As cloud computing continues to gain popularity, companies that are natively Windows question if they too can leverage AWS. Learn about the benefits the cloud provides, best practices of cloud computing services, and solutions available on AWS for Windows workloads. Learn how Covanta is delivering services to its users 90% faster and saving more than 60% in IT infrastructure costs after migrating its Windows workloads to the cloud.
Slide share device to iot solution – a blueprintGuy Vinograd ☁
Creating an IoT Cloud service for a connected product presents a huge challenge. Why? Because the tasks of serving millions, responding to events in near real-time, securing the solution from ambitious IoT hackers, AND generating a monthly bill that doesn't collapse the business model, resemble attempts to solve Rubik's Cube, but are far more difficult. Commercial IoT platforms are irrelevant because of the vendor-lock, so we must use basic building blocks to accomplish all this. This session will illustrate the architecture of an IoT service on top of the AWS Cloud.
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We also discuss how Earth Networks gained faster data insights using SnapLogic’s Amazon Redshift data integration and other connectors to quickly integrate, transfer and analyze data from multiple applications.
To learn more, visit: www.snaplogic.com/redshift
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VMworld 2013: VMware NSX: A Customer’s Perspective VMworld
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Jason Puig, Symantec
Richard Sillito, WestJet
Learn more about VMworld and register at http://www.vmworld.com/index.jspa?src=socmed-vmworld-slideshare
Introduction to Cloud Technology slide was prepared for Linux/Unix class lecture at Department of Computer Engineering, Chulalongkorn University in Jan 2013.
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In this webinar, you’ll learn how organizations such as Greenhouse Software harness cloud-native machine data analytics to optimize the internal and external process lifecycles, monitor the health of all AWS application and services and deliver a WOW application to their end users.
Moving applications to the cloud
Microsoft cloud services
Google cloud application
Amazon cloud services
Cloud application
Cloud based solution
Cloud Software Management
Google App engine
Microservices and Docker: Foundation for a New Generation of ApplicationsTechWell
Docker has matured and expanded from its primary use in the build/test stages into production deployments. Similarly, microservices are expanding from use mostly for greenfield web services to use in the enterprise as organizations explore ways to decompose their monolith to support faster release cycles. Anders Wallgren says that running microservices-based applications in a containerized environment makes a lot of sense—for both build and test, and from a runtime perspective in production. Docker and microservices are natural companions, forming the foundation for a new generation of applications. However, managing microservices and large-scale Docker deployments pose unique challenges for enterprise IT. Join Anders as he discusses patterns for microservices-based architectures and what makes Docker such a good fit for microservices. He explores how to operationalize Docker orchestration, autoscaling and disaster recovery in large-scale production environments, and best practices for Docker configuration and registry management to ensure consistency throughout the pipeline and stability in production. Anders offers tips and tooling for monitoring and managing clusters of containers as a single distributed application and more.
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Slide share device to iot solution – a blueprintGuy Vinograd ☁
Creating an IoT Cloud service for a connected product presents a huge challenge. Why? Because the tasks of serving millions, responding to events in near real-time, securing the solution from ambitious IoT hackers, AND generating a monthly bill that doesn't collapse the business model, resemble attempts to solve Rubik's Cube, but are far more difficult. Commercial IoT platforms are irrelevant because of the vendor-lock, so we must use basic building blocks to accomplish all this. This session will illustrate the architecture of an IoT service on top of the AWS Cloud.
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In this webinar, learn how SnapLogic and Amazon Web Services helped Earth Networks create a responsive, self-service cloud for data integration, preparation and analytics.
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VMworld 2013: VMware NSX: A Customer’s Perspective VMworld
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Jason Puig, Symantec
Richard Sillito, WestJet
Learn more about VMworld and register at http://www.vmworld.com/index.jspa?src=socmed-vmworld-slideshare
Introduction to Cloud Technology slide was prepared for Linux/Unix class lecture at Department of Computer Engineering, Chulalongkorn University in Jan 2013.
How Greenhouse Software Unlocked the Power of Machine Data Analytics with Sum...Amazon Web Services
Sumo Logic offers a powerful cloud-native analytics solution that supports all types of machine data. Our platform integrates easily with your AWS infrastructure supporting fast, accurate and secure analysis and monitoring of enormous amounts of data—giving you clear and direct visibility into its operations.
In this webinar, you’ll learn how organizations such as Greenhouse Software harness cloud-native machine data analytics to optimize the internal and external process lifecycles, monitor the health of all AWS application and services and deliver a WOW application to their end users.
