Tag: Microservices Architecture

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Understanding Cloud-Native Collaboration and DevOps Culture for the New Engineer

As a new engineer, understanding cloud-native collaboration and DevOps culture is important for several reasons.

First, it is essential for building and deploying cloud-native applications. These practices emphasize collaboration and communication between teams such as development, operations, and security, and aim to streamline the development and deployment process. By understanding how they work, you can build, deploy, and manage cloud-native applications more effectively.

Second, they allow for faster time-to-market. By promoting collaboration and communication between teams, development and deployment can be sped up, leading to faster time-to-market.

Third, they promote better quality of the applications. By promoting collaboration and communication between teams, more thorough testing and debugging can be done, resulting in better quality of the application.

Fourth, they allow for better scalability. By promoting collaboration and communication between teams, resources can be allocated and scaled up or down as needed, without incurring additional costs.

In summary, understanding cloud-native collaboration and DevOps culture is important because it is essential for building and deploying cloud-native applications, allows for faster time-to-market, promotes better quality of the applications, and allows for better scalability. It is a powerful tool for building and deploying applications in a cloud environment and is essential for any engineer working in the field today.

Learning Materials

Here’s a list to get you started learning about cloud-native collaboration and DevOps culture. Note that some of these links may not be free and may require a subscription or payment. I receive no affiliate payments for these links.

Beginner:

Intermediate:

Advanced:

Videos to Watch

Cloud Native DevOps Explained

This video outlines the steps for migrating an application to a cloud-native approach, including breaking it into a pipeline, building and packaging components, running tests, and scanning for vulnerabilities. It also covers the use of DevOps and continuous delivery, as well as frameworks for test-driven development.

A Possible Learning Path

Hands-on experience: Start by setting up a simple Kubernetes cluster and experimenting with different DevOps tools such as Jenkins, Ansible, and Helm. This can be done by following tutorials and guides, and deploying these tools on a cloud platform like AWS, Azure, or GCP.

Theoretical learning: Once you have a basic understanding of DevOps, you can begin to explore the underlying concepts and technologies such as continuous integration, continuous delivery, and infrastructure as code. This can be done through online resources such as tutorials, courses, and documentation provided by Kubernetes, as well as books and blogs on the topic.

Understanding the principles and best practices: DevOps is an important aspect of a microservices architecture, so it’s important to understand the key principles and best practices of DevOps, such as collaboration, automation, and monitoring.

Joining a community: Joining a community of Kubernetes enthusiasts will help you connect with other people who are learning and working with DevOps for Kubernetes. This can be done through online forums, meetups, and social media groups.

Practice, practice, practice: As with any new technology, the best way to learn is by doing. The more you practice deploying and using DevOps tools in a Kubernetes cluster, the more comfortable and proficient you will become with the technology.

A Note from the Architect

OK, let’s talk about DevOps. So, what is it exactly? Well, DevOps is all about breaking down the barriers between development and operations teams, and promoting a culture of collaboration and communication. The goal is to speed up the software delivery process, improve quality, and increase efficiency.

Now, you might be wondering why we want to practice DevOps. Well, in the past, development and operations teams often worked in silos, which led to a lot of delays and inefficiencies. With DevOps, we’re able to bring those teams together and get everyone working towards the same goal: delivering high-quality software quickly and efficiently.

There are a few key principles of DevOps that we like to follow. One of the most important is automation. By automating as many processes as possible, we’re able to speed up the delivery process and reduce the likelihood of errors. Another key principle is continuous integration and delivery. By integrating code changes frequently and delivering them to production as soon as they’re ready, we’re able to get feedback and make improvements more quickly.

Now, when it comes to cloud native approaches like developing on Kubernetes, they fit really well within DevOps practices. By using containerization and orchestration, we’re able to automate the deployment and scaling of our applications, which helps us move faster and be more efficient.

As an individual team member, you can contribute to the DevOps culture by being open to feedback and suggestions, and by being willing to work collaboratively with other teams. Some good practices for a new engineer or developer to pick up include learning how to use automation tools, getting familiar with containerization and orchestration, and practicing continuous integration and delivery.

You might be wondering how DevOps is related to agile and SRE. Well, DevOps is closely related to agile, as both focus on delivering software quickly and efficiently. SRE, on the other hand, is all about ensuring the reliability and availability of software in production. All these practices come together to make sure the software is delivered fast, reliable and with high availability.

Finally, let me tell you, before DevOps became a common practice, IT departments faced a lot of problems. There were often delays in getting new features or updates to production, and there were also a lot of communication issues between development and operations teams. DevOps helps us to overcome all these problems.

Well, dear reader, we’ve come to the end of our series of blog posts on cloud native technologies and practices, and especially Kubernetes. Well, this won’t be my last post on Kubernetes, but at least as far as it relates to this series. I hope you’ve found the information we’ve covered to be helpful and informative.

Throughout the series, we’ve talked about a lot of different topics, including security, CICD, DevOps, and containerization. These are all critical concepts for anyone working in the cloud, and I want to emphasize that these concepts aren’t just short-lived trends, but tools and ideas that will serve you well for many years of your career.

