Cloud-Native

What can we expect for Kubernetes in 2023? As Kubernetes approaches the eighth anniversary of its first version launch, we look into the areas of significant change. So what does the Kubernetes ecosystem look like and What can we expect for Kubernetes in 2023? In short, is huge and continues to grow. As more businesses, teams, and people use it as a platform for innovation, more new applications will be created and old ones will be scaled more quickly than ever before, fuelling its continual development. The State of Kubernetes 2022 study from VMware Tanzu and the most recent Annual Cloud Native Computing Foundation (CNCF) Survey both indicate that Kubernetes is widely adopted and continues to grow in popularity as a platform for container orchestration. These studies suggest that Kubernetes has become a de facto standard in the industry and its adoption will likely continue to increase in the coming years. Anticipated Shift towards Kubernetes on multi cloud As we move forward into 2023, it’s becoming increasingly common for businesses to utilize multiple cloud providers for their Kubernetes deployments. This trend, known as multi-cloud/hybrid deployments, often involves the use of container orchestration and federated development and deployment strategies. While there are already tools available for deploying and managing containers across a variety of cloud providers and on-premises platforms, we can expect to see even more advancements in this area. Specifically, there will likely be an increase in technology that makes it easier to create and deploy multi-cloud systems using native cloud services that work seamlessly across different providers. Multi-cloud adoption allows businesses to take advantage of the strengths of different cloud providers, such as leveraging the best database solutions from one provider and the best serverless offerings from another. This approach can also increase flexibility, reduce vendor lock-in, and provide redundancy and disaster recovery options. Additionally, it can allow for cost optimization by taking advantage of different pricing models and promotions offered by different providers. Continual Evolution of DevOps and Platform Teams: To survive in this digital age, businesses need to have a diverse set of skills and knowledge areas within their workforce. Close collaboration between different departments and disciplines is essential for leveraging new technologies like Kubernetes and other cloud platforms. However, these technologies can be difficult to learn and maintain, and teams may struggle to gain in-depth understanding of them. Businesses should focus on automation and acceleration, but also invest in training and development programs to help their teams acquire the necessary skills to effectively use these technologies. Companies of all sizes should think about where they want to develop their Kubernetes knowledge base. Many businesses choose a platform team to develop and implement this knowledge. Multiple DevOps teams can be supported by a single platform team. This separation allows DevOps teams to continue concentrating on creating and running business applications while the platform team looks after a solid and dependable underpinning platform. Improved Stateful Application Management: Containers were originally intended to be a means of operating stateless applications. However, the value of running stateful workloads in containers has been recognised by the community over the last few years, and the newer versions of Kubernetes have added the required functionalities. Now there are better ways to deploy stateful applications, but the outcome is far from ideal and inconsistent. By including a controller in the cluster, K8s operators can resolve this difficulty. Reconciliation loops are controller loops that monitor differences between the current and intended states and adjust return the current state to the desired state. Maturity in Policy-as-Code for Kubernetes The goal has been to give teams more autonomy when delivering applications to Kubernetes for several years. In many businesses today, creating pipelines that can quickly send out apps is standard procedure. Although having autonomy is a great advantage, maintaining some manual control still requires finding the proper balance. The transition to everything as a code has opened a plethora of opportunities. Following accepted engineering principles will make it simple to validate and review policies defined as-code. As a result, the importance of policy frameworks will increase. Within the CNCF, Open Policy Agent (OPA) is the most common policy framework. Practices like this will advance concurrently with the adoption of Kubernetes and autonomous teams to enable continual growth while preserving or even gaining more control. Adoption enables you to control how Kubernetes is used by a wide range of teams. Enhanced Observability and Troubleshooting capabilities: Troubleshooting applications running on a Kubernetes cluster at scale can be challenging due to the complexity of Kubernetes and the relationships between different elements. Providing teams with effective troubleshooting solutions can give an organization a competitive advantage. The Four elements (Events, Logs, Traces, Metrics) are important in understanding the performance and behaviour of a system. They provide different perspectives and details on system activity, and when combined, give a more complete picture of the issue. Solutions that integrate these four elements can aid in faster troubleshooting and problem resolution and can also help in identifying and preventing future issues. Vendors and open-source frameworks will continue to drive this trend. Focus on supply chain security: Software supply chain security has been in laser sights for a while now, as most software rooted from other software. The necessity of ensuring Kubernetes’ strength has increased along with its importance as it becomes more widely adopted, it is important to ensure its security as it is a critical component of the software supply chain. This includes securing the infrastructure on which it runs, as well as securing the containerized applications that are deployed on it. The “4C’s of cloud native security” model is a good place to start thinking about the security of the different layers of a cloud native application: Cloud, Clusters, Containers, and Code. Each layer of the Cloud Native security model builds upon the next outermost layer, and they are equally important when considering security practices and tools. This can be done through a variety of methods, such as using secure configurations, implementing network

