Hello, everyone. I am thrilled you are here as I present my defense on using microservices in the ever evolving world of software architecture. Microservices have been both celebrated in question. In this presentation, I will discuss the benefits of microservices, address common critiques, and explore how they can be effectively adapted in your organization. if they even make sense for your needs. But before we proceed, let's examine how microservices meteoric rise turned into a journey through scrutiny and skepticism. We kick off the journey by diving into what I like to call the era of hype. Spanning from about, 2014 to 2018. During this time, microservices were not just a new architectural style, they were a revolution. The tech world was buzzing with excitement. Microservices were hailed as the silver bullet that would solve all our software development woes. Every conference agenda was packed with talks on microservices. Tech blogs and industry magazines featured headline after headline. Things like microservices, the future of software architecture, why monoliths are a thing of the past, and unlock unlimited scalability with microservices. The promise was alluring. Break down your bulky, monolithic applications into small, independent services that could be developed, deployed, and scaled autonomously. It was like going from steering a cumbersome cruise ship to piloting a fleet of agile speedboats. Companies like Netflix and Amazon were poster children of this movement. They share compelling success stories about how microservices enable them to innovate rapidly, deploy hundreds of times a day, and scale effortlessly to meet global demand. Developers and architects worldwide were eager to jump on the bandwagon. The idea that we could overcome the limitations of monolithic architectures was exhilarating. It felt like we had finally found the key to unlocking unlimited agility and efficiency in software development. Microsoft Mechanics I attended conferences where speakers passionately declared that microservices were not just an option. They were a necessity for any organization that wanted to stay competitive. Phrases like infinitely scalable, highly resilient, and built for the cloud era were the mantra of the day. Adopting microservices became a sort of badge of honor. Organizations proudly announced their transition plans. Job postings saw engineers with microservices expertise as a top requirement. It was as if not embracing microservices meant being left behind in the annals of outdated technology. But amidst this excitement, there was often little discussion about the challenges that might come from such a transformation. The focus was squarely on potential benefits, with less attention paid to the complexities of distributed systems, data management across services, or the operational overhead. It was a time of unbridled optimism. The industry was caught up in a whirlwind of innovation, eager to discard the old and embrace the new. Now, before I continue further, let me confess that I was a skeptic during the first part of this time. I remember 2016, sitting in a job interview, being asked about my thoughts on microservices. Now, having extensive experience with service oriented architecture and large enterprises, I confidently said, I think they're overhyped and this enthusiasm will fade very soon. needless to say, I did not get that job. Ironically, in my next role, I found myself implementing microservices because they were perfect for the project at hand. Since then, I have built several microservice based solutions. Through these experiences, I quickly realized that microservices hold a incredible promises. But they also introduced significant complexities. And it wasn't just me. Many organizations began sharing similar insights. This brings us to the next chapter of our journey. How the initial excitement gave way to rising skepticism. As the industry grappled with the practical realities of microservices. As the initial excitement around microservices began to settle, a new phase emerged, this rising skeptic phase. Expanding from about 2018 to 2022. Now here, organizations had eagerly jumped. on microservices, on the microservices bandwagon. But they started to face unexpected challenges. The promise of infinite scalability and seamless deployments were met with the realities of increased complexity and operational overhead. Implementing microservices was not as straightforward as many had thought. There was issues such as distributed, distributed systems. Inter service communication issues and data consistency problems. Developers found themselves spending more time on managing infrastructures and debugging complex issues rather than building new features. The microservice architecture introduced a myriad of new components service registers, API gateways, load balancers that required expertise and maintenance. Moreover, the operational cost began to rise. Running multiple services meant increased resource consumption, from computing power to monitoring tools. The simplicity of deploying a monolith gave way to the intricacies of deploying and orchestrating numerous services. Organizations started to question whether the benefits outweighed the cost. Was the shift to microservices delivering on its promises? Or had we underestimated the challenges inherent in such a transformation? Prominent voices in the tech community began expressing their concerns. Articles with titles like, the microservice trade off, monoliths strike back, and the hidden cost of microservices started appearing. Renowned software architects shared their experiences, pointing out that microservices were not a one size fits all solution. They emphasized that without proper planning and deep understanding of the domain, microservices could lead to more problems than they solve. Some common critiques include, breaking down applications into many services was causing unnecessary complexities and over engineering. Increased, network calls leading to performance bottlenecks. Ensuring data consistency across services became a significant challenge and caused data management difficulties. And end to end testing was complex due to numerous independent services. The initial enthusiasm was giving way to prudence. Teams realized that microservices demanded a cultural shift, not just a technical one. It required cross functional teams, developed DevOps practices, and a strong emphasis on automation and monitoring. Many began to ask, was adopting microservices the right choice for our organization? And do we have the necessary infrastructure and expertise to manage this complexity? This period of rising skepticism wasn't necessarily negative. Instead, it represented a maturation in the industry's understanding of microservices. We moved from seeing them as a silver bullet to recognizing them as a powerful tool that requires careful consideration. It was time for reflection and recalibration to assess when and how to use microservices effectively. Continuing our journey, we strive against the phase that I refer to as losing faith. Spanning the last couple of years, during this past, during this period, the skepticism that had been rising began to solidify into outright doubt, for many organizations. The challenges and complexities encountered led some to question whether microservices were the right path at all. We were hearing about organizations that had initially invested heavily in microservices began to reassess their architectural choices. For some, the operational burdens, talent shortages, and unrealized benefits led to decisions to scale back or even abandon microservices in favor of alternate architecture. Architectures. Articles and thought piece, pieces emerged with titles like it's time to abandon microservices. The microservice retrospective. Was it worth it? And embracing the model of the modular monolith. Prominent tech leaders voiced their concerns more openly. They highlighted cases where microservices had led to project delays, increased costs, and performance issues. The complexity of microservices required specialized expertise that was hard to find. The industry began to acknowledge that microservices were not a one size fits all solution. Without the right tools, culture, and resources, microservices could become more of a hindrance than a help. Common reasons for losing faith included overwhelming complexity due to sheer number of services being