We’ve covered a lot of ground in these posts, but there’s still so much more to learn about cloud native technologies and practices. As you continue to grow and develop your skills, I hope you’ll keep these concepts in mind and continue to explore the many different ways that they can be applied in your work.

I also want to take a moment to thank you for your time, support, and the conversations we’ve had throughout the series. Your feedback and input have been invaluable in helping to make these posts a success, and I appreciate the time you’ve taken to read and engage with the content.

As you continue your journey in cloud native technologies, keep in mind that it’s a constantly evolving landscape, and there will always be more to learn and explore. But with the concepts and tools we’ve covered in this series, you’ll be well-equipped to navigate this exciting and rapidly changing field.

Thanks again for reading and I hope you enjoyed the series. Let’s continue the conversation and explore even more of this exciting field together!

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Connect with Shawn

Connect with me on LinkedIn. It’s where I’m most active, and it’s the easiest way to connect with me.

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Master Cloud Native Governance: The Essential Guide for New Engineers

As a new engineer, understanding the concept of cloud-native governance is important for several reasons.

First, it is a key component of cloud native application development. It uses governance tools and technologies that are native to the cloud and designed to work seamlessly with cloud-native applications. This allows for better deployment and management of cloud-native applications.

Second, cloud-native governance ensures compliance and security. It ensures that the application and infrastructure meet compliance requirements and are protected from threats.

Third, it promotes better collaboration and DevOps culture. Different teams and developers can work together on the same application, and the organization’s policies and standards are followed.

Fourth, it allows for better cost management. Resources can be monitored and controlled, and the organization is not overspending on the cloud.

In summary, understanding the concept of cloud-native governance is important for any engineer working in the field today. It is a powerful tool for building and deploying applications in a cloud environment.

Learning Materials

Here’s a list to get you started learning about cloud-native governance. Note that some of these links may not be free and may require a subscription or payment. I receive no affiliate payments for these links.

Beginner:

Intermediate:

Advanced:

A Possible Learning Path

Hands-on experience: Start by setting up a simple Kubernetes cluster and experimenting with different governance tools such as Open Policy Agent (OPA), Kubernetes Policy Controller, and Kube-bench. This can be done by following tutorials and guides, and deploying these tools on a cloud platform like AWS, Azure, or GCP.

Theoretical learning: Once you have a basic understanding of governance, you can begin to explore the underlying concepts and technologies such as Kubernetes role-based access control (RBAC), Namespaces, and NetworkPolicies. This can be done through online resources such as tutorials, courses, and documentation provided by Kubernetes, as well as books and blogs on the topic.

Understanding the principles and best practices: Governance is an important aspect of a microservices architecture, so it’s important to understand the key principles and best practices of governance such as security, compliance, and auditing.

Joining a community: Joining a community of Kubernetes enthusiasts will help you connect with other people who are learning and working with governance for Kubernetes. This can be done through online forums, meetups, and social media groups.

Practice, practice, practice: As with any new technology, the best way to learn is by doing. The more you practice deploying and using governance tools in a Kubernetes cluster, the more comfortable and proficient you will become with the technology.

A Note from the Architect

Ok, let’s talk about cloud native governance. So, why do we need to practice it? Well, as we all know, the cloud is a constantly evolving landscape and it can be pretty overwhelming to keep up with all the new technologies and best practices. That’s where governance comes in – it’s all about making sure we’re using the cloud in a consistent and efficient way across our organization.

So what exactly is cloud native governance? It’s all about using policies and tools to manage the resources in our cloud environment. This includes things like setting up guidelines for how our teams use the cloud, automating tasks to keep our environment in check, and monitoring for any potential issues.

Now, you might be wondering why cloud native governance was created. Well, as organizations started moving more and more of their workloads to the cloud, they realized they needed a way to keep everything in check. Without governance in place, it can be easy for teams to create resources in an ad-hoc way, which can lead to wasted resources, security vulnerabilities, and inconsistencies in how the cloud is being used.

Now, let’s talk about the major tools on Kubernetes that help with cloud native governance. One of the most popular is Kubernetes itself, which provides a way to manage and scale containerized applications. Another popular tool is Helm, which helps with managing and deploying Kubernetes resources. There’s also Kustomize, which helps with creating and managing customized resources. And finally, there’s Open Policy Agent (OPA) which allows to define and enforce policies on k8s resources.

It’s important to note that governance is similar to security, and it requires a continuous practice. Governance policies and tools need to be regularly reviewed and updated to ensure they are still effective and aligned with the organization’s goals and requirements. It’s all about making sure we’re using the cloud in the best way possible.

Be sure to reach out on LinkedIn if you have any questions.

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Connect with me on LinkedIn. It’s where I’m most active, and it’s the easiest way to connect with me.

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Understanding Cloud-Native Observability for Kubernetes: Principles, Best Practices, and Tools

As a new engineer, understanding cloud-native observability is important for several reasons.

First, it is a key component of cloud-native application development. It uses monitoring and observability tools native to the cloud, designed to work seamlessly with cloud-native applications. This helps build, deploy, and manage applications more effectively.

Second, cloud-native observability provides better visibility and troubleshooting. It provides a comprehensive view of the application and its underlying infrastructure, helping to identify and troubleshoot issues quickly.

Third, it promotes better collaboration and DevOps culture. By providing insights into the performance and behavior of the application, it becomes easier for different teams and developers to work together.

