In this session, dive into Siemens Energy’s journey to using digitalization to shape its next-generation smart factories. In collaboration with AWS ProServe, Siemens Energy integrated IoT edge devices across more than 80 factories into the cloud. Explore the tangible benefits of smart factories, from improved problem-solving to increased machine uptime, which can lead to cost advantages. Learn about concrete examples demonstrating the impact of data connectivity on factory operations and Siemens Energy’s dedication to sustainability.
Learn more about AWS re:Invent at https://go.aws/46iuzGv.
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– Hello, how’s everybody doing today? Great. One of my friends was giving me a hard time about having a session at 4:00 PM on Thursday, like, wedged between your trip to the airport, maybe your fourth cocktail hour of the week, something like that. What I told ’em actually is like, the people
That are here really want to be here and I’m really thankful that you came today. So with that, let’s kind of jump in. I wanted to kind of start today with a little bit of a challenge and when we talk to customers, sometimes they’ll ask us for like our quick pithy kind of,
“Hey, what’s your advice in a couple sentences.” And the thing I always tell ’em is, “Think big, start small, and scale fast.” And we’ve actually used that throughout our time at AWS to describe everything from migrations to modernization efforts to adopting new technologies. But it really drives home the idea of,
Think big, have a big vision, but pick something achievable to start with and then learn from it and scale quickly. Today what you’re gonna hear is, we’re gonna have a great customer on stage, Siemens Energy. And they did that, they took that advice and they did it.
And you’re gonna hear about that today. What I would challenge all of you today to do is think about that in your business. It’s easy to get focused on technological hurdles, everybody’s got manufacturing estates that were result of mergers and acquisitions, legacy systems, different update cycles.
But just park for a second the technological obstacles and think about what business problems you would solve if those technological hurdles weren’t there. What kind of problems would you be able to solve today if you could instantly drill down into individual machine telemetry, pull up KPIs and historical performance data, correlate them quickly,
Visualize them in a easily customizable dashboard. If you could see the inbound and outbound supply chains for your business, for your production lines and understand the cost dimensions of each of ’em to do what if scenarios and model optimal outcomes, what kind of problems could you really solve?
And if you start at that level and think about those kind of problems and then work backwards from that, you’ll start to see some really, really interesting things emerge. And that’s what we’re gonna talk to you about today. There we go. So everybody in this room has probably heard
The term “Industry 4.0” many, many times. And in a survey of manufacturing leaders who’ve done steps on this journey across the last few years, these are some of the results they tend to quote. I think these are really great from an industry perspective and I don’t disagree with them.
I think what you’ll hear today is some very specific results from our customer here and I think that’s gonna be really powerful as well. Think about things that would make a difference in your business today. What would it do if you were to reduce downtime?
Or approve OEE or better forecast your inbound supply chain? These are the kind of things that then form that working backwards model that we were just alluding to. So I’ll frame today a little bit about what you’re gonna hear. So my name’s Jeff Bramlett, I am the professional services manufacturing industry lead.
So I cover our in-house consulting arm that goes out and helps our manufacturing customers achieve their business outcomes. You’ve got Guillaume, who led the engagement with Siemens Energy for AWS Professional Services, and then Mario, who’s the customer here, is gonna come up and talk.
And what we’ll do is I’ll talk a little bit high level about what we’ve seen, kind of some industry level observations. Guillaume will come up and talk about specific customer solutions and the the problems we are trying to solve. And then Mario is gonna be the real hit of the show here
And he’s gonna get up and talk about his experience working with a AWS Professional Services and trying to solve some of these big challenges. Specifically, this is the agenda we’ll follow. You can kind of see it there, but we’ll try to save about 10 to 15 minutes for Q&A at the end.
And depending on what kind of interaction we have, we may move it off stage and do a more formal one so you can ask more detailed questions. We’ll kind of play that by ear when we see, what kind of questions we’re getting and so forth.