lost. unmanageable. Teams lacked the necessary experience in DevOps, distributed systems, and cloud infrastructure. Existing tools did not adequately support microservice needs, and organization structures were not adapted for independent services development and deployment. In some cases, organizations made the difficult decision to revert to monolithic architecture or adapt a modular monolith approach. They sought to regain control over their systems, reduce complexity, and focus on delivering business value. This period is marked by a sense of disillusionment. The lofty expectations set during the era of hype had not been met for everyone. The pendulum has swung from excitement to fear. to skepticism. And now for some to abandon it. Now, having traversed the highs of the hype and the lows of the skepticism and the challenges that led some to lose faith, we now stand at the brink of a new era, the era of intelligent maturity. This phase is about leveraging experiences, embracing best practices, and implementing microservices where they make the most sense. It is a time to use microservices, but use them wisely. And only when they actually make sense. Advancements in tooling, the improved orchestration platforms, enhanced monitoring solutions, and robust security practices are contributing to smoother microservice operations. Importantly, there is a deeper understanding of when and how to use microservices effectively. Organizations recognize that microservices are not a universal solution, but a powerful option when applied to the right problems. This era represents a time of mastery and innovation where microservices are unleashing the power that they have been promising. But as we move forward, organizations are poised to harness this full potential microservices, driving unprecedented innovation and delivering exceptional value. Now that we explored the evolution of microservices, let's shift our focus on how we can apply these lessons to maximize their benefits, for our organizations. Here's what we're going to cover during the rest of this presentation. We'll begin by comparing various architectural styles, including monoliths, interior architectures, modular monoliths, and microservices, to understand their strengths, weaknesses, and ideal use cases. With that context, we'll cover the core benefits of microservices, and why they are a compelling choice for modern applications. Following that, we'll candidly discuss Common critiques and challenges associated with microservices, providing a balanced perspective. Afterward, we'll explore practical strategies and best practices to overcome these challenges and ensure you can adopt microservices successfully. Then I reflect back on the four primary architectural styles I introduced in comparing architectural styles to provide guidance on, on how to pick the right architectural style for your next project. Finally, I will wrap up with key takeaways and consider how you can apply these insights to your own organization moving forward. By the end of this session, you will not only understand why microservices still matter, but also gain practical insights on how to leverage them effectively, alongside other architectural options in your own organization. Hey, wait a second. We've been chatting all this chat about microservices, and I still haven't introduced myself. My name is Chad Green. I'm the Senior System Architect with 35 years experience in software development and architecture. throughout my career, I have had the pleasure of working with a variety of technologies, but my true passion lie in microservices, event driven architectures, serverless computing, and API first designs. I have helped organizations from nimble startups to global enterprises navigate the complexities of modern software architecture, enabling them to build scalable, resilient systems that drive innovation. Outside of work, you'll often find me in my Lego room building intricate Lego sets or updating my Lego city. I find it gives me a fresh perspective to my professional life and lets me step away from thinking about complicated software architectures. Feel free to connect with me after the presentation. I would love to hear your thoughts or answer any questions you might have. Now that you know a little bit about me, let's jump back into our exploration. And to truly appreciate the advantages of microservices, it's essential to understand how they compare to other architectural styles. So let's begin by comparing architectural styles. But before, let's talk about what we're talking about when we mean architectural styles in the context of software architecture development. An architectural style is essentially a blueprint, a set of principles and patterns that guide how we structure our software systems. It shapes how components interact, how data flows, and how the system scales and evolves over time. Choosing the right architectural style is crucial because it influences several key aspects. How well can the system handle increased load? How easily can the system be updated or modified? How effectively can your team develop and deploy code? It impacts everything from development speed to systems ability to adapt to future requirements. In our discussions today, we'll be exploring four prominent architectural styles, monoliths, n tier architectures, microservices, and modular monoliths. By understanding the strength and weakness of each, we'll better, we will be better equipped to make informed decisions about which style aligns best with our organizational needs and goals. First up, we have the classic monolithic architecture. A monolith is essentially a single unified application where all the components are interconnected and interdependent within one code base. Let's talk about the advantages with this approach. Monoliths are often simpler to develop and deploy, especially for small teams or projects. Internal calls within the application are faster than calls over a network, server. over a network between services. With all the code in one place, it is straightforward to trace through the code and find and fix issues. However, monoliths come with significant challenges. Scaling a monolith means replicating the entire application, even if only one part needs additional resources. A small change requires reapplying the entire application, which can slow down the release cycle and increase risk. As code base, as your code base grows, it becomes more complex and harder for developers to understand and modify. And making significant changes or adapting new technologies can lead, can be challenging without affecting the entire system. Think of a monolith as a big block of marble. It's solid and sturdy, but if you need to change, if you need to make a change, you have to chisel away at the whole block, which can be time consuming and risky. Monolithic architectures can work well for small applications or when you need to go to market quickly. However, as your application and team grows, the monolith can become a bottleneck, slowing down development and deployment. Understanding the monolith strengths and weaknesses help us appreciate why other architectural styles, like microservices, have emerged to address these challenges. Next, let's explore n tier architecture, also known as layered architecture. In an n tier architecture, the application is divided into logical layers or tiers, each with distinct responsibilities. Typically, layers like the presentation layer handling the user interface. The business logic layer, where the core functionality resides. And the data access layer, managing transactions, or interactions, with the database. This separation brings several advantages. Each layer is focused on a specific task, making the system more organized and maintainable. Layers can be reused across different applications, saving development time, saving development time. Teams can specialize in individual layers, improving efficiency and expertise. However, n tier architectures also present some challenges. Layers are often closely connected, so changes in one layer can impact others. Making the system less flexible. Scalability typically happens at the application level, not at the individual layer level. Limiting the scalability options. And data likely is passing through multiple layers, which can introduce latency and affect performance. You can think of NT architecture like a layered cake. Each layer