Fourth, it allows for better security. By using monitoring and observability tools native to the cloud, it enables quick detection and response to security threats.

In summary, understanding cloud-native observability is important for building and deploying applications in a cloud environment. It is a key component of cloud-native application development, provides better visibility and troubleshooting, promotes better collaboration and DevOps culture, and allows for better security. It is essential for any engineer working in the field today.

Learning Materials

Here’s a list to get you started learning about cloud-native observability. Note that some of these links may not be free and may require a subscription or payment. I receive no affiliate payments for these links.

Beginner:

Intermediate:

Advanced:

Videos to Watch

LF Live Webinar: Kubernetes Observability with OpenTelemetry and Beyond

Martin Fuentes and Cedric, product managers at Instantana, discussed Kubernetes resource management and how to observe Kubernetes workloads. They explained how CPU and memory are the most important resources managed by Kubernetes, and how requests and limits can be configured for containers. They also discussed the different types of scaling, such as horizontal and vertical scaling, and how HPA (Horizontal Pod Autoscaling) can be used to automatically scale containers.

A Possible Learning Path

Hands-on experience: Start by setting up a simple Kubernetes cluster and experimenting with different observability tools such as Prometheus, Grafana, and Elasticsearch. This can be done by following tutorials and guides, and deploying these tools on a cloud platform like AWS, Azure, or GCP.

Theoretical learning: Once you have a basic understanding of observability, you can begin to explore the underlying concepts and technologies such as Kubernetes metrics, logging, and tracing. This can be done through online resources such as tutorials, courses, and documentation provided by Kubernetes, as well as books and blogs on the topic.

Understanding the principles and best practices: Observability is an important aspect of a microservices architecture, so it’s important to understand the key principles and best practices of observability, such as metrics collection, log aggregation, and tracing.

Joining a community: Joining a community of Kubernetes enthusiasts will help you connect with other people who are learning and working with observability for Kubernetes. This can be done through online forums, meetups, and social media groups.

Practice, practice, practice: As with any new technology, the best way to learn is by doing. The more you practice deploying and using observability tools in a Kubernetes cluster, the more comfortable and proficient you will become with the technology.

A Note from the Architect

Ok, let’s talk about observability. It’s a pretty important concept to understand, especially if you’re working in a DevOps culture. Even if you’re not, it’s a great practice to start using when you think about building out your solutions.

So, what is observability? Essentially, it’s the ability to understand the internal state of a system by observing its external behavior. This means that you can use metrics, traces, and logs to understand what’s happening inside your system, even if you don’t have direct access to the internal state.

There are three main principles of observability:

  1. Measurability: The ability to collect and aggregate data from your system. This includes metrics, traces, and logs.
  2. Understandability: The ability to understand the data that you collect. This includes using visualization tools and dashboards to make sense of the data.
  3. Explainability: The ability to explain the data that you collect. This includes using tracing and logging to understand the cause of issues.

So, how does observability fit into a DevOps culture? Well, in a DevOps culture, you’re focused on smooth, but rapid development and deployment. This means that you need to be able to quickly understand and fix issues that arise in your system. Observability gives you the tools to do that, by providing a way to understand the internal state of your system.

Now, let’s talk about some tools that can help with observability on Kubernetes. Here are a couple of popular options:

  1. Prometheus: Prometheus is an open-source metrics collection and monitoring tool. It’s great for use cases where you need to collect and aggregate metrics from your system.
  2. Jaeger: Jaeger is an open-source tracing tool. It’s great for use cases where you need to understand the cause of issues in your system.

Both of these options are great choices for different types of observability, and they’re both built specifically to work with Kubernetes.

So, what are the consequences of not practicing observability? Well, if you’re not practicing observability, you’ll have a hard time understanding what’s happening inside your system. This means that you won’t be able to quickly fix issues that arise, which can lead to downtime and lost revenue. Additionally, you won’t be able to understand the performance of your system, which can lead to poor performance and a bad user experience. So, observability is a crucial practice to ensure the smooth running of your system.

So, that’s the basics of observability. It’s a powerful tool that can help you build robust and scalable solutions on Kubernetes. If you have any more questions, feel free to ask!

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Connect with me on LinkedIn. It’s where I’m most active, and it’s the easiest way to connect with me.

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Learn the Benefits of Logging and Monitoring in Cloud-Native Environments

As a new engineer, understanding the concept of logging and monitoring is important for several reasons.

First, logging and monitoring are key components of cloud-native application development. They involve collecting, analyzing, and visualizing data from an application and its underlying infrastructure. By understanding how logging and monitoring work, you can build, deploy, and manage cloud-native applications more effectively.

Second, logging and monitoring provide better visibility and troubleshooting. By collecting, analyzing, and visualizing data, you can understand the behavior and performance of the application, identify problems, and troubleshoot issues quickly.

Third, logging and monitoring promote better collaboration and DevOps culture. By providing insights into the performance and behavior of the application, it becomes easier for different teams and developers to work together on the same application.

Fourth, logging and monitoring allow for better security. By collecting and analyzing data from different sources, you can detect and respond to security threats quickly.