But really excited to have a chance to talk to you today. So Siemens Energy, who is Siemens Energy? Well, Siemens Energy is one of the world’s leading energy technology companies. You think about the impact that they have globally and I can’t think of a better stat
To share than their technology enables one sixth of global electricity consumption. Like, just think about that. Just think about the 7 billion or so people on this planet and one sixth of that flowing through Siemens Energy Technologies. They’re in 90 countries, truly global, truly global, 92,000 employees. And of note, they’re very forward
Thinking when it comes to R&D. They do make big investments in R&D and I think you’ll see that today that that engineering mindset, that willing to test and learn and experiment really comes through in our engagement and really delivered some great results. They have a comprehensive portfolio of energy solutions
And technology to enable that full pipeline and around 35% of their revenue is coming from their services business. So when you think about the power of data and being able to harness those advanced analytics that really speaks to that revenue source to them as well. When we talk to our customers
And say things like, “Think big, start small, move fast,” we also really stress the importance of top down executive vision and alignment and taking on really big aggressive goals. And Siemens energy does that. You can see that they’re based on decarbonization, they’re very, very committed to sustainability picture.
And the sustainability starts with the obvious applications of that, decarbonizing through technology, building more efficient power grids and so on and so forth. But they take that all the way down and think about how to sustain their workforce, for example. Like how do you build that workforce of the future,
Enable the right kind of diversity, enable the right kind of training and certifications and exposure to technologies to continue to modernize their workforce. They think about sustainability with partnerships like how do they build those long lasting relationships with partners, co-investing when it’s important to, and driving that future innovation, in that regard.
And then the last thing I’d hit on is profitability. I think one thing we all know is that supply chains and manufacturing businesses inside companies are not flushed with cash usually, right? Like I don’t need to tell anybody in the room that. And so one of the things that we’ve seen
With this start small application, is you can generate those results and start creating that flywheel. And that flywheel is something internal at Amazon we talk about a lot, right? The idea that you get this flywheel turning and you’re storing that energy and then at the right time you release it.
And that’s no different here, when you have a successful POC or MVP and you can show those results that then generates a vision of more free cash flow to then enable future investments and then keep going and that creates this virtuous cycle that we really try to achieve with our customer.
So it’s really thrilling to work with them on that because they have a very like-minded approach to that. So Siemens Energy is involved in the full value chain, all the way from production of equipment to downstream generation to midstream sort of distribution and energy management in that regard.
And so again, this data analytics package that we’re putting together and that we’ll talk about today is really important because it’s gonna feed that entire value chain. They really are focused on generating this low or zero emissions technology. And I’ll talk about that more here in a moment.
But it’s really key to think about the power of the technology to enable those kind of bold and audacious goals. So those goals are right here and as I said, when you have a really powerful high level vision, and your executives drive down these bold goals, it really informs that process.
So you’re thinking about this logically, you’ve come up with this really big vision, you’re starting to think about what problems you can solve and then you’ve got these goals that are sort of matriculated down the entire chain, to become climate neutral in 2030. 30% reduction in global greenhouse gas aligned
With the Paris Accord, 1.5 Celsius objectives and so on and so forth. Gender diversity. So feeding that first part of that vision or second part of that vision I talked about with the workforce of the future. Safety, obviously, big top of mind for everybody here. You’ve gotta protect that workforce.
And of course compliance, and being responsible, fiscally responsible, but also having good governance, good corporate governance and enabling that through the use of good data. So briefly I’ll talk about the journey with Siemens Energy and AWS Professional Services. So what’s really behind a lot of these workloads
That we see is actually a modern data strategy. And it’s not just about an implementation of a particular service or measuring performance and KPIs of a given set of machines or historians or PLCs. It actually starts with a bigger vision of how to think about your data strategy.
And one of the things that’s great about Siemens Energy is that AWS Professional Services has engaged across that journey with them. So we’ve been involved in things like their data platform, building a data mesh, building a data marketplace, and then all of that then enabling these use cases
Like we’re gonna talk about here today with data ingestion, Connected Factory and driving some of those line of sight to those business outcomes that we wanna talk about. So with that, I’m gonna hand it over to Guillaume to talk in a little more detail. Thank you. – Thank you, Jeff.
So thank you for giving the context of our representation today for also presenting who is Siemens Energy and showing a bit also what was their journey with us in the last few years. So first let me introduce myself. So I’m Guillaume, I’m a senior engagement manager for AWS Professional Services.
I would like to come back to the question that Jeff asked you at the start of the presentation, what problems would you solve if you had visibility across your operation? So Jeff showed you that within the industry we had different achievements which were done.
Now let’s focus a bit more on what Siemens Energy wanted to achieve with this program of Connected Factory. High level goals, increasing the operational efficiency and also improving on the sustainability front. How does this translate into some more measurable aspects that we can see and track while we are going
To be implementing this project? So first we want to reduce the unplanned machine downtime. Number two, is the number of defects that we want to reduce. And finally, reducing energy consumption will be able to help on the sustainability objective. So in order to be able to achieve that, in the journey
To achieve that, obviously there’s going to be quite a few challenges that we need to overcome. So what I’m going to explain and present in the coming slide is what kind of challenges are we going to face? How we decided to tackle them with Siemens Energy?