depends on one, on the one below it. And together, they create the whole cake. What? If there's an issue within one layer, it can affect the entire cake. N tier architecture often offers more structure than a monolith, bringing organization and clarity. However, it can still face challenges with scalability and agility, especially in the environments where requirements change rapidly. Understanding NTR architecture helps us see how software design evolved to address the limitations of monoliths, leading us closer to architectures like microservices. Now. Let's dive into microservices, the architectural style, at the heart of our discussion. In a microservice architecture, an application is composed of a collection of small, independent services. Each service focuses on a specific, business capability and operates autonomously. These services communicate over well defined APIs, often using protocols like HTTP, REST, gRPC, or messaging systems. Let's explore the advantages of microservices. Now, each service can be scaled independently. If a particular service experiences high load, you can allocate more resources to it without scaling the entire application. Teams have the freedom to choose the most scalable technology or programming language for their language. Services can be updated, deployed, and rolled back individually, which accelerates development cycles and reduces risk. And if one service fails, it doesn't necessarily bring down the entire system. This improves overall system resilience. Of course, now, there are some challenges. To include, managing numerous services requires a sophisticated infrastructure and robust DevOps practices, including containerization, orchestration, and monitoring. Dealing with network latency, load balancing, and service discovery adds complexity. Inter service communication can fail due to network issues, requiring strategies for retries and fallbacks. Ensuring consistency across networks. Services is complex. Transactions that span multiple services are harder to implement, often requiring eventual consistency and compensatory mechanisms. And testing individual services is straightforward, but end to end testing becomes more complicated due to the interactions between services. You can think of microservices as a fleet of small boats instead of a single large ship. Each boat operates independently and can navigate its own path. This provides greater flexibility and agility. But coordinating the fleet requires effort and sophisticated communication. Microservices are powerful for large, complex applications that need to scale and evolve rapidly. They enable organizations to innovate faster and adapt to changing business needs. However, they demand a mature organizational culture and technical infrastructure, including automation, continuous integration and deployment, such as CICD, and comprehensive monitoring. Understanding both the benefits and challenges of microservices is crucial to making informed decisions about whether the architectural style fits your organization's needs. Now finally, let's explore modular monoliths, an architectural style that offers a middle ground between monoliths and microservices. In a monolithic monolith, in a modular monolith, We have a single application that is divided into distinct independent modules. Each module encapsulates specific functionality and maintains strict boundaries, communicating internally within the application. So advantages? first off, clear module boundaries make the code base easier to understand and maintain. Developers can focus on specific modules without wading through the entire code base. Since all modules run within the same application process, intermodular communication is fast, avoiding the network latency associated with microservices. You deploy a single application, which simplifies the deployment process compared to managing numerous microservices. And a modular monolith can serve as a stepping stone, towards microservices. If needed, modules can be extracted into services over time. Of course, there are challenges to consider. Scaling is still done at the application level. If one module requires more resources, you have to scale the entire application. Changes in one module necessitate redeploying the whole application, which can impact deployment, frequency, and risk. Without strict discipline, module boundaries can erode over time, leading to tight coupling between modules. And a failure in one module can still affect the entire application, since all modules share the same processes, same process space. So we can think of a module monolith like a well organized toolbox. Everything, is in one place, but each tool or module has its own compartment. it's organized and efficient, but you have to still, you still have to carry the entire toolbox. Even if you only need one tool, modular monoliths offer a balanced approach. They, They bring structure and organization to your code base without the operational overhead of microservices. For many applications, especially those not requiring extreme scalability or independent scaling of components, a modular monolith can provide the necessary flexibility and maintainability. Understanding modular monoliths helps us see that there's more than one way to achieve separation of concerns and scalability. The best architectural choice depends on your project's specific context and needs. Having explored the spectrum of architectural styles, from the simplicity of monoliths to the organization of interior architectures, the flexibility of microservices, and the balance of modular monoliths, you've gained a comprehensive understanding Of their strengths and challenges. Each style offers a unique advantage, but as we have seen, they also come with their own set of trade offs. This begs the question, what makes microservices stand out as a compelling choice for modern applications? Now let's dive into the core benefits of microservices and understand why this architectural style has become a cornerstone for modern scalable applications. We'll explore how microservices can transform the way we build, deploy, and manage software, offering unparalleled advantages in scalability, flexibility, and resilience. By the end of this section, you will see how microservices address the challenges we have discussed and why they are a powerful tool in the Architects Toolkit. One of the most significant benefits of microservices is scalability. In a microservice architecture, each service is a separate component that can be scaled independently based upon its specific demands. This means if one service experiences increased load, say, like the payment processing service during holiday, shopping rush, we can allocate more resources to just that service without scaling the entire application. This approach optimizes resource utilization and cost, ensuring that we're not over provisioning resources for services that don't need them. Additionally, microservices support elasticity. With modern cloud, platforms and orchestration tools like Kubernetes, Kubernetes services can be scaled automatically in response to traffic patterns. This approach allows applications to handle varying workloads seamlessly, scaling up during peak demands, or scaling up during peak times and down during lulls, which is both, efficient and cost effective. To illustrate, consider an e commerce platform during Black Friday. The product catalog and checkout services can scale out to meet the surge in demand, ensuring smooth user experiences without overtaxing the other parts of the system. In essence, microservices enable us to build applications that are flexible and responsive, capable of growing with our user base and adapting to changing demands. Another crucial benefit of microservices is fault tolerance. With microservices, applications are composed of multiple independent services. This service isolation means that if one service fails, it doesn't necessarily bring down the entire application. For example, if the recommendation service on a streaming platform encounters an issue, users can still browse and watch content. The failure is contained. This isolation reduces the risk of systematic failures and enhances overall system scalability, leading to more resilient applications. To further strengthen fault tolerance, we implement various resilience strategies. These include retry policies to handle transient errors, circuit breakers to