In summary, as a new engineer, understanding the concept of logging and monitoring is important because it is a key component of cloud-native application development, provides better visibility and troubleshooting, promotes better collaboration and DevOps culture, and allows for better security. It is a powerful tool for building and deploying applications in a cloud environment and is essential for any engineer working in the field today.

Learning Materials

Here’s a list to get you started learning about logging and monitoring. Note that some of these links may not be free and may require a subscription or payment. I receive no affiliate payments for these links.

Beginner:

Intermediate:

Advanced:

Videos to Watch

Monitoring, Logging, And Alerting In Kubernetes

This video provides an overview of the different components of a self-managed monitoring and logging stack for Kubernetes clusters, such as Prometheus, Node Exporters, Push Gateway, and Alert Manager. Robusta is also mentioned as a platform for Kubernetes notifications, troubleshooting, and automation.

A Possible Learning Path

Hands-on experience: Start by setting up a simple Kubernetes cluster and experimenting with different logging and monitoring tools such as Prometheus, Grafana, and Elasticsearch. This can be done by following tutorials and guides, and deploying these tools on a cloud platform like AWS, Azure, or GCP.

Theoretical learning: Once you have a basic understanding of logging and monitoring, you can begin to explore the underlying concepts and technologies such as Kubernetes API objects, metrics, and alerting. This can be done through online resources such as tutorials, courses, and documentation provided by Kubernetes, as well as books and blogs on the topic.

Understanding the principles and best practices: Logging and monitoring are important aspects of a microservices architecture, so it’s important to understand the key principles and best practices of logging and monitoring such as observability, log retention, and monitoring dashboards.

Joining a community: Joining a community of Kubernetes enthusiasts will help you connect with other people who are learning and working with logging and monitoring for Kubernetes. This can be done through online forums, meetups, and social media groups.

Practice, practice, practice: As with any new technology, the best way to learn is by doing. The more you practice deploying and using logging and monitoring tools in a Kubernetes cluster, the more comfortable and proficient you will become with the technology.

A Note from the Architect

Believe it or not, in my early days of development a rarely created logs in production. I’m not sure if it was “bro science,” but many of us were of the opinion that writing logs would slow down our applications. It was almost as though many of us believed you could drive faster if you kept your eyes closed.

Logging and monitoring are like a detective and a spy for your application. They help you to understand what’s happening inside your application and detect any issues that might arise.

In a cloud-native environment, logging and monitoring are essential for understanding the health and performance of your application. Logging is the process of capturing information about what’s happening inside your application, such as error messages or performance metrics. Some of the common tools used for logging in cloud-native environments are Elasticsearch, Logstash, and Kibana (ELK stack), Fluentd, and Graylog. A typical log file might look like this:

[2022-11-01T09:15:00Z] [INFO] Server started on port 80
[2022-11-01T09:15:02Z] [ERROR] Failed to connect to database
[2022-11-01T09:15:03Z] [INFO] Successfully connected to database

Monitoring is the process of collecting and analyzing data about the performance and health of your application. Some common monitoring tools used in cloud-native environments are Prometheus, Grafana, and InfluxDB. These tools allow you to collect metrics about your application, such as CPU usage, memory usage, and network traffic. They also provide visualizations of the metrics, which makes it easy to understand what’s happening inside your application.

In Kubernetes, logging and monitoring are built into the platform and can be easily configured with Kubernetes resources. This allows you to collect and analyze data about your applications and systems.

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Understanding Cloud-Native Storage for Kubernetes: What It Is and How It Works

As a new engineer, understanding the concept of cloud-native storage is important for several reasons.

First, it is a key component of cloud native application development. It is the practice of using storage solutions that are native to the cloud and designed to work seamlessly with cloud-native applications. By understanding how cloud-native storage works, you will be able to build, deploy, and manage cloud-native applications more effectively.

Second, it allows for better scalability and cost efficiency. By using storage solutions that are native to the cloud, resources can be automatically allocated and scaled up or down as needed, without incurring additional costs.

Third, it promotes better collaboration and DevOps culture. By using storage solutions that are native to the cloud, it becomes easier for different teams and developers to work together on the same application.

Fourth, it allows for better data availability. By using storage solutions that are native to the cloud, data is stored in multiple locations and can be accessed from any location.

In summary, understanding the concept of cloud-native storage is important because it is a key component of cloud native application development, allows for better scalability and cost efficiency, promotes better collaboration and DevOps culture, and allows for better data availability. It is a powerful tool for building and deploying applications in a cloud environment and is essential for any engineer working in the field today.

Learning Materials

Here’s a list to get you started learning about cloud-native storage. Note that some of these links may not be free and may require a subscription or payment. I receive no affiliate payments for these links.

Beginner:

Intermediate:

Advanced:

Videos to Watch

CNCF Webinar – Introduction to Cloud Native Storage

This webinar provides an overview of the evolving cloud native storage requirements and data architecture, discussing the need for layered services that can be seamlessly bound for the user experience. It explores the extensible, open-source approach of abstractions and plugins that give users the choice to select the storage technologies that fit their needs. It also looks at the importance of persistent volumes for containers, allowing for the flexibility and performance needed for stateful workloads.

