Hi, this is Baskar America. today our topic is, revolutionizing telecom BS with go. So in this presentation, we will explore how go based solution have enabled the telecom companies to handle them millions of transaction while achieving the significant cost saving and performance improvement. Join us, as we shared that practical insight and real world implementation for the, engineering team looking into the build a next generation telecom, infras. So what are the DSS. BSS is I better been a support system in telecom, industries. it's a kind of pyramid architecture like, network layer and VSS layer on top of BSS layer on top of, customer experience layer kind of thing. telecom industries, they have a. Which we have to translating to the digital, using the GO programming and apply the microservice architecture and in data cloud. the digital BSS market, landscapes, so 8.9 billion, projected, global digital BSS market value markets size back, 2026. So they're expecting, almost, $9 billion, in 2026. The compound annual growth rate is almost 18%, 70.8%, and cost is 75%, and 40% is operational production. So telecommunication BSS market is experience. A rapid growth has provided, transition from the legacy system to a digital solution. This c is, driven by the increasing customer, demand for the real time services. The need for operation efficiency and, competition, competition from the digital need to company entering the space that go programming is emerged as a key enabler in this, transformation offering the performance benefit that translates that directly to the business value through the, through reduce their development cost and the operational savings. So when we are applying the, transformation from the legacy application to the digital, so it's almost a percent cost sale and 40% operational traditions. why go, for the telecom bss. So go programming language, having a special features. using these features we can, efficiently develop the, transformation from, legacy application to the, digital. So high performance, concurrency model and a memory efficiency cross platform supports. concurrency model means, go, go routine for the efficient processing. and memory efficiency to go programming, having, language, having a special, garbage collection, features and class platform support means it's compiled once and put anywhere. So go doesn't philosophy aligns there perfectly with the telecom BSS requirement. It's, compiled the natural delivery and performance needed for the high volume transaction processing while maintaining the developer productivity through the clean accessible syntax. The language is built in the concurrency model with the go routine, and the channel provided a solution for the handling them. Millions of simultaneous connections, a common scenario in the telecom enrollment. Additionally, gross memory management and garbage collection minimize the resource utilization and making it a. But always on systems. So that is what earlier, we discussed go programming language, having a special features like a congruency model. It has to, handling the, parallel process, concurrency programming kind things. and, special garbage collections. so I, because of that, utilizing the resources, very minimal. So when we are supposed to using the any resources, once that, task is done, that resources immediately are released. So that's part microservice architecture in the tele. Service independence. Each business function operates as a standalone service with, with it one data store and the AP interface. This independence allows the team to develop and apply the scales, services without affecting other components. So service, independence. when we are, talking about translating application to. we have to, I mean that, BSS enterprise applications, we have to divide into the multiple services. So each services, it has a own data source and, multiple a PA calls or multiple a p interfaces. because of that, it is very easy to develop that services and it applied individually and, development activity is very ly happening, so multiple services we have to. And the resilience and, for, to isolation, failures in one service, don't catch cutting into the system. in the, in BSS side, we have a. Multiple services, I suppose any services, is down so it do not cascade through the system. So we can apply some patterns like, circuit, brake cards or time mode, and mechanism ensure that viral system remains operationally even when individual component fails. At the same time, target scaling resources can be allocated precisely where needed. High demand services like a building or customer management can scale independently during the peak period without, our project. Yeah, that's absolutely. So we no need to enter system to scale up something like that. So what are the service, on demand? That particular service only we have to scale up actually. So that is a targeted scaling. So the transac, transition from the monolithic, VSS to the microservices has been, transformative to, for the telecom approach, this architectural approach, based on the complex systems into the manageable, manageable and specialized services that communicating through the well defined a PS. Go small memory, footprint and fast. start, time. Make it, practically well suited for the microservice implementation. Enable that rapid scaling in response to change the demand pattern. performance metrics and benchmarks. So our real world implementation of core base BSO solution have demonstrated signal performance improvement, legacy systems. Our benchmark shows that, go implementation, consistently. our performance previous, generations of telecom software across the critical metrics, they able to handle the 2.5 million transaction per, our, representative of four times of implement our legacy systems. While then 99.99% uptime translate into just a minute of. A critical requirement with telecom operation