prevent repeated attempts to failing services, and fallback mechanisms to provide default responses. We also use timeouts to prevent services from waiting indefinitely for a response. A design for graceful degradation. Ensuring the applications can continue to function in a limited capacity if certain services are unavailable. By incorporating these strategies, microservices can withstand the failures and continue to provide essential functionality to users. This fault tolerance is essential for applications where uptime and reliability are critical. Next, let's explore how microservices enable Independent deployments, a game changer for modern development practices. In a microservice architecture, each service is a separate deployable unit. This means teams can update and deploy their services independently without needing to coordinate with other teams or wait for a synchronized release for the entire application. This capability leads to faster release cycles, updates. rather, whether they're for new features or bug fixes can be delivered to users more quickly, providing a comprehensive advantage and improving customer satisfaction. Moreover, reduced deployment risk is a significant benefit. Deploying smaller incremental changes lower the likelihood of introducing system wide issues. If there's a problem with a deployment, it's easier to roll back and fix. without impacting the entire application. Additionally, microservices offer flexibility in scheduling. Teams can deploy when they are ready. aligning releases with business priorities and market demands. Without being tied to lengthy release cycles or waiting for other teams to complete their work by enabling independent deployments, microservices support more agile and responsive deployments practices, aligning perfectly with modern day DevOps and continuous delivery approaches. Another core benefit of microservices is team autonomy, empowering teams to work effectively, efficiently and innovatively. In a microservices architecture, we organize around autonomous cross functional teams. Each team owns the entire life cycle of their service, from development and testing to deployment operations. This ownership encourages accountability and fosters a strong sense of pride and responsibility. This structure enables parallel development. Multiple teams can work on different systems. or different services at the same time without stepping on each other's toes. This concurrency accelerates development and fosters innovation as teams can progress independently. Additionally, microservices can facilitate faster decision making. Teams can make techno technology and implementation choices that best fit their services need without waiting for the company wide consensus or being constrained by a single technology stack. By promoting team autonomy, microservices reduce dependencies and bottlenecks between teams, leading to increased productivity and a more agile organization. This empowerment not only accelerates development, but also enhances team morale and job satisfaction. Now let's explore how microservices offer flexibility in technology choices, empowering teams to select the best tools and technologies for their specific needs. First off, microservices enable polyglot programming. Since each microservice is a separate entity, teams can choose to, the most appropriate technology stack by pro, by it, be it programming languages, frameworks, or databases for their service. This means that one service might be written in Java, another in Python, and js, each optimized for its purpose. This flexibility allows teams to leverage strengths. of different technologies, optimizing performance and efficiency for each service's unique requirements. Second, microservices in, foster innovation and experimentation. Teams are encouraged to adapt, to new and emerging technologies. Where they make the most sense, experimenting without risking the stability of the entire system. This facilitates continuous innovation as teams can implement cutting edge solutions in their services, driving the overall advancements of the application. Third, microservices reduce technology lock in. By avoiding a monolithic technology stack for the entire application, organizations minimize dependencies on a single technology vendor or platform. It is easier to replace or upgrade individual services as technologies evolve, enhancing the system's longevity and adaptability. This means your applications can stay current with technological advances without requiring a complete overhaul. Overall, the flexibility in technology choices provided by microservices not only optimizes each services, each service, but also empowers teams to innovate and adapt swiftly in the ever changing tech landscape. Finally, for now, let's, we have how microservices enable alignment with business goals, enhancing organizational agility and effectiveness. First, microservices support organization, organizing around business capabilities. In this model, each microservice is designed to handle a specific business function or domain. For example, in an e commerce platform, separate services might handle inventory management, payment processing, and customer reviews. By structuring services this way, we can enhance collaboration between development teams and business units. Teams have a clear understanding of their, of how their work directly supports business objectives, fostering a more integrated and purpose driven approach. Next, we have autonomous cross functional teams. These teams comprise of the necessary skills developers, of developers, testers, operations, to develop and operate their service end to end. This promotes ownership and accountability, as teams are fully responsible for their services success from conception to deployment and beyond. This structure improves responsiveness to business needs. Teams can quickly implement changes or features in their services, aligning development closely with business priorities and customer feedback. Finally, microservices enhances business agility. By aligning organizations and teams with businesses, Business capabilities. Organizations can accelerate the delivery of new features that are more impactful to the business. Microservices enable rapid adoption to market changes. If a new organization or new opportunity arises or a competitor introduces a feature, teams can respond swiftly without being hindered by the complexities of a monolithic system. The agility, reduces time to market for innovations, giving organizations a competitive edge and ability to meet customer expectations more effectively. In essence, microservice bridge the gap between technology and businesses. Encourage ensuring that the technological efforts. Are directly contributing to business goals and enabling organizations to thrive in a dynamic market environment. So as we have explored, the core benefits of microservices are scalability, fault tolerance, independent deployments, team autonomy, flexibility in technology choices and alignment with business goals. We have showcased their transformative potential. These advantages enable organizations to build resilient, agile, and innovative systems that can adapt to changing demands and drive business successes. However, like any architectural style, microservices come with their own set of challenges. It's important to acknowledge that while the rewards can be substantial, the journey isn't always straightforward. In this next section, I'm going to address several of the common critiques of microservices. While there are many critiques, in the interest of time, I'm going to focus on the top five that most organizations encounter. As we look into these critiques, you'll notice common themes that highlight the inherent complexities of implementing microservices. These critiques resonate strongly with me because I have seen how overlooking these challenges can lead to unsuccessful microservice implementations. By understanding these challenges up front, you will be better equipped to determine if microservices align with your architectural needs and organizational readiness. Maybe there's too much complexity in the implementation. To make it, feel worth the effort. Ultimately, by understanding these challenges, you'll be better prepared to navigate the journey and reap the substantial rewards of Microsoft can offer. Much like a journey through uncharted territory. Microservices offer a