Hello everyone. Welcome to corner 42 SRE 2025. I am a pian a technology infras specialist, and I will be talking about how adopting effective site reliability engineering practices can significantly reduce operational it streamline infrastructure deployments and enhance our overall system performance in multi-cloud infrastructures. In agenda I'll be focusing on the overview of multi-cloud infrastructures and their complexities, and then role of SRE in multi-cloud and how we can leverage SRE best practices to to reduce or operation over it and observability, automation and tools and security and much more. So multi-cloud infrastructures involve leveraging multiple cloud providers. Simultaneously to achieve optimal flexibility, resilience, and performance. So organizations are rapidly adopting multi-cloud infrastructures to capitalize on their distinct advantages. But this also introduces operational complexities that blocks effective monitoring security enforcement and performance optimization across environments. F first complexity like operational and architectural complexity. So whenever you adopt multiple clouds, you are dealing with different architectures, APIs, and service offerings. So which significantly increases complexity in management and operations. And second one, visibility and observability caps. So maintaining a clear visibility and a consistent observability across various cloud environments often becomes difficult due to different monitoring tools and standards. And the third one, data silos or fragmentation. So using separate monitoring and logging solutions for each cloud results in fragmented data that limits the ability to have a unified, comprehensive view of the entire system. And Atla the scalability and cost management so efficiently managing the scalability of data ingestion and the retention across clouds, while ensuring you remain within the budgets can present substantial financial and operational challenges. Next, we can focus on the role of SR in multicloud. So E core SRE principles so in multi-cloud, we rely on clear measures like SLI service level indicators to track the performance SLOs, like service level objectives to set reliability targets and error budgets to manage risk proactively across distributed environments. Why SRE is critical in multi-cloud. Like for coordination and standardization. SRE provides a unified approach ensuring consistent processes, tools, and practices human across diverse cloud providers and for reducing operation over it. No. We, if we implement consistent automation leveraging self feeling infrastructures and centralized observability, SRE helps reduce manual intervention and those streamlines the operations. Also for performance and reliability management. If we establish clear performance baselines and reliability thresholds it help effectively manage the complexities and dependencies between different cloud service products and that last like collaboration and organization. So for cross-functional teams, like if you follow the effective multi-cloud SRE, that involves like collaboration among teams from operations, development, security, and cloud providers that helps, share fosters shared responsibility and efficient workflows. And also if we clearly align the SRE objectives with organizational priorities that ensures the reliability and performance initiatives directly support, broader business strategies and outcomes. So next is architecting for reliability in multi-cloud. The first, like we need to focus on designing resilient services. So when architecting resilience services, it's critical to choose architectures wisely. Adopting microservices or model designs help because each component can scale and update independently. And also it helps us to reduce the downtime and enhance the reliability of the systems. So additionally implementing active or active passive strategies across clouds that ensure high availability and provides seamless failover in the event of disruptions or outages. Also planning for failure and cross cloud dependencies so we can proactively simulate potential failure scenarios, ensuring that fallback mechanisms are not only effective, but tested regularly. We can also focus heavily on maintaining the data consistency and efficient replication and synchronization across multiple cloud environments. And at last like network and data management, so reliable network and data management form a backbone of resilient multi-cloud setup. So we we can employ secure and high performance data transfer designed explicitly for multi-cloud environments. So it is vital to manage data carefully because achieving consistency across clouds without excessive replication over it and that helps balance the performance, reliability, and cost efficiency. So next we can see how we can leverage SRE practices for re reducing the opportunity over it. First is the automation and self feeling. By adopting IAC, the infrastructure as code practices and human driven automation may the organizations or teams can minimize the manual interventions and mitigate configuration drift. Second is the standardized CICD pipelines. So implementing consistent CICD pipelines across multiple cloud providers that support uniformity and reliability and software delivery. So this standardization simplifies the deployment processes, s errors, and accelerate the time to market for critical updates. And the other one is the observability and monitoring. Deploying the advanced observability frameworks can no provide or support comprehensive logging metrics, collection and tracing. To provide a deep visibility into the system health and performance. So this empowers various teams to proactively identify agonize and