Moving applications to the cloud
Microsoft cloud services
Google cloud application
Amazon cloud services
Cloud application
Cloud based solution
Cloud Software Management
Google App engine
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Docker has matured and expanded from its primary use in the build/test stages into production deployments. Similarly, microservices are expanding from use mostly for greenfield web services to use in the enterprise as organizations explore ways to decompose their monolith to support faster release cycles. Anders Wallgren says that running microservices-based applications in a containerized environment makes a lot of sense—for both build and test, and from a runtime perspective in production. Docker and microservices are natural companions, forming the foundation for a new generation of applications. However, managing microservices and large-scale Docker deployments pose unique challenges for enterprise IT. Join Anders as he discusses patterns for microservices-based architectures and what makes Docker such a good fit for microservices. He explores how to operationalize Docker orchestration, autoscaling and disaster recovery in large-scale production environments, and best practices for Docker configuration and registry management to ensure consistency throughout the pipeline and stability in production. Anders offers tips and tooling for monitoring and managing clusters of containers as a single distributed application and more.
Similar to Cloud-grilled delights a high-tech approach to perfect BBQ (20)
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Session Overview
-------------------------------------------
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Search and Society: Reimagining Information Access for Radical Futures
Cloud-grilled delights a high-tech approach to perfect BBQ
1. Cloud-grilled delights a high-
tech approach to perfect BBQ
JIMMY DAHLQVIST | Believe In Serverless 2024-05-
16
2. @jimmydahlqvist
JIMMY DAHLQVIST
Head of AWS @ Sigma Technology Cloud
Founder of serverless-handbook.com
AWS Community Builder | AWS Ambassador | User Group Leader
§
Hello, I'm
21. @jimmydahlqvist
Cloud architecture
• Reliably capture data
• Managed services
• No direct EventBridge
integration
Data service
Detection service
Notification service
Data augmentation service
IoT Core and SQS
33. @jimmydahlqvist
AWS StepFunctions workflow types
Standard workflow
• Long running - 1 year
• 2000 starts per second
• Pay per state transition
Express workflow
• Short running - 5 minutes
• 100k starts per second
• Pay for duration
39. @jimmydahlqvist
Next step
• Remove my own hardware (Inkbird IBT-6XS)
• Make it SaaS!!
• Blog posts and Open Source coming!
• Add camera support
• Train an ML model for detection
• Alexa integration
Hi! I'm Jimmy!
I have worked with AWS and severless since 2015, almost a decade now, and I have seen all kind of strange things.
I’m a true serverless enthusiast, the very first solution I built on AWS was serverless and I have not looked back since.
I have built serverless solutions for a variaty of companies, from startups to large enterpices.
I'm the founder of serverless-handbook.com where you can find all kind of serverless things that i have built, ranging from workshops to small architecture patterns.
And I have my blog on Jimmydqv.com
As a day-time job, and yes, I do have a daytime job, I know people have been questioning that.
I work as Head of AWS at Sigma Technology Cloud, we are an advanced services partner with AWS and do all kind of fun solutions.
If you like to know more about us, visit our booth outside....
I'm AWS Ambassador, AWS Community Builder and one of user Group leader for the Scania user group.
So the agenda for the day is:
Background to the project
Overview of the architecture and how it has evolved over time
Cloud deep dive and – talk about changes I made and the benefits of that
Summary – and final thoughts
Before we dive into everything, who am I?
Let’s jump into the background so we all have the same context.
What is ?
Low & Slow – Vs hot and fast I normally target ~120-125c – Reason for doing that is….. Tenderize, tissue breakdown
Styles – Us (varies by state, Texas, Tenesee, Nort caroline, New york…), Jamaica, Austrailia, UK – Sweden most US styles
Not cooking – Art! But doesn’t mean we can’t use Tech…..
Audience Poll!!
Kamado ?
UDS?
Electric ?
Offset ?
My offset smoker – Isn’t she a beuti!
How does an offset work + IoT Device – ANIMATION
IoT Device – Watch fire, help from technology, What does it do!!
This is an overview of the IoT Device and the food probes I use, standard 2.5mm thermistor probes.
What is a Thermistor?
Negative Temperature Coefficient (NTC) Thermistors
NTC thermistors exhibit a rapid decrease in resistance with an increase in temperature.
NTC is used
Positive Temperature Coefficient (PTC) Thermistors
PTC thermistors exhibit a sharp increase in resistance with an increase in temperature
Background and context done
Let’s look at the components, and architecture
Two parts – IoT device + cloud
Example services for both
CLICK!!!
Let us take a closer look at the IoT Device
Two parts – HW + SW
HW:
Rasp-Pi 4
2.5mm food probes – thermistor!
MCP3008 (10bit 8 channel)– AD converter – read voltage
SW:
AWS IoT Greengrass 2.0 – Core
Custom component – math voltage to temp
Initialy simple Python app updated over SSH
Problems – Logs and Hard to update
Done – Looked at IoT device
CLICK
Let’s talk about Cloud – where we will spend most of our time
First version of cloud looked like this…
Happy little man to the left I guess is me…
Device data -> IoT Core
IoT Core -> Rules -> Storage + Athena + Dynamo
IoT Core -> Rules -> Several SF business logic (thresholds, trends…)
API GW RESTful…
IoT rules as router –> on mqtt –> not on payload –> messages discarded in business logic
Each event –> one OBJECT in s3 –> Glue/Athena not optimized for that
Data written directly to storage (Storage First is good but…) –> Format dictated by the device –> need transform
Hard to extend –> Several services did same thing –> notification –> or needed to implement API
So I had a couple of areas that I wanted to improve.