great reward, but also present obstacles that must be navigated carefully. microservices increases operational overhead. There is the added complexity in deployment, monitoring, and maintenance compared to monolithic architecture. first off, the critiques are very much correct. Microservices do add operational complexity. This complexity stems from the need to orchestrate Multiple services, each potentially with his own set of dependencies and resource requirements. It requires robust infrastructure and tooling to handle aspects like service discovery, load balancing, scaling and fault tolerance. To adjust these challenges, various approaches and tools are available across different cloud platforms. For container organization, Kubernetes is the way to go. It's a powerful platform that can handle large scale deployments and offers extensive customization. Services like Azure Kubernetes Service, better known as AKS. Amazon Elastic Kubernetes Service, better known as EKS. And Google Kubernetes Service, sometimes known as GKE, provides managed Kubernetes clusters in the cloud. These services offer managed Kubernetes environments for deploying and scaling containerized applications. For monitoring and logging, tools like Prometheus, which excels at metrics collection, and the Elk Stack. which includes Elasticsearch, Logstash, and Kibana are ideal for logging, aggregation, and analysis. They offer robust solutions to tracking performance metrics and analyzing logs across multiple services. However, in my experience, especially when working with organizations that have standardized Microsoft technologies and Azure services, or the other clouds and their compatible technologies, I have found that leveraging native tools provided by the cloud platforms can greatly simplify organizational complexity. Instead of managing kubernetes clusters ourselves, we have utilized Azure Container Apps, a serverless container hosting service. It abstracts away the underlying infrastructure, allowing us to deploy and run containerized applications without the overhead of managing Kubernetes directly. This approach, reduces operational burden as Azure handles the orchestration, scaling, and maintenance of the underlying resources. It lets us focus on developing our services rather than managing infrastructure. Similarly, services like AWS Fargate and Google Cloud Run offer serverless container platforms providing similar benefits on their respective platforms. Additionally, we have turned to serverless offerings like Azure Functions, AWS Lambdas, and Google Cloud Functions to enable us to run code in response to events without provisioning or managing servers. This approach abstracts away much of the infrastructure management, allowing development teams to focus on writing code that delivers business value. Azure Functions allow us to deploy individual functions that can scale independently and respond to specific triggers, making them ideal for event driven architectures. For monitoring logging, I have found that Azure Monitor with Application Insights and Log Analytic Workspaces provide comprehensive insights into the health and performance of our applications. This tight integration within the Azure ecosystem simplifies setup and management. Other cloud providers offer similar integration tools, such as AWS CloudWatch and Google's Cloud Operations Suite. other, I'm sorry, automation and CD pipelines are essential across all platforms to manage operational complexity, effectively. Tools like Azure DevOps and GitHub Actions have been invaluable in automating our build, test, and deployment processes. Likewise, AWS CodePipeline and Google Cloud Build provide robust CICD capabilities on their platforms. By leveraging these serverless offerings, monitoring tools, and automation platforms, have been able to mitigate much of the operational complexity associated with microservices. In conclusion, while microservices introduce operational complexity, selecting the right tools and platforms can align with your organizational needs, and, simplify management, enabling you to fully leverage the benefits of microservices. So whether you're using Azure, AWS, GCP, or another platform, it's important to evaluate the services they offer. Like serverless functions, container platforms and logging solutions to reduce overhead and streamline operations. Another significant, critique of microservices revolve around the challenges inherent in distributed systems. Breaking an application into multiple services introduces complexity in how these services communicate and maintain data consistency. Firstly, let's discuss network, the network complexity. Some of the issues we have, have within microservices include handling network latency and ensuring reliable communication. between, services can be complex. Inner service communication adds overhead, and network issues can lead to unexpected failures. We also need to manage load balancing to distribute requests effectively across instances. Secondly, there is the issue of data consistency to include. Ensuring data integrity across multiple services is more challenging than with than with, than within a monolith. Managing transactions in a distributed environment can be difficult, as traditional ACID transactions do not easily extend across services. This can lead to data anomalies and conflicts if not properly handled. To address these challenges, there are several strategies we can employ. One effective approach is to is using asynchronous communication. By leveraging messaging queues and adopting event driven architecture, we can decouple services. This reduces dependency on the immediate availability of other services, improving resilience. Services communicate by sending and receiving messages asynchronously, which can help us manage network latency and improve fault tolerance. In my experience, focusing on serverless and event driven design, such as Azure Functions and Azure Service Bus, provide a robust way to implement asynchronous communication. These services enable us to build reactive systems that respond to events that as they occur without tight coupling between services. Implementing retry policies and circuit breakers is also crucial. Retry policies allow services to handle transient failures by retrying operations after a delay. Circuit breakers help prevent cascading failures by stopping, attempts to communicate. with a failed service after repeated failures. These patterns improve system scalability and resilience. Adopting eventual consistency models is another strategy. In distributed systems, it is often acceptable for data to be temporarily inconsistent to achieve better scalability performance. Implementing patterns like event sourcing and CQRS, or Command Query Responsibility Segregation, can help you manage data consistency across services. These patterns allow services to update independently and synchronize changes asynchronously. However, it's important to recognize that while these strategies mitigate certain challenges, they can introduce additional complexity. For example, event driven architecture can make it harder to trace the flow of data and understand the system's state at any given time. Balancing consistency, availability, and scalability requires careful architectural consideration and deep understanding of the trade offs involved. Some organizations use service meshes to manage inter service communication, providing features like traffic management and, security and observability. While these services meshes can be powerful, they also add another layer of complexity. In my work, I have found that for many applications, especially those leveraging serverless and event driven architectures, a service mesh might not be necessary. Instead, focusing on designing for asynchronous communication and using managed services can simplify the system. Ultimately, addressing distributed systems Challenges in microservices requires thoughtful design and the right set of tools and patterns. By implementing strategies like asynchronous communication, retry policies, and eventual consistency, we can build systems that are robust, scalable, and capable of handling the complexities of a distributed environment. Next, we'll explore another common critique, data management and consistency. Diving deeper into how we manage, how we handle data across distributed services. And in microservice based systems, data is often spread