where service interruption to directly impact the revenue and the customer satisfaction. So using this, transformation, so it has to improve the performances. almost 2.5 million, transaction per hour. At the same time, using this, transformations, our downtime means very minimal per year. So almost 1e-05% of downtime per year. so almost your system is available, 99.999%. yeah, that's the, here. So security implementation. whenever, we have a services, when we are developing that, go language with microservices and enterprise B BSS applications. So each services have a multiple, a Ps and those a Ps communicating internal a, internal a Ps or external a Ps or third party, a Ps. Like that. So in these cases, we have to, provide the security for the a PA calls. So we have to use the authentication and author mechanism, implement the s to, and, implementing the J token with, GO crypto package or identity management across the microservice. And data production. Data production is most crucial thing. So that's the reason we have to apply the encryption, A ESO 2 56 algorithms. the data encryption where we need, actually, we have a very, since two customer data at the same time, financial transaction data. we need to provide that data protection and correction at the, the rest and in transit using the AS 2 56 with the customer. Go. Implementation optimization for telecom workloads, threat monetary, a real time security event processing with the go forward analysis in general for the pattern detection. Complaints adherent ITU, eight by 8 0 5 standard throughout, automated security control on the audit capability. So security is a paramount in a telecom bss. Which handled us to customer data and financial transactions. Our goal base security implementation, leverage the languages performance to process the security even at the unprecedented scale while maintaining the comprehensive protection. Go Standard Library provides a robust, cryptographic tool that we have extended, with the telecom specific security modules aligned with the in state standard like itt, GT TX, 8 0 5, ensuring the both regulatory and competence protection evolving threats. So in, in this, security implementation, so we have to provide the APAs security at the same time, we have to provide that at the protections. DevOps integration. DevOps integration is the most, crucial part, while translating from legacy application to the, digital. DevOps, integration. It's, providing a very fast development. So continuous integration, automated build, quality assurance, deployment, and monitor. So continuous integration is the, about automated testing with the ghost building there, testing framework. Automated, build across, compilation for multiple deployment, targets and the quality assurance of static analysis and security scanning, deployment blue gate deployment with the CAN testing, monitoring realtime metrics and distributor, tracing. In this, DevOps integration. that develop, develop the code and they, we have automated, execution of journey integration test after that, Build up, code actually. And that, that, once that build is happened, then we have to deploy our services, into the, cloud networks, actually cloud platforms. At the same time, we have to, check the quality assurance like, sonar, sonar quality checks actually, once we applied and services running in the production. we have to monitor the services, whether the services is, down or up and, the particular services, how much, CPU time, and how much memory it is, occupied. These things also, we can monitoring actually, so using that DevOps integration, each and every services. We can monitor it and how much, CPU and memory it is occupied actually, that we can monitoring it and the entire, deployment and build and deployment process, we can automate it actually. So DevOps practices are essential for realizing the full potential of go in the telecom environments. Our integrated pipeline enable us to deploy the changes to production multiple times per day with the confidence dynamically reduce the time to market for a new future. So when we are developing any new feature, it's very less time we can deliver those things actually, and goes to compilation speed and, comprehensive testing capability make it, particularly well suited for CICD workflows. The ability to quickly build test the plan changes has, transformed how telecom BSS evolves enabling a continuous improvement rather than the, Infrequent high risk upgrades. overall, DevOps integration is the most crucial part in the translating from the legacy application to the, digital. cloud data deployment, so containerization, orchestration, multi-cloud strategy, and the service mass. So cloud network deployment model enables, telecom b to achieve the elastic scaling and the graphical distributions goes. Minimal random dependency and the small boundary size make it ideal for the environments with typically microservice required for, request. 1520 MB for container space. So whenever we go with, when we are using the GO programming language, the, what are the dependencies? It is very, 15 to 20 MB only for container space occupation. And this container radiation is, one of the. Crucial part. And, it is called as a docker containerization. And, that container, we have to convert as a docker, images, that images we can, apply into the, higher involvement. because of that, we have to award the. enrollment basis, discrepancies, any issues, enrollment, lower enrollment, having, lot of issues one enrollment or another when we are moving to our code. So it has a lot of, discrepancies. So to avoid those things, we can use the docker container variations. So yeah, our cloud native approaches has enabling to us to the 300% improvement in scalability with the system automatically expanding and contracting based on demand patterns. This elasticity is, particularly valuable for the telecom operators