And then Mario will be able to show you what is the solutions that we decided to put in place and what are the main outcomes. So, in order to get these objectives, one key thing is to be able to get the data from the shop floor, so from the factories.
And in order to do that, it’s key to have a robust industrial IoT solution. And that’s where most of our presentation is focusing. So, now I’m going to ask you a bit of your participation. So, I would like to ask you the question,
What do you believe is the biggest challenge when we want to implement this industrial IoT strategy? Is it about number one, technology? Meaning do you have the right hardware, do you have the right software? Do you know how to acquire all this amount of data
And know how to make sense out of it? Number two, is it about know-how and skills? Do you have the workforce who is capable to implement these solutions, maintain these solutions or even use them? Number three, is it about security? Are you concerned about exposing your operational assets?
And finally, number four, is it about integration with the existing systems? You probably have variety of types of machines, variety of IT systems, and you are concerned on how to integrate them. So for those who think that technology is the biggest challenge, I would like
To ask you to raise your hand if you can. On know-how and skills? Okay, more hands. About security? Small group here. And about integration with existing systems? Quite a lot on that one, which is good ’cause that’s a key topic of the presentation actually. So, what we have been seeing as AWS working
With multiple customers and partners. So, I’m gonna dive deeper in a bit into four specific topics. Integration, that’s what we were talking. So I’d like you to imagine basically being on the shop floor of one of the factory and you have one old CNC machine
Which is standing there and it’s been there for 10 years and it’s has its own language, it’s own protocol to communicate. Next to it, you have the brand new welding robot that you just acquired, which is talking a completely different language, maybe providing more data but in a totally different format.
In the background, you also have all your IT systems, being SAP, being manufacturing execution system, being even your ticketing systems to raise and log alarms. So it becomes really important and and critical to get and to be able to get the source of all, to get all this data
And being able to adapt to whatever language we have with the sources of data, package them and make them usable. Number two is about scale. So let’s say that you managed to implement that in in one plant, now you need to scale it up in the multiple plants that you would have.
And for that, one key thing is to have consistent solutions deployed all around your factories. Otherwise you’re going to end up having to maintain a multitude of different solutions. So having a consistent solution is going to facilitate having a robust management strategy. Number three, is about security and compliance.
So, I remember having a lot of discussions with customers were already moving data from on-premises to the cloud is a big concern. Now you can just increase this concern because we are talking about connecting the machines on the shop floor, your operational assets to the cloud.
And now it becomes critical to have robust control in place to make sure that the security of both your data and machinery remains under control. So we must do everything that is possible to avoid that any cyber threats would impact your production flow. Finally, operation at the edge, that’s the fourth challenge
That I want to highlight today. Operations at the edge mean that you will have for example, a remote factory somewhere and there you would have one of your IT people, let’s name him John. And John is really good in being able to manage all the IT services,
But he’s probably not an IoT expert. And one thing that we need to take into account while building this solution, it’s we cannot expect John or all the other IT people in the factories to become also expert to manage the solution that we’re going to deploy. So,
That was, I would say the general view of what we’ve observed with customers and partners. Now let’s dive a bit deeper with what was the status at Siemens Energy before they started the Connected Factory program. So there was not a standard IoT solution across the multiple plants that they had.
So it was often proof of concept that were started in some plants independently. And I think as you all know, having a proof of concept doesn’t mean that you have a robust solution that can scale. So that ended up in a landscape where you have multiple IoT platforms, isolated data silos,
Which then don’t allow you to kind of get the whole insights from your data. Last but not least, in the context of Siemens Energy, they have a long history of innovation and you have a large diversity of machines on their shop floor.
So you have some machines which could be 10 to 15 years old as I was describing a bit earlier, just sitting next to very recent machines. There was some inventory which was done and at least we can consider that we have to deal with more than 10 different protocols, different languages
Of data coming from the machine to be able to have solutions which is scalable. Another quick question for the audience is that, does it sound familiar to you? Does anybody has been confronted to some of these problematics which are described here? Anyone? Okay, quite a few.
So what is the vision with Connected Factory? So number one, the goal is to have an IoT solution which is going to scale a unique IoT solution, which is going to scale across 80 plus factory, which will be able to connect more than 2,500 assets.