across multiple services, each with its own database or data store. This leads to complexities that are not present in a monolithic system. First, ensuring the data consistency across services is more complex. Managing transactions that span across multiple services isn't straightforward. Traditional asset transactions do not extend easily in a distributed system. This can lead to difficulties in maintaining a single source of truth. Data may reside in multiple places, and keeping it synchronized requires careful planning. Organizations often struggle with the idea In a microservice architecture, data will be in multiple locations, and that's okay with the right practices. Understanding and embracing this reality is essential. how do we address these challenges? One key strategy is embracing eventual consistency. Except that data might not be instantly consistent across all services. Design systems to handle temporary inconsistencies gracefully. Recognize that eventual consistency can be a strength and not necessarily a weakness. By accepting that data will become consistent over time, we can build more scalable and robust systems. This requires a shift in mindset, but opens up new possibilities for performance and resilience. Next, we can implement specific patterns to manage distributed interactions and data consistency. The Saga pattern is one such approach. It manages distributed transactions by breaking them into a series of local transactions. Each service plat, performs its local transaction and then pushes an event or message to trigger the next action. If a failure occurs, compensating transactions are to undo the changes made by previous services. This way, we maintain overall data consistency as transactions are executed to undo the challenges or the changes made by previous service. This way, we maintain overall data consistency without relying on distributed transactions. Another powerful platform, or pattern, is event sourcing. Instead of storing just the current state, we store all changes to the application state as a sequence of immutable events. The current state is reconstructed by replaying these events. This ensures a single source of truth, through an authoritative event log. Event sourcing provides a clear audit trail and can simplify debugging and compliance efforts. To implement these patterns effectively, we can leverage tools and frameworks that support messaging and event driven architectures. Apache Kafka is a, is a popular distributed event streaming platform that enables building real time data pipelines and applications. Cloud specific implementations like Azure Service Bus, Azure Event Hubs, and AWS Kinesis offer similar capabilities with seamless cloud integration. These tools allow services to communicate via events, facilitating data synchronization and consistency across the system. By adopting these patterns and leveraging them, appropriate tools, we can now overcome the data management. Next, we'll explore another common critique, testing complexity, and discuss how to navigate the challenges of testing in a microservices environment. With multiple services interacting, end to end testing becomes more challenging. Coordinating and verifying the behavior of numerous components can be complex. There is also an increased need for extensive integration and contract testing to ensure services interact correctly and adhere to agreed interfaces. But here is the opportunity. Because we've, separated everything into independent services, we can better test the individual pieces of business logic. When testing a shipping service, for example, we do not have to worry about how the payment service works, at least not until we get into integration testing. This separation allows for more focused and effective unit testing, ensuring each service functions correctly in isolation. Integration testing is important in any architectural style, but crucial in microservices. By thoroughly testing the interaction between services, we can catch issues early and ensure smooth collaboration between components. Moreover, comprehensive testing is not just about finding bugs. It is about finding, building confidence amongst users. stakeholders, they need assurance that what we are deploying will also will work as intended. In microservices, there's a lot of happening underneath the covers, including services that stakeholders didn't even explicitly ask for, but are necessary to realize their vision. Testing gives us the confidence that these unseen components are functioning correctly. To navigate these challenges, we need a comprehensive testing strategy that includes multiple levels of testing. Unit testing, testing individual components in isolation to verify their correctness. Next we have integration testing, verifying that services interact correctly with each other. This is a vital in microservices. Contract testing, where we ensure services adhere to agreed upon interfaces. And end to end testing, where we test complete user flows using, through the system. These are essential. for validating the entire application behavior. In terms of tools, PACT facilitates contract testing by allowing us to define and verify services and contracts. It's something I've been exploring and shows promise in reducing integration issues. For end to end testing, tools like Playwright and Selenium offer modern, automate UI testing. While these tools can be more fragile, implementing them correctly ensures they add value. But remember, they are at the top of the pyramid. You've built up to other testing before depending on end to end testing, giving it a strong foundation to rely on. However, this isn't a presentation about testing tools. The key takeaway is the importance of comprehensive testing to ensure we are deploying reliable software and instilling the confidence with our stakeholders. By continuously testing our code at every stage, we catch issues early and reduce the risk of defects reaching production. In summary, while testing complexity is a valid critique of microservices, it presents an opportunity. By leveraging comprehensive testing strategies, we can assure our services not only work individually, but also function seamlessly together. This thorough approach to testing builds confidence amongst our stakeholders and helps us deliver robust, reliable software that meets their needs. Okay, one last critique I want to address today is the skills and expertise requirements they demand. Now, my first response to people raising this type of critique is, boo hoo. If you are afraid of the need to learn, then software development might not be right for you. If your team has a hard time with this, then you need to work on that. But let's get back to the point. Some of the challenges normally associated with microservices is that microservices necessitate a higher level of expertise in DevOps, distributed systems, and cloud infrastructure. And they are not wrong. Teams need to understand complex architectures, deployment processes, and the nuances of managing distributed systems. Additionally, there is a steep learning curve for teams transitioning to microservices. This transition requires a significant mindset shift and adapt, adaption to new practices and tools. However, this critique, while valid, should not be seen as a negative. In any architectural style, continuous learning is essential, even with legacy systems. New techniques are needed to solve evolving problems. Encouraging continuous learning and professional development within the team is crucial. Your company should foster a culture of growth and development. And we need to promote the idea that learning is a key part of being a professional in software development. In fact, software development professionals who do not want to learn are truly not professional. If one doesn't want to learn, then perhaps software development isn't right for the right path. To support this continued learning, we can leverage various external resources. For example, we can, utilize training programs, workshops, and certification courses to upskill the team, access online resources, communities, and mentorship opportunities to stay current with industry trends and best practices. By embracing these resources, we can assure our teams have the necessary expertise to succeed in a microservices environment. It is important to advocate for the continuous learning, not just as a necessity, but as