GitOps Explained — Principles, Deployment, and Best Practices
In the ever-evolving landscape of software development, efficient deployment practices have become crucial to stay ahead of the competition and deliver high-quality products. GitOps has emerged as a cutting-edge methodology, fostering collaboration, scalability, and reliability. As it leverages version control systems like Git, GitOps enables teams to maintain a declarative representation of the desired system state, streamlining the deployment process and ensuring consistency across different environments. From understanding the core components of GitOps to implementing the most effective deployment strategies, this article aims to equip readers with the knowledge and tools to excel in the dynamic world of modern software deployment. So, let’s get started! What is GitOps? — Core Components to Excel GitOps is an advanced software deployment paradigm that revolves around the principle of “desired state” and Git version control system. The core concept involves describing the desired configuration and state of a system declaratively and storing it in a Git repository. All changes to the system, whether they pertain to application code or infrastructure settings, are represented as Git commits in the repository. The Git repository serves as the single source of truth, reflecting the actual state of the system. CI/CD pipelines, tightly integrated with the Git repository, automatically detect changes and reconcile the system state with the desired state defined in Git. The entire deployment process is thus version-controlled and auditable. CI/CD (Continuous Integration and Continuous Deployment) Continuous Integration and Continuous Deployment (CI/CD) is a fundamental aspect of GitOps. CI/CD pipelines automate the process of building, testing, and deploying code changes to production or staging environments. By integrating version control systems with CI/CD pipelines, GitOps ensures that every change made to the codebase goes through automated testing and verification before being deployed, enhancing the overall quality and reliability of the software. IaC (Infrastructure as Code) Infrastructure as Code (IaC) is a key principle in GitOps. It involves managing infrastructure configurations in a version-controlled manner, just like application code. As it describes the desired infrastructure state in code, GitOps allows teams to automate the provisioning of infrastructure resources. This approach eliminates manual setup and reduces the risk of configuration drift, leading to more predictable and reproducible deployments. MRs and PRs (Merge Requests and Pull Requests) Merge Requests (MRs) in GitLab or Pull Requests (PRs) in GitHub play a crucial role in the GitOps workflow. They serve as collaboration platforms for code reviews and discussions among team members. Before changes are applied, they undergo thorough review, testing, and validation through MRs or PRs, ensuring that only well-tested and approved changes are merged into the main codebase. Principles of GitOps Declarative System The declarative system is a fundamental concept in GitOps. Instead of defining the sequence of actions to achieve a particular state, GitOps focuses on describing the desired end state of the system. The Git repository serves as the single source of truth, containing all the necessary configurations to achieve that state. As a result, GitOps ensures that the system converges to the desired state automatically, making it easier to manage and audit changes. System State Captured in a Git Repository GitOps relies on maintaining a Git repository as the central repository for the desired system state. All changes, whether related to infrastructure or application code, are committed and version-controlled in the repository. This approach provides a historical record of changes, enabling teams to track the evolution of the system and easily roll back to a previous known state if needed. Automatic Deployment With GitOps, deployments are automated based on changes to the Git repository. Whenever a new commit is pushed to the repository, the system automatically applies the changes to the target environment. This automation reduces manual intervention, minimizes the risk of human errors during deployments, and ensures a consistent and reliable deployment process. GitOps Deployment Strategies Rolling Strategy The Rolling Strategy is a deployment approach where new changes are incrementally rolled out to the target environment while the existing version remains operational. This gradual deployment minimizes downtime and allows for easy rollbacks if issues arise during the deployment process. Canary Deployment Canary Deployment is a technique where a small subset of users or servers receives the new changes while the majority continues to use the existing version. This approach helps validate the changes in a real-world environment with reduced risk. If the canary group shows positive results, the changes are gradually rolled out to the entire system, ensuring a smooth transition. Blue-Green Deployment Blue-Green Deployment involves maintaining two identical environments—blue and green. The current version of the application runs in one environment (e.g., blue), while the new version is deployed to the other (e.g., green). Once the green environment is thoroughly tested