Hello, my name is Community. I'm working as a senior manager at Micro Technologies. I'm a leading, I'm leading team of student developers who support enterprise applications such as Team Center, rapid Response and building RPA tools, using UiPath, robotic process automations, and our team also. Includes dashboard development using Power BI and Tableau. Today I'm going to discuss about how, why, how, and why we should build scalable platforms for developers in general. Engineering teams spent around like 40% of their time on the infrastructure tasks, especially for deployments. 60% of this time can be reduced using integrated development platform engineering tools and IDPs also helps us to increase our delivery rate by three times. So typical key challenges in platform engineering. Looks like they have disconnected tools with inefficiencies and lot of repetitive. Manual tasks, and we always need to upgrade our skillset because this requests special knowledge and lack of standardization also causes quality issues and knowledge gaps for any tool. We always have resistance to adapt especially for new platforms and workflows. It's always difficult to scale the teams, especially when we have multi-skilled teams. In addition to that, there are overbearing issues with respect to complexity of softwares, especially when we are using microservice architectures and multi clouds deployments. So today every company is using multiple clouds, including AWS. Azure or any kind of leading cloud deployment and complex dependency management distributor system challenges. These are all related to all the complexity of softwares. In addition to that, developers has lot of issues with respect to inconsistent workflows, a lot of infrastructure dependencies. Standardization problems, all these things leading to cognitive overheads. So this sentence reduces the productivity and increases the time to market. So platform engineering integrated platform engineering solves these problems. All the challenges by creating internal development platforms, we call it as I, dps. So always focuses on the developers. They, we want to give some time back to developers. So developers, we need to think about fitting them in the driver's seat wherever it is possible. These IDPs helps us to automate manual tasks, which can reduce tasks and it all these IDPs comes with clear APIs and interfaces. They have, they also comes with lot of services and workflows, prebuilt services and workflows. Because IDP is also platform engineering. Tools also comes with lot of metrics where we can use the metrics to adapt, increase the efficiency, and also in term like we can increase the developer development satisfaction. So core components in the platform engineering starts with self-service infrastructure. It's a key component for IDPs, which will help to reduce the wait time, remove the bottlenecks, they'll improve the teams, empower the teams, and reduce the deployment complexities by 60% or more. So integrated toolkit is a core component which has key components such as version control, security scanning, performance testing, compliance checks and deployment automations. They helps in increasing the productivity and develop developer components like I mentioned earlier. Observability and monitoring frameworks. This is a key factor for platform engineering, which comes with logging metrics, traces, and also some of the advanced capabilities like how to detect the anomalies, interactive visualization and proactive alerting with automation. So here are the best industry, best platform engineering tools like, like I mentioned earlier, each component has its own flavors. So self-service infrastructure, Kubernetes, Terraform, omi, cross plan. These are the tools widely used for CICD, Argo C Teton, GitHub actions, Jenkins X. These are the tools managers for CICD, for observability, especially for metrics, parameters, Grafana, open Telemetry, Datadog, other tools for incident and service management. Backstage, human tech query are the tools. And finally, for security, we can use vault OPA and sync. So what are the strategies we should use for implementing? So for develop, for developers centric, we need to follow the best practices, a PA design following the A PA design principles and command line tools for automations. So establishing metrics, this is a key 'cause we need to monitor active users and deployments time and how much platform usage. In addition to that, we should monitor productivity metrics and satisfaction metrics. So another strategy is. Creating feedback loops. So we should be analyzing the, collecting the data usage data errors, performance metrics, gather the feedback, analyze the patterns, and identify the improvements, and we should communicate the plan to gain the confidence. Finally, we need to deliver the improvements based on the constant feedback. So this is a cycle we need to continue. To evolve in the platform engineering implementations. So now I'm going to explain about few success stories. The first story is about e-commerce change. The biggest challenge they faced up is like how to scale up the team. So they build the platform in engineering tool by building the platform, focusing on provisioning standard development environment. Integrated CICD pipeline automation and centralized observator observability metrics. So this helped this e-commerce chain. They increased the feature velocity by three times and they reduced the production bug by 75% and they have fewer deployment failures and that improved 60% of their deployment failures. Pure deployment failures. Of course, it comes up with the developer satisfaction. The next success story is financial services firm. So they struggle with operational overheads, manual security reviews, audit trials, and change management processes. They create a lot of bottlenecks and they delayed the future religious by month. So that's a good challenge they have. So they developed the platform by embedding complaints, enabling automated security and policy as a code implementation. They adapted and self-service provisioning, which helped them to available on demand. Finally, the register overhead by 50% and improved the time to market. And less security incidents. The third success story is with the technology startup by enabling golden parts in the ideas and by automating onboarding and technology flexibility. The startup company scaled from 10 to hundred users, and this is achieved by investing in the platform engineering early in the. Growth journey. Okay. Lot of times we have the confusion about platform engineering, DevOps, and software relat engineering. So here are the key differences. Platform engineering main goal is to build internet development platforms to make it consistent. Whereas DevOps focuses on the bridging the gap between development and operations. Software Reliability engineering focuses on the reliability of the software. And there are different tools in the market and different metrics for each section. So like I outlined here, like platform engineering focuses on the productivity and adoption, whereas SRE focuses on uptime and latency, and DevOps focuses on MTTR and deploy frequencies. So these DI disciplines. Often overlap, but they have distant focus. Okay. What is the future of how is how this platform engineering is going to evolve in future? The biggest challenge currently is how can we how can we work on the multi-cloud environments? So basically enabling workload portability between the cloud providers. If we can achieve that is the biggest success. I think things are going in that direction. The next biggest thing is lot of Gene and a agent DK Innovations. They helps this platform engineering in big way, cell LMS for code generation, intelligent automation, robotic process automation, predictive analysis. So that looks promising for future innovation. And finally. These tools should move beyond reactive operations to proactive capacity planning. So that way we can sustainably impact, we can do, make sustainable impact on the platform operations. Okay? How do we build platform engineering? And what are the strategies we should be using? First and foremost, we need to have clear vision of the future and understand the problem statement. Always start with a narrow scope, then we can scale it up and focus on building the team with unique skillset by using the observability metrics, constantly measure the success and evolve continuously and keep on getting feedback from developers to innovate the key, key takeaways. From the platform engineering perspective is it's no. It is complexity of today's software ecosystem. It is demanding the need of platform engineering. Successful platforms prioritize on the developer needs. They establish clear metrics for adoption and increase the productivity. As I mentioned earlier. Always start with narrow scope and scale it. Finally, platform engineering is not an optional anymore. It is a foundation for software excellence given the direction of future citizen development and lot of, non code environments. Thank you.