a positive aspect of our professional growth. Learning new skills and staying updated with industry advancements not only enhances our capabilities, but also keeps our work engaging and fulfilling. In the fast paced world of technology, standing still is not an option. We must keep moving forward. And that means embracing the learning curve and turning it into an opportunity for growth. as we've explored, the common critiques of microservices, operational complexity, distributed system challenges, data management and complexity issues, testing complexities, and the higher skills and expertise requirements are all valid concerns. Thank you. However, each of these challenges can be effectively addressed with the right strategies, tools, and mindsets. By embracing testing strategies, fostering continuous learning, implementing patterns like saga and event sourcing, and leveraging appropriate tools and frameworks, we can overcome these obstacles and harness the full potential of microservices. It is important to recognize that while microservices introduces complexities, they also offer significant advantages in scalability, resilience, and agility. The key is to navigate these complexities thoughtfully and thoroughly and strategically. Now that we've addressed the common critiques and challenges of microservices, let's shift our focus to strategies for successful microservices implementation. In this section, we'll look at practical approaches and best practices that can help you effectively adapt microservices within your organization. We'll explore actionable strategies such as leveraging automation and CICD pipelines, implementing robust monitoring and observability practices, and fostering a culture of continuous improvement. By adapting these strategies, you can confidently navigate the complexities of microservices and unlock their transformative potential for your organization. To make the most of our time together, I have grouped the strategies for successful microservice implementation into thematic areas. This approach will help us understand how different aspects of adaption work together to create a cohesive and effective microservices architecture. We'll begin with culture and organizational strategies. As the foundation of any successful microservices implementation lies in the people and the organizational mindset. Let's see how embracing a DevOps culture, fostering continuous learning, and aligning teams with business capabilities can set the stage for microservices success. First, let's talk about embracing the DevOps culture. In the context of microservices, fostering a DevOps culture is crucial. It involves breaking down silos between development and operation teams, and encouraging collaboration. By forming cross functional teams that own services from development through deployment and into operations, we promote a sense of shared responsibilities. This ownership means teams are accountable for the entire life cycle of their services, which enhances accountability and encourages higher quality outcomes. Automation is a key aspect of DevOps culture. Implementing continuous learning and continuous deployment pipelines, steering lines the development process and reduces manual errors. Tools like Azure DevOps, GitHub Actions, or Jenkins facilitate this automation, allowing teams to deploy changes rapidly and reliably. Embracing a DevOps culture not only improves efficiency, but also enhances collaboration and communication across your organization, laying a microservices implementation. Next, let's focus. or let's explore the importance of fostering continuous learning within your teams. Microservices require teams to be proficient in various areas like distributed systems, DevOps practices, and cloud infrastructure. Therefore, promoting, professional development is essential. Encourage team members to upskill and learn new technologies by providing access to training programs, workshops, and certification courses. Build a learning culture means fostering an environment where, where learning is valued and supported. This can be achieved by hosting regular tech talks, workshops, or lunch and learn, events. Yeah, lunch and learn sessions where team members can share knowledge and learn from one another, participating in industry conferences, webinars and community events can provide valuable insights and network opportunities by fostering continuous learning. You empower your teams to tackle the complexities of microservices with confidence and innovation. Finally, let's, discuss aligning teams with business capabilities by organizing teams with around business domains. Each team owns microservices, related to Pacific, business, functions. This alignment enhances domain expertise within the team and fosters a sense of ownership over the services they develop and maintain. It also facilitates better communication and collaboration between technical teams and business stakeholders. When teams understand the business context and objectives, they can make technical decisions that directly support and advance business goals. Empowering autonomous teams by granting them the authority to make decisions about their services encourages agility. Teams can respond more quickly to changing business needs and innovate without unnecessary bottlenecks. By aligning teams with business capabilities, you ensure that your microservices architecture is not only technically sound, but also strategically focused on delivering business value. In summary, focusing on culture and organizational strategies is vital for the success of microservices implementation. By embracing a DevOps culture, fostering continuous learning, and aligning teams with business capabilities, you create an environment where teams are empowered, collaborative, and aligned with the organization's goals. These cultural and organizational functions enable technical strategies to flourish, paving the way for robust and effective microservice architecture. Now, having established a strong foundation with cultural and organizational strategies, we can now turn our focus to the technical best practices that microservices implementation. In this section, we'll explore three key strategies, beginning with clear architectural vision, implementing effective testing strategies, and investing in monitoring and observability. These practices are practical, are crucial for building a resilient and scalable microservices architecture that can meet the demands of modern applications. First, let's discuss the importance of beginning with a clear architectural vision. A well defined architecture vision is crucial for the development and evolution of your microservice architecture. To start, it's essential to define the service boundaries using techniques like domain driven design. This involves identifying bounded contexts and ensuring each microservice aligns with specific business capabilities, creating a cohesive and modular architecture. Developing a comprehensive plan is equally important. Create detailed architecture diagrams and documentation that outline the overall structure, scalability, security, and integration considerations. Finally, it's crucial to communicate the architectural vision with all stakeholders. Ensure everyone understands the goals, principles, and reasoning behind the architecture to align efforts and expectations. A clear architectural vision serves as a roadmap, guiding your team's efforts and ensuring a structured approach to building and maintaining your microservices environment. Next, by implementing effective testing strategies. we can ensure the reliability and stability of your microservices. A comprehensive testing approach includes multiple levels of testing to cover various aspects of your system. Start with unit testing to test individual components in isolation. This ensures that each service functions correctly on its own. Then, move to integration testing to verify interactions between services, ensuring they work together as expected. Contract testing is crucial for ensuring service interfaces meet expectations. Finally, perform end to end testing using tools like Playwright or Selenium to validate the entire system flow from start to finish. Automating these, These tests in CICD pipelines ensure they run continuously and catch issues early in the development process. Focus on the critical paths in high risk areas to prioritize testing efforts where they