I wanted to add the possibility to do a proper ETL and data transformation. So it would be easy to change how data is stored and presented in the cloud withour having to change the device,
Introduce a event driven architecture with EventBridge as the event router instead of relying to heavily on rules in IoT core. The rules are great but at this point they didn’t really fulfill what I wanted to accomplish.
Lastly decouple the services. Break the mini-monolith...
All changes was to create a more flexible system that was easy to extend and manage.
Let’s start by looking at the changes made for the IoT device
With the Initial problems I decided to test out Greengrass.
Interact with AWS Services – s3 config etc
AWS provided components – Log Manager
Build SW as components - Easy to push and publish new versions
AWS Lambda support
Now we move over to the cloud part what was done there
Second iteration several improvments.
IoT Core no longer primary message router -> EventBridge introduced -> EventDriven architecture -° Rules / targets / subscription
Business Logic -> Microservice pattern – with clear responsibility -> Communicating over EB and API
Transformation service -> EB Transform / augemnt
EB – PayLoad filtering
Let’s take a closer look at some parts of the architecture…..
And start with the ingress part……
CLICK! -> Animate
Favorite pattern – Storage First
Create reliable way to capture data – prevent data loss
Use managed services
Very powerful when incoming data doesn’t require instant transformation
Lambda is probably not the best solution……
The next part we should look at is the data augmentation
CLICK
This part became very important in the new design…
CLICK
….. It allowed me to decouple cloud development from device development
Data transform pattern
Data augmentation -> Additional information fetched from DynamoDB.
Data is transformed to an internal format -> Decouple from the IoT device
Almost no code. StepFunctions integration to other services
One of the most important services are the detection service
CLICK
This is where all the BBQ magic happens…..
CLICK
Threshold breach
Trends
Stall – Happens around 70c (160f). What is it?
Next part to look at is actually the entire system.
CLICK!!
Everything is built on a serverless and event-driven approach.
Reason You build an serverless and eventdriven architecture.
Loosely coupled services
Scale and fail independently
Cost effective – pay for what you use
Extensibility – easy and fast to extend
HA – built in
So have technology help me to become a better pitmaster and to get some great BBQ?
Some may say it’s cheating but why not use tech to help?
…. I let the result speak for it self!
EventBridge Choreographs
Four bounded contexts represented by each service (orchestrated)
Stepfunctions
The service has unique business logic that need to be implemented and happen in a certain order, when a event is invoked.
StepFunctions Express Workflow has an invocation model of “At least once” which means that it’s possible that your workflow get invoked twice.
In dev and test it’s unlikely that it will happen, even in my small project I never saw it. But if you run it in a large enough scale it will happen.
So make sure your workload is idempotent and can handle it.
This makes them ideal for orchestrating idempotent actions such as transforming input data and storing via PUT in Amazon DynamoDB.
When building on eventbridge I would recommend that you create subscriptions.
With that I mean that you create one event rule for one target. Even if EB support up to 5 targets per rule I still say this should be a 1-2-1 mapping.
Why?
If you create one rule with multiple targets you will create a coupling on the event filter. And if you hit the 5 target limit what are you suppose to do then? Create a second rule with the same filter and start adding new targets?
What if you need to update the filter? You will impact several targets that might not be what you wanted to do in the first place, leaving you to start breaking things apart again.
So instead we create subscriptions where we create the coupling on the event it self, and we set one target for one rule.
It’s easy to add more target, just create a second rule and add the target to it. And the filter in every rule can change without affecting any other target.
However…. This of course can lead to several rules having the same filter and that could create problems on it’s own.
But in my opinion it’s still better to create subscriptions and deal with a rule explosion.
there is a default EB bus in the region already existing that AWS services post events to.
Should you use that as your bus in your application? My recommendation is NO. Leave that bus to be used by AWS services and create your own custom buses for you application.
The reason for that is that in that case will become easier to extend and ass busses later. I have seen the default bus being used and the mess it was when then moving to a custom bus.
So can’t repeat it enough… Leave the default bus alone! Create custom buses! It’s like using the default VPC…. We don’t do that either!
So instead of using SQS + Lambda to transport.
It would be possible to have IoT Core invoke a Express StepFunction with only one step which would be a SDK integration and that integration would just post the event to EB.
No code, only 100% managed AWS services doing all of the work for me behind the scene. That is a really nice way to be able to use the SDK integration in StepFunctions.
This wcould however break my storage first approach, but since there is no code involved, just AWS calling the SDK on my behalf I could totally live with that.
It truly show the power and flexibility in a serverless approach and a service like AWS StepFunctions.
So what is next in this project then?
So to summarize the last 40 minutes.
Building an IoT system
Serverless and event-driven
Get great BBQ with help of technology
And with that I say!
CLICK!!