A Possible Learning Path

Hands-on experience: Start by setting up a simple Kubernetes cluster and experimenting with different cloud-native storage options such as Kubernetes Persistent Volumes (PVs), Persistent Volume Claims (PVCs), and StatefulSets. This can be done by following tutorials and guides, and deploying these options on a cloud platform like AWS, Azure, or GCP.

Theoretical learning: Once you have a basic understanding of cloud-native storage, you can begin to explore the underlying concepts and technologies such as Kubernetes storage classes, storage provisioners, and storage backends. This can be done through online resources such as tutorials, courses, and documentation provided by Kubernetes and storage providers, as well as books and blogs on the topic.

Understanding the principles and best practices: Cloud-native storage is an important aspect of a microservices architecture, so it’s important to understand the key principles and best practices, such as data replication, data durability, and data accessibility.

Joining a community: Connect with other people who are learning and working with cloud-native storage for Kubernetes by joining online forums, meetups, and social media groups.

Practice, practice, practice: The best way to learn is by doing. The more you practice deploying and using cloud-native storage options in a Kubernetes cluster, the more comfortable and proficient you will become with the technology.

A Note from the Architect

Hey there! I’m glad you’re interested in learning more about cloud native storage. It’s a pretty important concept to understand, especially if you’re working with Kubernetes.

So, what is cloud native storage? Essentially, it’s a type of storage that is built specifically for use in cloud environments. This means that it’s designed to work seamlessly with cloud technologies like Kubernetes, and can handle the unique challenges that come with a cloud environment, like scalability and high availability.

Why is it necessary for certain solutions built on Kubernetes? Well, Kubernetes is a powerful tool for managing containerized applications, but it doesn’t come with its own storage solution. So, if you’re building a solution on Kubernetes, you’ll need to use a separate storage solution that’s compatible with it. That’s where cloud native storage comes in – it’s designed to work with Kubernetes, so it’s the perfect match.

Now, let’s talk about how it works. Essentially, cloud native storage solutions provide a way to store and access data that’s running on Kubernetes. They do this by creating a “volume” that can be mounted to a Kubernetes pod, which allows the pod to access the data stored in the volume. This way, you can store data in a persistent way, even if the pod is deleted or recreated.

Here are a couple of popular Kubernetes cloud native storage options and the types of solutions they’re used for:

  1. Rook: Rook is an open-source storage solution for Kubernetes. It’s great for use cases where you need to store data in a distributed way, like a big data analytics solution or a large-scale data storage system.
  2. GlusterFS: GlusterFS is another open-source storage solution for Kubernetes. It’s great for use cases where you need to store data in a highly available way, like a web application or a database.

Both of these options are great choices for different types of solutions, and they’re both built specifically to work with Kubernetes.

So, that’s the basics of cloud native storage. It’s a powerful tool that can help you build robust and scalable solutions on Kubernetes. If you have any more questions, feel free to ask on LinkedIn!

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Unlocking the Power of Service Discovery in Kubernetes

As a new engineer, understanding the concept of service discovery is important for several reasons.

First, it is a key component of microservices architecture. Service discovery allows services to find and communicate with each other, regardless of their location or IP address. This makes it easier to build, deploy, and manage microservices-based applications.

Second, service discovery enables greater scalability and flexibility. Services can be added or removed without affecting the rest of the system, and new services can be introduced without changing existing code.

Third, service discovery facilitates better collaboration and DevOps culture. By making it easy for services to find and communicate with each other, different teams and developers can work together on the same application.

Fourth, service discovery allows for better resilience. It enables the system to automatically route traffic to healthy instances of a service, even if some instances are unavailable.

In summary, understanding service discovery is important for any engineer working in the field today. It is a powerful tool for building and deploying applications in a microservices environment and is essential for achieving greater scalability, flexibility, collaboration, and resilience.

Learning Materials

Here’s a list to get you started learning about Service Discovery. Note that some of these links may not be free and may require a subscription or payment. I receive no affiliate payments for these links.

Beginner:

Intermediate:

Advanced:

Videos to Watch

What is Service Discovery?

Moving from a monolith to a Cloud-based Microservices Architecture presents several challenges, such as Service Discovery, which involves locating resources on a network and keeping a Service Registry up to date. Service Discovery can be categorized by WHERE it happens (Client Side or Server Side) and HOW it is maintained (Self Registration or Third-party Registration). Each approach has its own pros and cons, and further complexities such as Service Mesh can be explored in further detail.

Possible Learning Path (Service Discovery for Kubernetes)

Hands-on experience: Start by setting up a simple Kubernetes cluster and experimenting with different service discovery mechanisms such as Kubernetes Services, DNS, and Load Balancing. This can be done by following tutorials and guides and deploying these services on a cloud platform like AWS, Azure, or GCP.

Theoretical learning: Once you have a basic understanding of service discovery, you can begin to explore the underlying concepts and technologies such as Kubernetes Services, DNS, and Load Balancing. This can be done through online resources such as tutorials, courses, and documentation provided by Kubernetes, as well as books and blogs on the topic.

Understanding the principles and best practices: Service discovery is an important aspect of a microservices architecture, so it’s important to understand the key principles and best practices of service discovery such as service registration, service discovery, and service resolution.

Joining a community: Joining a community of Kubernetes enthusiasts will help you connect with other people who are learning and working with service discovery for Kubernetes. This can be done through online forums, meetups, and social media groups.