matter the most. Ensuring that essential functionality is thoughtfully validated. By implementing a comprehensive automated testing strategy, you can enhance the reliability and stability of your microservices architecture. Now, finally, let's discuss the importance of investing in monitoring and observability. Effective monitoring and observability are crucial for the main, for maintaining the health and performance of your microservices architecture. By starting start by centralizing, logging and monitoring using integrated tools like Azure Monitor and Application Insights or AWS CloudWatch. These tools provide a comprehensive view of your system's health and performance. Implementing distributed tracing to track requests as they flow through multiple services. This helps you pinpoint issues and understand the interaction between services. Next, step, set up alerting and dashboards to proactively monitor your system. Establish alerts for critical issues so you can respond quickly and create dashboards that visually visualize system health and performance metrics, making it easier to spot trends and potential problems. By leveraging observability data, you can enable proactive issue resolution. Use the insights gained from monitoring to identify and resolve issues before they impact users, continuously improving your system's performance and reliability. Investing in monitoring and observability practices ensures that you have the visibility and tools needed to maintain a resilient and efficient microservices architecture. In summary, technical best practices are essential for building a successful microservices architecture. Begin with clear architectural vision, provides a strong, will provide you with a strong foundation for your microservices. Implementing effective testing strategies ensures reliability, stability, while investing in monitoring and observability. helps maintain system health and performance by incorporating these best practices. You can navigate the complexities of microservices and create a robust, scalable and efficient architecture. Now, having covered the technical best practices, let's now focus on process, on processes and tooling that can enhance your microservices implementation. In this section, we'll explore three key strategies, leveraging automation and infrastructure as code, utilizing containerization orchestration, and utilizing appropriate tools and techniques. These processes and tools are essential for streamlining operations, ensuring consistency and maximizing the efficiency of your microservices architecture. First, let's discuss leveraging automation and infrastructure as code. Automation and infrastructure as code, or IAC, are crucial for, for ensuring consistent and reliable microservices environments. By automating infrastructure, provisioning, using tools like Terraform, Azure Resource Manager, or ARM, BICEP templates, or AWS CloudFormation. You can define and manage your infrastructure declaratively. This approach ensures that your infrastructure is consistent across all environments and reduces manual configuration errors. Next, streamline deployments using CICD tools like Azure DevOps. GitHub actions or Jenkins. Automate your deployment processes. and this will reduce manual errors, increase reliability and allow for faster iterations. Automation and IAC provide consistency and repeatability across development, testing and production environments, ensuring that your microservice operates reliably and without configurational drift. By leveraging these processes and tools, you can enhance your efficiency and reliability of your microservices. Next, let's explore utilizing containerization and orchestration. Containerization ensures consistency and portability across environments, different environments. By containerizing services using Docker, you can package microservices with all their dependencies, ensuring they run consistently, regardless of environment. For managing and orchestrating these containers, Kubernetes is a powerful tool. Whether you use AKS, EKS, or GKE, Kubernetes ensures your microservices are scalable, highly available, and efficiently managed. Additionally, serverless platforms like Azure Container Apps, AWS Fargate, or Google Cloud Run offer serverless options that reduce operational overhead while providing The benefits of containerized nation and orchestration by utilizing containerization orchestration, you can improve the scalability and portability. and manageability of your microservice architecture. Finally, we have the importance of utilizing appropriate tools and technologies. Selecting the right stack is essential. Choose technologies that align with your team's expertise and project needs, ensuring that they are compatible and can integrate seamlessly. Leveraging cloud services can significantly reduce operational burdens. cloud native services Offer scalability, reliability, and ease of management, allowing your teams to focus on developing features rather than managing infrastructure. Implementing observability tools is crucial for monitoring and debugging microservices. Tools like open telemetry and, or Jagger provide distributed tracing capabilities, ensuring you gain insights into how. Request flow through your system and identify potential bottlenecks. By utilizing tools and techniques, you can create a robust, scalable, and efficient microservice architecture that meets your project's demands and aligns with your team's strengths. One last thing I want to cover before wrapping up is a quick synopsis of the four main architectural styles I brought up at the beginning, and a quick comment about when to use one over the other. When considering architectural styles, it's important to understand the different strengths and weaknesses of each. let's take a quick look into this comparison, comparison matrix. Monolithic architectures are generally simpler to and faster for, smaller projects, but they have limited scalability and fault isolation. Maintenance becomes complex as the application grows. In tier architectures offer moderate scalability and fault isolation by separating concerns into different layers. It's suitable for medium to large applications with clear ties but becomes unnecessary complex. Modular monolith architectures improve scalability and fault isolation by organizing the application into well defined modules. This approach is faster for meeting complexity projects and easier to maintain. And microservices excel in scalability, fault isolation, and deployment speed for large, complex projects. However, they require skilled teams and can be highly complex to manage. To provide a clearer perspective, let's look at real world examples of where each architectural style is commonly used and why it makes sense in those contexts. Monolithic architectures are often used by early stage startups due to their simplicity and quick development speed. For example, a startup developing a basic e commerce platform might use a monolithic approach to get to the market quickly. N tier architectures are well suited for large enterprises with complex business logic and multiple user interfaces. For instance, a banking scenario our banking, solution might use a, an interior architecture to separate the user interface, business logic and data access layers, insurance, scalability and maintainability medium sized businesses, with growing complexity and might benefit from a modular. architecture. An example is an online retail company with separate modules for inventory management, order processing, and customer service. This approach allows them to maintain a single deployable unit while managing complexity. Now, large tech companies with complex scalable systems often use microservices. For instance, Netflix uses a microservice architecture to handle the immense load and complexity of delivering streaming services to millions of users worldwide. This approach allows for independent scalability and fault isolation. Now, these real world examples are just examples. They are, there are many situations where any of these architectures might be a good fit. The importance is to scrutinize your organization's needs and determine the correct architectural style for each particular solution. Not one's fits all. And just because you use one architectural style for one solution doesn't mean you always have to, or should, use the same architectural style for other projects.