Progressive Delivery (the GitOps way) with Kubernetes: One of the biggest challenges organisations faces, especially when running microservices, is managing application deployments. Having a proper deployment strategy is necessary. For instance, in a production environment, it is always a change management process requirement to ensure that the downtime impact on the end-user is minimised and maintenance windows need to be planned to cater for any changes that will cause an outage. It is also mandated that in case of any issues when deploying the change, a rollback plan must be ready for execution to recover from any failures. These challenges amplify with the increase of the number of microservices and makes it more difficult to assess the result of the deployment and execute the rollback if required. Enter progressive delivery. Thankfully, cloud native architectures using Kubernetes running microservices addresses this problem by offering increased flexibility, allowing teams to publish more useful updates more frequently and progressively. The use of release techniques like Canary, Blue-Green, and Feature flagging as part of progressive delivery enables teams to maximise an enterprise’s software delivery. It is predicated on the notion that consumers desire to test features prior to completion to enhance the user experience. In Kubernetes, there are different ways to release an application. It is necessary to choose the right strategy to make the infrastructure reliable and more resilient during an application deployment or update. The out of the box Kubernetes Deployment Object supports the Rolling Update strategy which comes as a standard and provides a basic set of safety guarantees (aka. readiness probes) during an update. When deploying into a development/staging environment, standard Kubernetes deployment strategies such as a recreate or rolling deployment might be a good option. However, the rolling update strategy faces may limitations such as controlling the speed and flow of the rollout. in large scale high-volume production environments, a rolling update is often considered too risky of an update procedure since it provides no control over the blast radius, may rollout too aggressively, and provides no automated rollback upon failures. In production environments, more advanced deployment strategies are much needed to satisfy the business requirements. These advanced strategies are called “Progressive Deployments”. An example of these deployment strategies is the Blue/Green deployment which allows for a quick transition between the old version and the new version by deploying them side by side and then switching to the new version when testing has been successful. This testing of the platform needs to be thorough to avoid having to rollback frequently. If unsure of the platform’s stability or the potential effects of releasing a new software version, a canary deployment offers a smaller scale next version of the release running side by side the current version in production. By doing so, the new release is rolled-out to a small subset of users to test the application and provide their feedback. Once the change is accepted, it is rolled out to the rest of the users. Benefits of Progressive Delivery: Progressive delivery lowers the risk of releasing new features, as well as identifying and resolving possible issues with those additions. It also offers early feedback on any version of your application. Before a feature is fully deployed, the developer can test out various changes on the product to see how the application behaves. The idea is that the developer can alter the release strategy if the modifications are unfavourable to prevent end users from experiencing any glitches. Secondly, improved release frequency results from sequential delivery. While the primary goal of progressive delivery is to provide end users with safer, more dependable releases, you as the DevOps team will benefit from being able to deploy new versions in smaller parts and hence release more frequently. You can work on each feature separately and release it in tiny sprints. The time to market is shortened, and any DevOps team can now deploy better software more quickly. Finally, and this is something that is frequently ignored, progressive delivery leads to improved segregation of duties between the development and operations teams. This segregation of duties works better with progressive delivery since developers concentrate on creating new features while operations concentrate on rolling out the new features gradually in a strategy that suits the operational needs of the platform. Progressive delivery is best achieved with GitOps: This demand for progressive delivery in a cloud native manner can be achieved with GitOps. The objective behind GitOps is to define and declare everything in Git including operational tasks. Git is already used by developers to generate and collaborate on code. GitOps simply expands this concept to include the creation and setup of infrastructure as well. Git becomes the control plane for operations and deployments because everything is declared as code in Git. GitOps is being enabled by open-source tooling such as ArgoCD, Flux and Flagger, which automatically checks Git repositories for any new changes, and if it detects a change, it automatically deploys it to production. With progressive delivery, these automated deployments need to be done in phases and to multiple target Kubernetes clusters. These tools offer full control of the software delivery pipeline, rollback strategies, test executions, feature releases, and scaling of infrastructure resources. In conclusion, there are various methods for deploying an application to cater for applications with varying complexities, teams with different demands, and environments with different operational requirements and compliance levels. Selecting the right strategy or strategies and having full control over these strategies in code when combined by the right tools is an extremely powerful feature of cloud native platforms that greatly simplifies change management, release management, and operations of the applications. It completely disrupts the way operations teams traditionally thought of these processes as rigid and extremely sensitive with a dramatic business impact in case anything went wrong, into simplified processes and tasks that can be executed every day in the background without having an impact on the end-user.