Security will be at the core of the solution. That means that the design will be done by first analyzing what kind of threats can come what could be the impact of these threats and the probability of occurrence? And then once we have identified them, implement the right solution
To bring these risks at an acceptable level. One thing is good to design the solution properly. What is important is also to make sure that these constraints remain in place, that we have during the life of the solution always the right security measures in place.
So it’s important to ensure that compliance is always there. Then number three, is about having a fully managed IoT solution. So I am back with John, the IT guy in the remote factory. If we have a fully managed solution which is going to be managed mostly by a central group of IT,
Then we don’t expect from this person to be able to maintain and and debug the very complicated aspects. Finally, just to show that there’s a willingness to have a solution which is going to scale in the future, it was decided to have as a standard connectivity protocol, a protocol OPC/UA.
So now I would just like to recap a bit what we’ve been discussing. By summarizing a bit, what are the requirements of the solution that Mario is going to present us afterwards? So number one, we are building a solution to connect in a fast way the machines from 80 plus plants
And this solution has to be secure. Number two, these solutions need to be able to acquire data from a lot of different sources and actually needs also to make this data available to multiple consumers. Number three, simplicity is key. We want a solution which is easy to understand and work with.
That will basically help to have this solution easily maintained and make sure that it’s going to run smoothly without having any heavy support or high costs. So now Mario is going to come on stage to present to you what is the solution that we put in place
And also show you the first achievements that were done. – Thank you very much Gil. Hello everyone. My name is Mario Pilz, I’m an industrial IoT program manager at Siemens Energy and I’m very happy to share some insights on our learnings and experiences while transforming our factories with industrial IT on AWS.
So let’s jump right into it. This is Connected Factory that was mentioned a couple of times already during the presentation. Connected Factory is our industrial IoT end-to-end solution to our internal operations. Connected Factory is connecting more than 80 factories globally and thousands of assets behind that. Connected Factory comes with managed edge onboarding
And cloud services in self-service to our internal customers. So services from the bottom to the top include a fully managed edge experience, meaning even non-IT experts are able to onboard a bare bone industry PC in just like 10 minutes to a fully connected and protected IoT edge,
Which is a game changer for us and very important to our strategy. On the cloud, we are offering managed services like data collection from the edge, data modeling and processing, and obviously real time analytics in the form of dashboards and alarms. Further northbound, we integrate with other platforms like manufacturing execution systems,
In our case the standard platform is the SAP manufacturing cloud or advanced analytics platforms on AWS for machine learning use cases. And last but not least, third-party ecosystems like Mendix, which allows our customers to build low-code tools and apps on their IoT data. So in a nutshell,
We want to do a very few things really well. That is along security out of the box, it is along self-service, it’s ease of use, it’s native interfaces, native cloud interfaces as we don’t do any own software on the front end. There’s a very important and central service
To our solution under the hood. And that service is AWS IoT SiteWise. IoT SiteWise is, as many of you probably know already, a fully managed purpose-built IoT solution on AWS and it’s doing all the heavy lifting, from getting the data from the edge, processing that data, associating that data
With asset models, which kind of is important. So think of you would define there is an asset, it has components, those have sensors, they have data types, and then you can reuse that kind of model across as many assets as you wish. And SiteWise helps with integrating real-time dashboards and alarms.
So now using SiteWise as a core service, there isn’t a lot we had to put around that, and it kind of reflects in a high level view of our infrastructure. So, two important pieces on that slide. On the left side there is a factory indicated by the box.
You can see a factory asset and an IoT edge. So think of an industry pc, an IoT edge connected to a machine, could be a robot, could be a milling machine, and it would pull data out of that machine over a certain protocol. I will come back to that later.
And it would set the data into the cloud, into the box that you can see in the middle of the slide, right into IoT SiteWise. And the way for us to do that is we are running those edges on a Ubuntu Linux. Systems manage on top of that for the management
Of the fleets of IoT devices, Greengrass Version 2 and SiteWise Edge on top of that, which is kind of the standard architecture of doing these things. So SiteWise would do all the fancy things that you just have seen on the previous slide plus,
And this is my personal favorite, it comes with a really, really well architected storage concept, out of the box. By that I mean it comes with a hot storage real-time database. So fully managed, you don’t need to do that, really performant, a bit more pricey but really, really low latency, right?
