhere else in
engineering.

We setup a lab of 100 simulated sensors in MIMIC MQTT Simulator
publishing telemetry in real-time to one instance of Greengrass, simulating
an IoT edge scenario where telemetry is processed at the edge, without
needing to go to the cloud. Most of the telemetry is uninteresting, unless an
anomaly occurs, such as a temperature value above a certain threshold.

In this 2-minute Youtube video 10 of those sensors are started, and monitored
by a subscriber application based on NODE-RED. You can see how it
tracks the temperature and light values of the sensors. We dynamically
and predictably create the anomaly in a matter of seconds.

Then we expanded the number of active sensors to 100, but the NODE-RED
application would not easily show the number of sensors on the graph
(even 10 cannot be definitively shown, and 100 hung the app).

So, we wrote a small Python MQTT subscriber client, which monitors each
sensor reported at the Greengrass local shadow, and displays the number
of sensors detected, and whether any of them exceeds the arbitrary
threshold (our anomaly).

This 2-minute Youtube video shows the interesting parts of the setup,
and the successful completion of the test.

When testing with Greengrass, make sure to use MQTT simulation to
verify your application.