Transforming the Way We Manage Data Data is the backbone of today’s digital economy. With the ever-increasing volume of data being generated every day, the need for efficient, scalable, and robust data management solutions is more pressing than ever. Enter Kubernetes, the revolutionary open-source platform that’s changing the game of data management. Market research suggests that the demand for Kubernetes in data management is growing at a rapid pace, with a projected compound annual growth rate of over 30% by 2023. There is an increase in demand for Kubernetes. With its ability to automate deployment, scaling and management of containerized applications, is providing organisations with a new way to approach data management. By leveraging its container orchestration capabilities, Kubernetes is making it possible to handle complex data management tasks with ease and efficiency. Stateful applications, such as databases and data pipelines, are the backbone of any data management strategy. Traditionally, managing these applications has been a complex and time-consuming task. But with Kubernetes, stateful applications can be managed with ease, thanks to its Persistent Volumes and Persistent Volume Claims. Data pipelines, the critical component of data management, are transforming the way organizations process, transform and store data. Kubernetes makes it possible to run data pipelines as containers, simplifying their deployment, scaling, and management. With Kubernetes in-built jobs support, these workflows can run as a scheduled or triggered jobs that are orchestrated by the Kubernetes engine. This enables organizations to ensure the reliability and efficiency of their data pipelines, even as the volume of data grows. Scalability is a major challenge in data management, but with Kubernetes, it is by design. Its ability to horizontally scale the number of nodes in a cluster makes it possible to easily handle the growing volume of data. This ensures that data management solutions remain robust and scalable, even as data volumes increase. Resilience in another key requirement in data management. Traditionally, a single point of failure can bring down the entire system. But with Kubernetes, failures are handled gracefully, with failed containers automatically rescheduled on healthy nodes. This provides peace of mind, knowing that data management solutions remain available even in the event of failures. Kubernetes also offers zero downtime deployment in the form of rolling updates. This also applies to databases where the administrator can upgrade the database version without any impact to the service by rolling the update to one workload at a time until all replicas are upgraded. To complement the resilience features, operations such as memory or CPU upgrades which, in the past, were considered destructive changes that required planning and careful change and release management. Today, since Kubernetes relies on declarative management of its objects, this change is just a single line of code. This change can be deployed similar to any code change that progresses to the different environments using CI/CD pipelines. Conclusion In conclusion, Kubernetes is transforming data management. Gone are the days of regarding Kubernetes as a platform suitable only for stateless workloads leaving databases running on traditional VMs. Many initiatives took place to adapt stateful workloads to run efficiently and reliably in Kubernetes from releasing the StatefulSets API and Storage CSI, to building Kubernetes operators that will ensure databases can run securely in the cluster with massive resilience and scalability. With these operators being released for common database systems such as Postgres and mySQL to name a few, daunting database operations such as automatic backups, rolling updates, high availability and failover are simplified and taken care of in the background transparent to the end user. Today, with more database vendors either releasing or endorsing Kubernetes operators for their database systems, and enterprises running databases in Kubernetes production environments successfully, there is no reason to think that it lacks the necessary features to run production enterprise database systems. The future of data management is looking bright, and we excitedly await what lies ahead thanks to the Kubernetes community’s constant drive for innovation and the expansion of the possibilities. To learn more about Kubernetes and our service offering here.