address issues rapidly that helps improve overall operational resilience. And at last, the capacity planning and performance optimization. Leveraging realtime performance metrics and predictive analytics enables proactive resource management and efficient auto scaling. So this approach ensures optimal resource utilization and minimizes the cost over next, how sari can improve the performance reliability. For performance optimization, we need to clearly identify and target the most critical performance areas that reduce latency and improving the throughput with residency and geographical dispersed setups. And the next is the proactive capacity planning. We can leverage predictive analytics and forecasting to efficiency manager resources that prevents both research shortage and over provisioning. And next the engineering. So if we integrate some fault injection tests across multi-cloud environments that helps us to detect weaknesses and also we can confidently validate for any failover strategies. And at last resource allocation. If we strategically distribute workloads to balance the cost, efficiency and performance. We can, and also leverage the ephemeral and serverless computing to minimize the hover it without sacrificing the reliability of systems. Next, we talk about one of the most crucial component of sorry, like observability monitoring and instant response. First is the unified monitoring. So we leverage unified monitoring techniques to seamlessly aggregate metrics, logs, and traces from diverse cloud vendors. So delivering it helps us to deliver comprehensive visibility through your through single path or pan of class. And the next is a distributor tracing. So distributed tracing ensures, end to end visibility by tracking requests across microservices or environments that span different cloud service products provide that helps provide deep insights into performance, bottlenecks, and service interactions. And the other one is the electing and incident management. So if you configure the alert thresholds and unified incident workflows, that helps us to reduce the alert noise and minimize the operational description. And also it enables the faster resolution times and improve overall service stability. And that lasts the tools and platforms tools such as open telemetry Prometheus and Grafana. Support, multi-cloud visibility and real time insights. So these powerful tools empower teams with actionable data, accelerating response, and enhancing proactive management across diverse cloud infrastructures. Next, the automation and tooling strategies. First is the automated C-I-T-C-D pipelines. If we establish automated continuous integration and deployment pipelines that helps us like streamline multi-cloud deployment releases. Also, it minimizes the human error and prevents configuration drift across platforms. And the other one is the the configuration management and policy environment. Enforcement. The tools such as like Ansible, chef, puppet, and open policy agent that consistently enforce security policies compliance and standardized to configurations across the complex infrastructures. The next one is the self filling mechanisms so we can design like intelligence systems capable of proactively detecting, mitigating and recovering from failures or performance issues autonomously. So that helps us to reduce any operational challenges. And the last platform engineering and developer enablement. We can implement some intuitive self-service portals or platform that interacts with the developers to seamlessly build, deploy and scale applications without any involvement to work on any infras activities. They do not require to have our infrastructure expertise. And the next is the security and compliance in multi-cloud. The first one, it's like your unified security frameworks. So if you implement a comprehensive security scanning, automated configuration checks and continuous posture management, that helps us to maintain a consistent security baseline across diverse cloud providers. And next, the IAM identity access management. So if you establish a centralized IAM solution. That helps us to unify roles, permissions, and enforce the least privileged access models that can support, IAM policies across multiple cloud environs. And the third one is the data production and encryption. And we can adopt some robust encryption methods for data first and in and in transit. That leverages integrated key management systems that operate eff effectively across different cloud provided platforms. And at last, the zero trust architecture. So zero trust principles strategically, can verify and secure every communication and transaction between sources, applications, and users within complex multi-cloud landscapes. And at last, to see future trends and considerations. See here the evolution of cloud native technologies like organizations will increasingly leverage serverless architectures. Or like function as a service to simplify the operations and optimize resource usage across various cloud platforms. Nowadays AI driven practices or like strategies known as AI ops or becoming, I know essential for managing the scale and complexity of large scale multi-cloud environment. Next is the advanced SRES approaches. SRE practices will evolve through advanced reliability modeling advanced observability frameworks, proactive chaos engineering and continuous resilience testing to ensure systems are robust in multi-cloud infrastructures. And at last year, the shifts in industry standards and compliance. So we can anticipate more rigorous and expansive data governance regulations associating like proactive adaptation and compliance across global cloud infrastructures. Thank you.