and verified, traffic is switched from the blue to the green environment, making it the new production version. This approach enables seamless rollbacks if issues are discovered during the deployment. A/B Deployment A/B Deployment, also known as Feature Toggling, allows for deploying multiple versions of a feature simultaneously. This approach enables teams to test different implementations or user experiences and analyze their performance and impact on users. By gradually exposing different features to different user groups, A/B Deployment allows for data-driven decision-making and fine-tuning of features before full rollout. GitOps Best Practices Avoid Mixed Environments Maintain clear separation between development, staging, and production environments. Avoid mixing different configurations or states, as this can lead to unpredictable outcomes and make it challenging to identify the root cause of issues. Separating environments ensures that changes are tested thoroughly in isolated environments before reaching production. Leverage the Request Discussion Encourage collaboration and knowledge sharing among team members by using MRs or PRs as platforms for discussions. This ensures that all changes are thoroughly reviewed, tested, and approved by relevant stakeholders before being deployed. Discussions within MRs or PRs provide valuable feedback and foster a culture of continuous improvement. Policy as Code Implementing policies as code helps ensure compliance with organizational standards and best practices. Policies defined in code are version-controlled and can be automatically enforced during
NetDevOps — A Comprehensive Guide with Components and Obstacles
Considering the automation through Agile development processes, the software development industry has experienced a massive shift towards NetDevOps. The credit goes to its underlying network infrastructure offering network automation to fast-paced modern businesses. Since the non-DevOps approach hovers around tools, developers may experience a lack of traceability, testing, and collaboration. Here NetDevOps can help you cop with these limitations and eliminate security vulnerabilities while ensuring expected performance. Similarly, there’s a glut of things you need to know about NetDevOps if you’re looking to incorporate it into your development process. This guide will lead you to the various NetDevOps components and obstacles for a better understanding. What is NetDevOps and Why is it Worth Using? As the term describes itself, NetDevOps is a technical blend of Networking and DevOps. It streamlines the DevOps principles for the deployment and management of network services. If we dig deeper, NetDevOps apply CI/CD DevOps concepts to networking activities for faster delivery. In addition to this, its automated workflows bolster the abstraction, codification, and Infrastructure as Code (IaC) implementation. NetDevOps also eliminate the configuration drift to embed quality and resiliency within the network. In a nutshell, it improves agility by driving clear workflows aiding auditing, governance, and troubleshooting. Challenges You May Face During NetDevOps Development Risk Aversion One of the challenges that organizations may face during NetDevOps development is risk aversion. Many companies are hesitant to adopt new technologies and practices due to the fear of potential failures or disruptions to their existing network infrastructure. This risk aversion can hinder the adoption of NetDevOps methodologies, which emphasize automation, continuous integration, and continuous delivery. To address this challenge, organizations need to focus on building trust by demonstrating the benefits and success stories of NetDevOps implementation. Technical Debt Technical debt refers to the accumulated shortcuts, workarounds, and suboptimal code or configurations that result from rushed or incomplete implementation of network automation processes. This can lead to various issues, including increased complexity, reduced maintainability, and decreased scalability. To mitigate technical debt, organizations should prioritize code quality, conduct regular code reviews, and follow established best practices and coding standards. Implementing automated testing frameworks and leveraging continuous integration and delivery pipelines can help identify and address technical debt early in the development process. Skills Shortage NetDevOps development requires a unique set of skills that combine network engineering, software development, and automation expertise. However, finding individuals with a strong skill set in these areas can be challenging due to the shortage of qualified professionals. To address this issue, organizations can invest in training and upskilling their existing network and IT teams. This can include providing access to relevant courses, certifications, and hands-on training programs. Collaboration with external training providers or universities can also help bridge the skills gap. Documentation Effective documentation plays a crucial role in NetDevOps development, as it ensures that network configurations, automation workflows, and troubleshooting processes are well-documented and accessible to the team. However, maintaining up-to-date and comprehensive documentation can be challenging, especially when changes occur rapidly in dynamic network