What is Cloud Transformation?  What is cloud transformation? In today’s world, cloud is the first option for everyone to run their workloads, unless they have a compelling reason such as compliance or security concerns to deploy it on-premises. Most of the organisations who manages their workloads on their own data centres, are looking for an opportunity to move to the cloud for numerous benefits which most of the cloud services providers offer. As per the recent survey by Forbes and Gartner recently increased prior forecasts of worldwide end-user spending on public cloud services to anticipate a 23.1% jump this year, followed by a more than 16% increase in 2022 — up from $270 billion in 2020 to just under $400 billion.  While the acceleration of cloud transformations continuous, most businesses data still reside on on-premises. Consequently, hybrid solutions that were once downplayed by virtualisation have emerged as not only practical but likely a preferred approach. We’ve moved past the “cloud-first” era to a time when clouds are becoming omnipresent.   There are numerous benefits in using cloud services. Some of key benefits are discussed below;  Pay per use: Switching from the on-premises IT infrastructure to remote cloud infrastructure provided by a third-party cloud provider allows businesses to make potentially significant cost savings in their IT expenditure.  Disaster Recovery: Cloud computing ensures that disaster recovery is much easier than it might otherwise be. This is because critical data is stored off-site in third-party data centres, thereby making it easier to retrieve in the event of unscheduled downtime.  Scalable: As your business grows, so is your infrastructure needs. Alternatively, it may be that you’ve had to scale down your operation, and with it your IT compute and storage needs. Cloud computing provides easy scalability, allowing you to scale up and scale down as your circumstances change.   Less maintenance: By adopting cloud, businesses can free up the resources (including both financial and human resources) for deployment in other areas. This allows them to have more focus on customer base, rather than managing and maintaining their own IT resources.  Security: Data security has been one of the key aspects to be considered when migrating into cloud. cloud providers go to great lengths to ensure that data is kept secure. They are tasked with protecting data from threats and unauthorized access, and this is something they do very effectively using robust encryption.  Because of these obvious reasons and much more benefits, many businesses are starting their journey to move or transform their applications or workloads to the cloud and this process of migrating or transforming the applications or workload is called as “Cloud Transformation”  What is Cloud Transformation? Cloud transformation is simply the process of migrating or transforming your work to the cloud, including migration of apps, software programs, desktops, data, or an entire infrastructure in alignment with the business objectives of the organization  The first step in performing the transformation is to do a comprehensive assessment if the cloud computing is suitable for our organisation from a long-term business strategy. Cloud transformation is popular because, among many other benefits, it increases the efficiency of sharing and storing data, accelerated time-to-market, enhanced organizational flexibility and scalability, and centralize their network security. Overall, it hugely changes the way of operating a business.  How to Approach Cloud Transformation? As state above cloud transformation is the enablement of a complete business transformation. To achieve this, organizations focus on cloud strategy, migration, management and optimization, data and analytics, and cloud security to become more competitive and resilient.  There are various ways the transformation to the cloud can be done but you may need to choose the option that better suits your organisation and its goals. A few options listed below will help you to consider the right options for the transformation approach.   Understanding the Organisation long term goals and environment   Security and regulatory considerations  Building a cloud transformation strategy and roadmap  Choosing the right cloud and approach   Defining a Robust Governance model  Layers of Cloud transformation  All or any of the below component layers are to be changed as a part of transformation when migrating to the cloud.  Application layer  It is the core layer where your application is hosted to run. It is also known as compute layer to run application code which performs business operations. Along with application code base, it also contains dependencies and software packages which are required to run your application.  Data layer  It consists of data which are processed by the application layer. This is the layer which maintains the state of your application. Storage (Files, Databases, stage management tools) is the key components of this layer.   Network layer  It consists of network components like LAN, router, load balancers, firewalls, and VPN etc. It is responsible for providing the segregation between different components and ensure restriction is applied between them as needed.  Security layer  Though it is mentioned as a separate layer, it will be part of each other layer mentioned above. For e.g., when migrating application layer, we will not be just migrating it but will be considering proper security in place by having security rules (firewall rules) in place and only the required traffic is allowed from and to the application. It applies for data and network layer as well.  Types of Cloud transformation  Distinct types of cloud transformation are listed and discussed below,  Lift & shift (or) Re-hosting  Re-platform  Re-factor (or) Re-architect  Develop in cloud  Lift & Shift (or) Re-hosting  This approach is nothing but lifting the application from on-prem and deployed to the cloud as-is. This is one of the quickest ways to transform the application from on-premises to the cloud but will not utilize the benefits of cloud-native features. The applications which do not have dependencies with on-premises and have less business impact are the ideal candidates for this approach. It is a way to start your cloud journey with smaller applications and then progress to a bigger one.  Application layer – No change  Data layer – No