There is warm storage that was just announced ahead of re:Invent. And the one that we are using is cold storage. So all the data from that real-time database is replicated over time at a given threshold that you would define into that S3 Bucket. And if you do any changes on your assets,
It would reflect at the same time in your real-time database and your code storage…magic. I mean try to do that on your end. What I especially like is the API on SiteWise as it exposes all the data, wherever it is stored through the same API at all times. This is great.
We put Amazon Athena on top of that bucket. It helps us to pull out really large amounts of data into other tools for machine learning, BI tools and so on. There is a ton of Athena connectors out there for different ecosystems and tools. So really, really helpful.
Our primary playground for use case implementation that we also give to our end customers. And by end customer I really mean shop floor engineers, maintenance engineers, is the manage Grafana. Manage Grafana is a great tool to implement real time dashboards, put alarms of your data and use that on your tablet,
On your laptop in the shop floor. Last but not least, we make use of APIs, API gateway. It’s a great way to control the platform from the outside. It’s also a good way to read and write data through the sideways API, with other applications outside. In terms of security services mentioned before,
It’s core to our solution, we are making use of IoT Device Defender. It’s a really, really great tool, very powerful tool to detect anomalies on edge behavior. That could be local IP changes, authorization at terms or really, really unusually high message loads. So IoT Defender will detect those.
We use KMS for key management. It’s very easy. We use GuardDuty for the detection of potentially malicious code pieces in our Lamba functions. Very important. And my personal favorite, again here is AWS Security Hub. It’s a really useful service to aggregate findings across all these security services
In one consolidated view, rated by severity, low, medium, high. And it even will give you indications on how to mitigate those issues. So really, really helpful. Okay, now you have seen how we manage like one factory environment. Each of those has one AWS environment of its own account.
This is our concept of tenancy. Now we’ll show you in a little bit more detail how we bring this to a global footprint of many, many 80 plus factory accounts. And here we go. So from left to right, there’s a small but dedicated DevOps team in our company dedicated to IOT DevOps.
What they’re doing is they’re creating infrastructure code obviously in scripts, running those across our CI/CD pipelines on GitLab, which then in turn is pushing the logic and the infrastructure code into a so-called chat service account. It’s one of our AWS environments with one very important task. And that is take the logic
And distribute it through different means and technologies into any number of other factory accounts. Simple, right? And the way we do this is by using two different services. One is StackSets. StackSets is a great way to push stacks, collections of infrastructure code, cloud formation scripts into any number of other AWS environments.
And we use that for standard features, security functions, user roles, service policies and so on. So the must have for all these environments. And the other mechanism that we are using is Service Catalog. For those you who haven’t heard about it yet, it’s kind of an app store right inside your AWS console.
And the mechanism here, it’ll take the infrastructure code, will replicate it to all the other accounts globally, 80 plus accounts. But here it’ll be an optional install so the local user can decide whether he wants to install that feature like MES connectivity or a more sophisticated backup mechanism, or not.
So overall this gives us a grip on very strong governance on one side, and some kind of flexibility on the other side. Okay, so what did we do with that? Here is an overview, a really nice overview of our first five pilots factories that we have been rolling out the solution
Only six months after starting the project with AWS Proserve. And that is crazy. Six months is a very short timeframe for such a project. So for example, in our Switchgear factory in Berlin that is on the upper left side of the screen, we are monitoring the behavior of autonomous vehicles
As they carry our products through shop floor. And I talk about 5, 6, 7 tons of load on those vehicles and the local team is monitoring capacity and load charge on the batteries on those vehicles. And, as we were setting up the IoT solution, it was already collecting data from the machines
While actually the vehicles were introduced into the factory and the team was able to detect some issues with some of the batteries while the system was being set up and they could report that back to the supplier, and which had largely to claim the defects
With the supplier and keep on track timely with the project. And another example on the lower left of the screen, you can see our coating booth, or one of our coating booth in Charlotte, Northern Carolina that we have just been visiting earlier that week. It’s a way, it’s a place
Where we apply our heat to powder and spray that on metal surfaces to create a heat protective shield on gas turbine blades or transitions. And the team is monitoring the flow rate of water into the cooling process, and the temperature of the water before
And after the process, which both are pretty good indicators of the health of the process in part. In turn this helps us to reduce nonconformance costs on part and equipment, a lot. In other use cases, we deployed industrial IoT technology to robots like with the red robot in Nuremberg, Germany,
Core cutting robot or lots and lots of CNC like milling machines across for example, Sweden, Finspang Sweden, and our gas turbine factory in Berlin. This is the most common use case actually in our company with CNC. Some numbers, the first five pilot sites suggest that we can heavily decrease the amount
Of time necessary to collect data. I mean this is a no-brainer and I believe 50% is still quite conservative. The first use cases show that we can decrease maintenance efforts by 25%. And this is also kind of obvious because we spend less time on finding the root cause of the issue, right?