Practice, practice, practice: As with any new technology, the best way to learn is by doing. The more you practice deploying and using service discovery mechanisms in a Kubernetes cluster, the more comfortable and proficient you will become with the technology.

A Note from the Architect

So, you know how in a microservice architecture, we have all these different services that need to talk to each other? Well, service discovery is kind of like a phone book for those services (this is DNS). It helps them find each other and communicate with each other.

In traditional networks, service discovery is often done using a centralized server or load balancer. This means that all the services need to know the IP address or hostname of this central server in order to communicate with other services.

But in Kubernetes, service discovery is built into the platform. Each service gets its own unique IP address and DNS name, and Kubernetes automatically handles routing traffic between them. This means that the services don’t need to know anything about other services except their own name.

And the best part? Kubernetes service discovery is dynamic, which means that it automatically updates when new services are added or removed, so you don’t have to manually update the phone book every time something changes.

But that’s not all, Kubernetes also provides a way to expose your services externally, so that you can access them from outside the cluster, which is very useful for example if you want to access your services from the internet.

So, with service discovery in Kubernetes, you don’t have to worry about keeping track of IP addresses and hostnames, and you don’t have to worry about updating a central server when things change. It’s like having a personal assistant who always knows the latest phone number of your services and also makes sure that they are accessible from anywhere.

Basically, service discovery in Kubernetes provides a way for services to easily find and communicate with each other, and it’s built right into the platform. It’s a game-changer for managing and scaling a microservice architecture.

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Connect with me on LinkedIn. It’s where I’m most active, and it’s the easiest way to connect with me.

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What is Load Balancing, and How Can it Help Your Cloud-Native Applications?

As a new engineer, understanding the concept of load balancing is important for several reasons.

First, it is a key component of cloud native application development. It is the process of distributing incoming network traffic across multiple servers to ensure that no single server is overwhelmed. By understanding how it works, you will be able to build, deploy, and manage cloud-native applications more effectively.

Second, load balancing allows for greater scalability and availability. By distributing traffic across multiple servers, it ensures that the system can handle a large number of requests and can continue to function even if one server goes down. This makes it easy to handle the increasing demand for more computing power and storage.

Third, it facilitates better collaboration and DevOps culture. By making it easy to distribute traffic across multiple servers, it becomes easier for different teams and developers to work together on the same application.

Fourth, it enhances security, by distributing the traffic across multiple servers, it makes it harder for attackers to target a single point of failure.

In summary, as a new engineer, understanding the concept of load balancing is important because it is a key component of cloud native application development, allows for greater scalability and availability, better collaboration and DevOps culture, and better security. It is a powerful tool for building and deploying applications in a cloud environment and is essential for any engineer working in the field today.

Learning Materials

Here’s a list to get you started learning about load balancing. Note that some of these links may not be free and may require a subscription or payment. I receive no affiliate payments for these links.

Beginner:

Intermediate:

Advanced:

Videos to Watch

How load balancing and service discovery works in Kubernetes

Kubernetes provides a range of features to enable applications to communicate with each other, including service discovery, load balancing, DNS, and port management. These features are enabled through the use of namespaces, labels, services, and Linux networking features such as bridges and IP tables.

A Possible Learning Path

Hands-on experience: Start by setting up a simple Kubernetes cluster and experimenting with different load balancing mechanisms such as Kubernetes Services, Ingress, and External Load Balancers. This can be done by following tutorials and guides and deploying these services on a cloud platform like AWS, Azure, or GCP.

Theoretical learning: Once you have a basic understanding of load balancing, you can begin to explore the underlying concepts and technologies such as Kubernetes Services, Ingress, and External Load Balancers. This can be done through online resources such as tutorials, courses, and documentation provided by Kubernetes, as well as books and blogs on the topic.

Understanding the principles and best practices: Load balancing is an important aspect of a microservices architecture, so it’s important to understand the key principles and best practices of load balancing such as traffic distribution, service availability, and fault tolerance.

Joining a community: Joining a community of Kubernetes enthusiasts will help you connect with other people who are learning and working with load balancing for Kubernetes. This can be done through online forums, meetups, and social media groups.

Practice, practice, practice: As with any new technology, the best way to learn is by doing. The more you practice deploying and using load balancing mechanisms in a Kubernetes cluster, the more comfortable and proficient you will become with the technology.

A Note from the Architect

A load balancer is like an air traffic controller for your network. It ensures that traffic is evenly distributed across all servers, so that no single server becomes overwhelmed and crashes. This is especially important when there is a lot of incoming traffic or a large number of users accessing the application.

In traditional networks, load balancers are typically dedicated hardware devices that sit in front of the servers and manage the traffic. However, in cloud-native networks, load balancers are usually software-based and run as part of the infrastructure. This is where Kubernetes comes into play.

Kubernetes has a built-in load balancer that can be easily configured with the Kubernetes resources. It automatically distributes traffic to the services running in the cluster. This is a great advantage, as it allows for more flexibility, scalability, availability, and the ability to handle failover automatically.

Another benefit of using a load balancer in a cloud-native network is that it makes it possible to expose services to the outside world. This means that services can be accessed from anywhere, which is especially useful if you want to access them from the internet.