environments. Organizations can address this challenge by adopting documentation frameworks and tools that facilitate automated documentation generation. Version control systems, wiki platforms, and collaborative document editing tools can also help streamline the documentation process. Unstandardized Data NetDevOps development relies on gathering and analyzing network data to drive automation and decision-making processes. However, network data can be highly diverse and unstandardized, making it challenging to extract meaningful insights and build reliable automation workflows. Organizations should invest in data normalization and standardization techniques to ensure consistency and compatibility across different data sources. This can include using standardized data models, implementing data transformation pipelines, and leveraging data analytics tools for data cleansing and preprocessing. Tool Limitations NetDevOps development often requires the use of various tools and technologies, including network configuration management systems, automation frameworks, and orchestration platforms. However, tool limitations can arise, such as a lack of integration capabilities, limited scalability, or inadequate support for specific network devices or protocols. To overcome these challenges, organizations should thoroughly evaluate and choose tools that align with their specific requirements and network environment. They should also consider open-source solutions that offer flexibility and community support. Top NetDevOps Components Modularity Modularity is a key component of NetDevOps, enabling the creation of flexible and scalable network architectures. By breaking down network systems into modular components, organizations can easily adapt and scale their networks as per evolving requirements. Modularity facilitates the deployment of microservices, allowing for the independent development and deployment of specific network functionalities. This approach not only enhances agility but also simplifies troubleshooting and maintenance, as issues can be isolated to specific modules. For instance, using containerization technologies like Docker, network functions can be encapsulated within lightweight, portable containers, ensuring consistent behavior across different environments. Example 1 – Multiple applications in a single VPC network architecture Example 2 – Single application per VPC network architecture Cultural Changes Cultural changes play a crucial role in successfully implementing NetDevOps. Traditionally, network and operations teams operated in silos, with limited collaboration between them. However, NetDevOps encourages a cultural shift towards increased collaboration, communication, and shared responsibility. By fostering a DevOps culture, organizations can break down barriers between different teams, promoting a collaborative approach to network management. This cultural shift involves embracing shared goals, establishing cross-functional teams, and encouraging continuous learning and skill development. Automation and Infrastructure as Code Automation and Infrastructure as Code (IaC) are pivotal components of NetDevOps, enabling organizations to achieve faster and more efficient network deployments. Automation eliminates manual, error-prone tasks and accelerates the provisioning and configuration of network devices. Tools like Ansible, Puppet, or Chef enable the automation of network device configurations, ensuring consistency and reducing human errors. Infrastructure as Code allows network infrastructure to be defined and managed through machine-readable configuration files, promoting version control and reproducibility. Continuous Integration/Continuous Deployment Continuous Integration/Continuous Deployment (CI/CD) practices are integral to NetDevOps, enabling organizations to rapidly and reliably deploy network changes. CI/CD pipelines automate the process of integrating code changes, testing them, and deploying them to
Kubernetes Persistent Volumes — 5 Detailed Steps to Create PVs
If you want to persist data in Kubernetes, you may utilize the readable and writable disk space available in Pods as a convenient option. But one thing you must know is that the disk space depends on the lifecycle of Pod. Unsurprisingly, your application development process features independent storage available for every node and can handle cluster crashes. Kubernetes Persistent Volumes got your back with their independent lifecycle and great compatibility for stateful applications. This article will lead you to 5 extensive steps to create and implement persistent volumes in your cluster. Before that, let’s dig down to know what exactly persistent volumes in Kubernetes are along with some important terms! Persistent Volumes in Kubernetes A Kubernetes Persistent Volume is a provisioned storage in a cluster and works as a cluster resource. It’s a volume plugin for Kubernetes with an independent lifecycle and no dependency on the existence of a particular pod. Unlike containers, you can read, write and manage your databases without worrying about disk crashes because of restart or termination of the pod. As a shared unit, all the containers in a pod can access the PV and can restore the database even if an individual container crashes. Here are some important terms you must know! Access Modes The accessModes