are dealing with, unpredictable traffic spike during the network, events or marketing promotions. Okay. So yeah, this cloud NATO deployment, mostly, we are using the docker containerization, open source tools and frameworks. using this open source tools and frameworks, so it's obviously, reduce our cost. It's a open source, so using that open source tool to start developing your activity. So you have to spend the only development activity. There is no license cost for the, or, tools or, so it is available on open source. Okay? we have to, use those things and we can develop the, our entire transformation from the legacy application to digital. And, we can, implement our, BSS application. Actually, okay. Data access and storages, go, for our capabilities, cockroach for their distributor desk. cockroach distributed means cockroach, DB is nothing but the NoSQL kind of things. Ready for caching with, go ready client. these tools provide the foundation for that data per, persistency with the performance characteristics required by the telecom workloads. So a PA development, again, an E ECHO framework for the, high performance, rest, P-A-G-R-P-C for the internal service communication and open a PA for the documentation. Our a PA handling, millions of requests with, sub millisecond latency. Observability, premises for the metric, collections for the distributor. Tracing and grafana for visualization. Complete observability has reduced the MTTR from, hours, two minutes for the, production issues. Project structure, go module for the dependency management and, project organization Following, domain, domain driven, design principles, consistent structure, has improved the developer onboarding time base system, the go ecosystem year rich collection of open source tools, that, accelerate the BSS development. we have leveraged these tools to create the modular maintainable and co maintainable code basis that reduce the service time by 50% improving. So to, using this open source tools and framework. So they're telling that we are leveraging these tools to create the modular maintainability, code basis that reduce the service ing 10 by 50%. Absolutely. So using these tools, we can, protein 10, 50%. A real time data process. So yeah, real time data process, nothing but Kafka streaming with, go consumer processing and enrichment. go powered streaming Processor analysis is ML model with a go, inference engines. Action, automat response on three A ps. real time data processing forms the backbone of the modern telecom bss, enabling the intermediate insights and actions. Our go base, stream processing pipeline, handle the millions of events, but second. From network performance metrics to customer interaction, all process with, minimal latency, these capabilities as, transformed how telecom operators will respond to the customer needs with the EA driven system, reduce the. Shown by the 45 person through proactive inter interventions, the net promoter score improvement of 25 points, demonstrate that the impact of the, technical capabilities as customer experience of more respons and this realtime data processing, we obviously use that Kafka. It's millions of transactions. So we have local transaction mechanisms there. We have to apply this, kafa. It's nothing but a event driven architectures. In the event driven architectures. Obviously each event triggering. And based on that, what transactions we have to roll back. What are the transactions, rollbacks or tasks or rollbacks that we can using, the Kafka streaming section. This is a real time processing data processing. So implementing your go power BSS transformation, start with the clear business objectives. when we are, implementing your go power BSS transformation, so we have a clear business objective and defining services properly. And each services, defining multiple, aaps and, those a Ps, with, using the, securities and, that also more protect and modular transformation. Begin with the bound context that offer the high business value, but moderate risk. gradually expand your go, footprints. Build, build a Go expertise, investing in training and, pair programming to build a solid foundation of Go kill with your engineering team. Yeah, this is obviously so better to do with, pair programming, learn the go programming language, and understand the key features, of the go language and, Whenever we develop any services, we have to apply these, go features and especially, there is a parallel processing. so this go parallel processing is very, effectively, and, provide the more performances, measure and optimizing, establish the performance, baselines and, continuously optimize, based on your real world telemetry and user feedback. As we conclude, remember that successful BSS transformations technical excellence with a strategic, business alignment, your journey to go forward. Bss, should follow the clear roadmap that delivers the incremental value while building towards comprehensive organization. By leveraging a growth performance advantages, embracing cloud NATO architecture, and implementing the DevOps practices, your team can achieve the, remarkable performance improvements and the cost savings we have discussed today. The features of telecom BSS belongs to those who can deliver the robust, scalable, and secure systems and go provider, ideally foundation for this next generation of telecommunication infrastructure. So as we discussed, on previous slides, so go provide the, ideal foundation of this next generation of telecommunication project. so far, whatever the legacy is on, also, they are facing plenty of issues. So any, environmental wise or whatever it is. and performance wise or whatever it is. when we are using this, go programming language and translating into the microservice architecture, so definitely we have to see that dramatic changes, and a lot of, performance improvements. Thank you. Thank you so much.