Using a load balancer in a cloud-native network has many advantages, such as increased availability, scalability, and flexibility, as well as the ability to handle failover automatically. Plus, it’s like having a superhero that ensures traffic is evenly distributed and users are happy.

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Understanding Microservices Architecture: Key Concepts, Learning Resources & More

As a new engineer, understanding the concept of microservices architecture is important for several reasons.

First, it is a key component of cloud native application development. It allows for faster development, easier scaling, and more flexible deployment options. By understanding how microservices work, you will be able to build, deploy, and manage cloud-native applications more effectively.

Second, microservices architecture promotes modularity, which allows for greater flexibility, scalability, and maintainability of the system. Each microservice can be developed, deployed, and scaled independently, making it easier to handle increasing demand.

Third, microservices architecture facilitates better collaboration and DevOps culture. By breaking down the application into smaller, independent units, different teams and developers can work together on the same application.

Fourth, microservices architecture allows for greater resilience. By isolating the failure in one service, it will not impact the entire system.

In summary, understanding the concept of microservices architecture is essential for any engineer working in the field today. It is a powerful tool for building and deploying applications in a cloud environment and provides benefits such as faster development, easier scaling, more flexible deployment options, greater flexibility, scalability, and maintainability, better collaboration and DevOps culture, and greater resilience.

Learning Materials

Here’s a list to get you started learning about Microservices architecture. Note that some of these links may not be free and may require a subscription or payment. I receive no affiliate payments for these links.

Beginner:

Intermediate:

Advanced:

Videos to Watch

Microservices explained – the What, Why and How?

In this video, the Nana explains the concept of microservices architecture and its advantages over monolith architecture. He also discusses best practices for microservices communication, such as using API calls, message brokers, and service meshes. Finally, he mentions the importance of a CI/CD pipeline for deploying microservices.

Possible Learning Path

Hands-on experience: Start by experimenting with building simple microservices using technologies such as Node.js, Spring Boot, or Flask. This can be done by following tutorials and guides and deploying these services on a cloud platform like AWS, Azure, or GCP.

Theoretical learning: Once you have a basic understanding of microservices, you can begin to explore the underlying concepts and technologies. This can be done through online resources such as tutorials, courses, and documentation provided by microservices architecture, as well as books and blogs on the topic.

Understanding the principles and best practices: Microservices architecture is not just about technology; it’s also about principles and best practices. It’s important to understand the key principles and best practices of microservices, such as loose coupling, autonomy, and scalability.

Joining a community: Joining a community of microservices enthusiasts will help you connect with other people who are learning and working with microservices architecture. This can be done through online forums, meetups, and social media groups.

Practice, practice, practice: As with any new technology, the best way to learn is by doing. The more you practice building and deploying microservices, the more comfortable and proficient you will become with the architecture.

A Note from the Architect

I’m not in the camp that thinks monolithic architecture is necessarily bad. However, I believe that, in the long run, microservices have a better chance of success. Are microservices more work? Yes, there is an overhead associated with them, but I think it’s worth it for the added flexibility.

To explain the difference between microservices and traditional monolithic architectures, a monolithic architecture is when all the different parts of an application, such as the user interface, the database, and the backend, are bundled together in one package. This can work well for small projects, but as the project grows and becomes more complex, it can become harder to manage and maintain.

On the other hand, microservice architecture breaks the application down into smaller, individual services. Each service is responsible for a specific task, such as user authentication or payment processing.

The benefits of microservices include the ability to make changes to one service without affecting the others, as well as more flexibility and scalability, since each service can be deployed and scaled independently.

For example, here’s some code in Python that demonstrates a microservice:

from flask import Flask

app = Flask(__name__)

@app.route('/')
def hello_world():
    return 'Hello, World!'

if __name__ == '__main__':
    app.run()

This code is a simple web service that listens for a request to the root URL and returns the string “Hello, World!”.

That doesn’t do much, but it does show how you can quickly create a service. A series of these services working together could create a more robust solution. I won’t dive into the Actor Pattern, but it’s probably the ideal approach to microservices.

Keep in mind, an organization would select microservices over other architectures because they are more flexible, scalable, and easier to maintain as the project grows. Plus, it’s way cooler to say you’re working with microservices than a monolithic architecture. Trust me, it’s like being in a secret club of developers who know how to handle complexity in the best way possible.

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Why Should a New Engineer Learn the Cloud Native Concepts?

As a new engineer, learning cloud native concepts is important for several reasons.

First, cloud computing is becoming increasingly popular and is now the norm for many organizations. Many companies are moving away from traditional on-premises data centers and migrating their infrastructure and applications to the cloud. Knowing how to build, deploy, and manage cloud-native applications will give you a valuable skill set that is in high demand in the job market.

Second, cloud native concepts and technologies are designed to be flexible, scalable, and efficient. They enable faster development and deployment of applications and make it easier to handle the increasing demand for more computing power and storage. By learning these concepts, you will be able to build applications that can handle large amounts of traffic and data and can easily scale up or down as needed.

Third, cloud native concepts and technologies are designed to work well together. They are all part of a larger ecosystem that is designed to make it easy for developers to build, deploy, and manage applications on cloud infrastructure. By learning these concepts, you will be able to take advantage of the full range of cloud-native tools and services, and will be able to create more powerful and efficient applications.