And can spend more time on keeping the process of the asset in a healthy state. And ultimately we can increase asset availability by up to 15%, which is huge. That has impact on our bottom line. Okay, what’s next from here? There are two very, very interesting services that are very important to us,
Especially in the shape that they are now just before or during re:Invent. The first one is Lookout for Equipment. It’s a game changer for us. Lookout for Equipment is a service AI/ML based service that does anomaly detection on IoT data. So what you do is, as per the new update
And SiteWise, you would connect sensor data right inside your IoT platform on SiteWise, feed it into lookout for equipment and it would then based on AI/ML algorithm indicate possible anomalies in the future. It would even forecast breakdowns of the asset. It would let you know which sensor values did contribute to the problem.
It’s a game changer in a way that it’s bringing AI/ML at scale. I mean still a simple AI, but at scale into all our use cases and factories. Everybody who tried or did bring ML into production, I believe knows what I’m talking about. Another very promising service to us is IoT TwinMaker.
IoT TwinMaker is the service to create digital factory twins by combining IoT data, asset dependencies, hierarchies, 3D data, and other data sources into one model. And we want to use that for root cause analysis. So if this breaks down, what could be possible root causes along our process chain?
And here’s another game changer, and this is very important to us. Very, very important. And if you haven’t seen it yet during re:Invent or before, I would like to highlight that a little bit more. So recently, Domatica and AWS partnered up to bring the Domatica Easy Edge solution onto the SiteWise platform.
What that means is, for the first time we have now access to Brownfield protocol support right inside SiteWise as a data source. Again, 10 plus protocols, which is a way to speak to shop flow assets across typical suspects like Modbus, S7, OPC UA obviously. PROFINET, PROFIBUS are now available
As a data source right in SiteWise, which is a game changer. It also comes with low code or even low code, a flow editor. You can implement logic like combining thickness from different machines into one new synthetic signal and feed that back into SiteWise as a data stream.
This is really, really powerful as a concept. Whatever you configure in terms of connectivity or logic is pushed for you directly, fully managed into your IoT edge in the background and will run there continuously. This allows us to connect more machines in less time at lower cost. Okay. Lessons learned.
So I have two slides on that. First is on working with ProServe. So working with ProServe is very agile and fast-paced. Be prepared for some very, very positive surprises. The teams are really intrinsically motivated to get things done in a very short time. They come in with a very deep technical knowledge,
Expertise, especially in the field of, also in the field of cybersecurity. We had a dedicated cybersecurity consultant in our team helping us to translate our own regulations and rules, cybersecurity rules into concrete architecture and solution. And also document the same. Very important. They’re able to start very slow,
I mean down to just one consultant without any overhead and can scale up into very large projects and teams, if you need that. And fourth, they help with, yeah, getting in touch with partners with the ecosystem around AWS. Same for service teams inside AWS.
So you can hear about, okay, what’s next on the roadmap? Can articulate your own requirements, give feature requests, participate in roadmap sessions. They help with all of that. For personal learnings from my side, so the first one is an evergreen, it never gets old, fail fast, iterate, improve.
But my advice would be, do it in a low-risk environment with a customer that you know very well already. Keep it simple. So this goes back to managed services. So try to figure out really well where you need to invest your money and your time in your own code stacks
And where can you just use a managed service available already on AWS or on the roadmap for next month, next quarter, or maybe even next year. Yeah. Try to do things that scale. Try to focus on the big picture. Don’t get lost in small details, obviously, and strong collaboration.
Talk to AWS, they listen, really. And this helps AWS to build their roadmap, to implement features that customers actually need. And it will help you to make that decision, “Okay, will I go into my own code stack or will I wait for the feature to be developed by AWS?”
If you want to learn more about Siemens Energy, and what we do for our sustainable operations internally and externally, we set up a website for you behind that QR code that you can scan with your mobile phone now. And with that, we are at the end of our presentation. Thank you very much.
We hope you enjoyed the presentation. We will be around for a couple of more minutes for any questions that you might have. Thank you.