represent the nodes and pods that can access the volume. The field ReadWriteOnce defines every pod having access to read and write the data in a single mode. If you’re using Kubernetes v1.22, you can read or write access on a single node using ReadWriteOncePod. Volume Mode The volumeMode field is mounting functionality of volume into the pods based on a pre-set directory. It defines the behaviour of volume in each Filesystem of a pod. Alternatively, you can use a volume as a raw block storage without any configuration with a Block field. Storage Classes As the name describes, storage classes are the different storage types you can use according to the hosting environment of your cluster. For instance, you can choose azurefile-csi for Microsoft Azure Kubernetes (AKS) clusters while do-block-storage is great for DigitalOcean Managed Kubernetes. Creating a Persistent Volume Step 1: YAML file The process of creating Kubernetes persistent volumes starts with creating a YAML file. The storage configuration represents a simple persistent volume of 1 Gi capacity. Here’s how you can create a YAML file for your PV in Kubernetes: apiVersion: v1 kind: PersistentVolume metadata: name: example-pv spec: accessModes: ReadWriteOnce capacity: storage: 1Gi storageClassName: standard volumeMode: Filesystem Step 2: Adding Volume to the Cluster Once you have created the Persistent Volume, you can add your new persistent volume to your cluster. We recommend using Kubectl for this to make it easier. To add new persistent volume, run: $ kubectl apply -f pv.yaml If you see the following error message while running the command, The PersistentVolume "example-pv" is invalid: spec: Required value: must specify a volume type Try using dynamic volume creation which will automatically create a persistent volume whenever it’s used. That’s because the cloud providers usually restrict allocating inactive storage in the cluster and dynamic volume can be your good-to-go option. Step 3: Linking Volumes to Pods Linking PVs with the pods requires the request to read/write files in a volume. Here the Persistent Volume Claim (PVC) can get you access to the example-pv volume. Let’s see how an example volume claim looks like! apiVersion: v1 kind: PersistentVolumeClaim metadata: name: example-pvc spec: storageClassName: "" volumeName: example-pv As discussed above, you may need dynamic volume creation in some scenarios. You can request a claim for that in the way mentioned below. apiVersion: v1 kind: PersistentVolumeClaim metadata: name: example-pvc spec: accessModes: – ReadWriteOnce resources: requests: storage: 1Gi storageClassName: standard Now, you have unlocked accessModes and storageClassName fields after the claim. All you need to do is to apply the claim to your cluster using Kubectl. Run the following command to quickly apply the claim to your cluster. $ kubectl apply -f pvc.yaml persistentvolumeclaim/example-pvc created In the last, use the volumes and volumeMount fields to link the claim to your pods. This will add pv to your containers section of the manifest and make the files overlive the container instances. To link the claim, run: apiVersion: v1 kind: Pod metadata: name: pod-with-pvc spec: containers: name: pvc-container image: nginx:latest volumeMounts: – mountPath: /pv-mount name: pv volumes: – name: pv persistentVolumeClaim: claimName: example-pvc Step 4: Demonstrating Persistence In the demonstration, you can verify the behaviour of PV in different scenarios. Let’s take a quick example for better understanding. Get a shell to the pod: $ kubectl exec –stdin –tty pod-with-pvc — sh Write a file to the /pv-mount directory mounted to: $ echo "This file is persisted" > /pv-mount/demo Detach the file from the container: $ exit Delete the pod using kubectl: $ kubectl delete pods/pod-with-pvc pod "pod-with-pvc" deleted Recreate the pod: $ kubectl apply -f pvc-pod.yaml pod/pod-with-pvc created Get a shell to the container and read the file: $ kubectl exec –stdin –tty pod-with-pvc — sh $ cat /pv-mount/demo This file is persisted Step 5: Managing Persistent Volumes Kubectl allows you to manage your Kubernetes Persistent Volumes whether you want to retrieve a list or remove a volume. To retrieve a list of PVs, run: $ kubectl get pv NAME CAPACITY ACCESS MODES RECLAIM POLICY STATUS CLAIM STORAGECLASS REASON AGE pvc-f90a46bd-fac0-4cb5-b020-18b3e74dd3b6 1Gi RWO Delete Bound pv-demo/example-pvc do-block-storage 7m52s Review persistent volume claims: $ kubectl get pvc NAME STATUS VOLUME CAPACITY ACCESS MODES STORAGECLASS AGE example-pvc Bound pvc-f90a46bd-fac0-4cb5-b020-18b3e74dd3b6 1Gi RWO do-block-storage 9m Sometimes, a volume or PV claim may show a Pending status as the storage class is yet to provision storage. But you can check what’s slowing down the claim process in object’s event history with describe command. $ kubectl describe pvc example-pvc … Events: Type Reason Age From Message —- —— —- —- ——- Normal Provisioning 9m30s dobs.csi.digitalocean.com_master_68ea6d30-36fe-4f9f-9161-0db299cb0a9c External provisioner is provisioning volume for claim "pv-demo/example-pvc" Normal ProvisioningSucceeded 9m24s dobs.csi.digitalocean.com_master_68ea6d30-36fe-4f9f-9161-0db299cb0a9c Successfully provisioned volume pvc-f90a46bd-fac0-4cb5-b020-18b3e74dd3b6 Conclusion: By combining Kubernetes and Persistent Volumes, you can effectively and easily