In summary, as a new engineer, learning cloud native concepts will give you a valuable skill set, allow you to build flexible, scalable, and efficient applications, and enable you to take advantage of the full range of cloud-native tools and services. It is an essential skill set for many companies today and will be essential in the future.

What is Cloud Native?

Cloud native is a term used to describe an approach to building, deploying, and running applications on cloud infrastructure. It involves containerization, microservices architecture, and the use of cloud-native tools and services.

Containerization packages software, its dependencies, and configuration files together in a lightweight and portable container, allowing it to run consistently across different environments.

Microservices architecture designs and builds software as a collection of small, independent services that communicate with each other via well-defined APIs. This approach enables faster development, easier scaling, and more flexible deployment options.

Cloud-native tools and services are designed specifically for cloud environments and provide capabilities such as auto-scaling, load balancing, and service discovery. They allow for faster and more efficient deployment and management of applications.

In summary, cloud native is a way of designing, building, and running applications on cloud infrastructure. It leverages containerization and microservices architecture, and utilizes cloud-native tools and services for faster and more efficient deployment and management of applications. As a new engineer, it is important to understand these concepts and how they work together in order to build cloud-native applications.

Learning Materials

Here’s a list to get you started learning about Cloud Native. Note that some of these links may not be free and may require a subscription or payment. I receive no affiliate payments for these links.

Beginner:

Intermediate:

Advanced:

Videos to watch

What is Cloud Native and Why Should I Care?

Wealth Grid is a mid-sized firm that has product and service market fit, but is struggling to shorten its time to value and stay off the front page news. To do this, they must embrace cloud native technologies, but this is not business as usual. With the help of the Cloud Native Computing Foundation, Wealth Grid can learn from their mistakes and use tools and techniques to achieve their goals.

Expert talk: Cloud Native & Serverless • Matt Turner & Eric Johnson • GOTO 2022

Matt Turner and Eric Johnson discuss the importance of Cloud Native Concepts for the new engineer to learn, such as Continuous Integration and Continuous Delivery, and the benefits of testing in production to catch certain classes of bugs.

A Possible Learning Path

Hands-on experience: It is important to start by experimenting with different cloud providers, such as AWS, Azure, and GCP, to understand the basic concepts and services offered by each. This can be done by creating a free account and following tutorials and guides to build and deploy simple applications.

Theoretical learning: Once you have a basic understanding of cloud computing, you can begin to explore cloud native concepts such as containerization, microservices, and service discovery. This can be done through online resources such as tutorials, courses, and documentation provided by cloud providers, as well as books and blogs on the topic.

Joining a community: Joining a community of cloud native enthusiasts will help you connect with other people learning and working with cloud native technology. This can be done through online forums, meetups, and social media groups.

Practice, practice, practice: As with any new technology, the best way to learn is by doing. The more you practice building and deploying cloud native applications, the more comfortable and proficient you will become with the technology.

Specialize in a specific cloud provider: Cloud providers each have their own set of services and ways of working, so it is beneficial to specialize in one or two providers that align with your business or career goals.

A Note From the Architect

Don’t be intimidated by the volume of information you’ll need to learn to be proficient in cloud-native technologies. Because I have a secret for you from a twenty-five year veteran. There’s little chance you’ll ever be much more than competent. You may be able to master a few of these subject areas, and that’s great if you do, but it’s not necessary if you truly understand one important thing.

I call this important thing, “The Why”.

In each of these articles where I present an important topic from big concepts in cloud-native development I will give you my opinion based on personal experience as to why you should consider using this technology, what are other possibilities, and what are the trade offs.

I believe that ‘The Why’ is one of the most important parts of a technology consideration. So what is the, “why,” of Cloud Native? In my opinion, it’s the ability to develop and deliver solutions on their built-to-fit platform. Even though there’s still a huge market for large systems like SAP, Microsoft Dynamics, and Oracle, the future belongs to value created solutions running on platforms that best fit their need.

I’m sure some people are wondering if everything really needs to be containerized. No, there are plenty of alternative options for running your workloads that don’t involve containers.

As a developer, I have come across several alternatives to cloud native technologies. One alternative is using virtual machines (VMs) instead of containers. VMs offer a higher level of isolation and security, but they also have a larger footprint and are less portable. Another alternative is using on-premises infrastructure, which provides greater control over data and security, but also comes with higher costs and maintenance responsibilities.

Another alternative is using a platform-as-a-service (PaaS) instead of containers. PaaS provides a higher level of abstraction and can simplify the deployment process, but it also limits the level of control and customization that you have over the infrastructure.

It’s important to note that, while these alternatives can be viable options depending on the specific use case, they often trade off some of the benefits of cloud native technologies such as scalability, flexibility, and cost-efficiency. Ultimately, it’s important to weigh the tradeoffs and choose the solution that best aligns with the needs of your project and organization.

What I hope to accomplish with this series is to open your eyes to the possibilities of what Cloud Native has to offer.

Connect with Shawn
Connect with Shawn

Connect with me on LinkedIn. It’s where I’m most active, and it’s the easiest way to connect with me.

Shawn’s LinkedIn