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What is Continuous Delivery

Technology is advancing at a breakneck speed, and customers expect to experience that from their service providers and products. In today’s fast-paced world, technology is advancing at a breakneck speed, and customers also expect the same speed from their service providers.

Continuous Delivery (CD) is a DevOps methodology that enables development teams to deploy changes such as new features, configuration, bug fixes, and experiments into production safely and quickly in a sustainable manner. The continuous delivery process requires a collaborative approach from different stakeholders in a software delivery process such as developers, operations, and testing teams. It streamlines the complexities of software delivery into a pipeline model that allows for a smooth flow of codes/changes from developers into the hands of end-users.

We refer to this pipeline as a DevOps CI/CD pipeline that allows organizations to deploy code changes to test and production environments through a repeatable and automated test release process empowering developers to release changes on demand.

Differentiating Continuous Delivery from Continuous Deployment

Continous Delivery is a framework that commences at the end of a Contionuous Inmtegration cycle. Continuous Delivery is all about deploying code changes to staging and then to a prodction, post the build. It enables organisations to deploy code to production on an on demand basis.

Wheras, Continous deployment enables the automatic deployment of changes to production. This accelerates the improvment process becuase developers can verify their code at prduction on the same hour. This gives them the incentive to experiment and test out new features beasue the same code can be rolledback at the same speed it was deployed into production.

Why was there a need for Continuous Delivery

More than a decade ago, engineers and developers improved the software delivery process by introducing Continuous Integration. The CI framework formed the stepping stone for immutable infrastructure where developers could push code changes multiple times a day, thus triggering an automated build cycle that takes care of integration issues before the change reaches production. Normally after the code was built, it was ready to be deployed into standalone monolithic servers and mainframes. In this traditional environment, the deployment process was mostly manual and sometimes leveraged scripts. But with the release of modern platforms like Kubernetes, the traditional physical machine-based platforms became redundant. The script leveraged delivery processes failed to scale. The distributed topologies made the delivery process much more complex, and they met with a series of issues that are highlighted below:

1. Machines move bits better than humans. Manual effort leads to mistakes, defects, and higher cost

A manual process is highly prone to errors. When the organizations scale the process, they cannot keep up with business expansion. For example, a multinational company with developers located across the globe pushing codes will significantly constrain the delivery process and may eventually lead to a process breakdown.

2. Scripts are not scalable.

Point automation with the help of scripts could only improve efficiency to a certain extent. When organizations moved from the monolithic architecture of mainframes and on-premise servers to a microservices production environment, the scripts just weren’t able to cope with this transformation. But an automated continuous delivery pipeline will guarantee that the code flows to its destination at the push of a button.

3. Misaligned goals led to a lack of ownership and collaboration

Successful deployment of code into production is a goal, not only for SREs but also for developers. Everybody is responsible for a code failure at production. But in reality, responsibility gets passed across the different stakeholders in a software delivery process. Crucial time gets wasted in blame games and firefighting.

 4. Low frequency of deployments correlated to lower standards of Code Quality

Working in small and frequent steps is always beneficial. The same logic can be applied in the context of the software delivery process. When a bulk load of code updates gets lined up for deployment at the last minute things are bound to go wrong. This will lead to last-minute firefighting. In turn, code quality gets compromised to meet deadlines. Doing things in bite-size makes things easy to manage and quick to troubleshoot.

5. Faster feedback incorporation is essential for continuous improvement

Feedback from end-users of a product highlights underlying issues or improvements. These feedbacks when incorporated as soon as they are received will ensure that customers engage more, and do not switch to competitor applications. This cycle, when repeated, is called continuous improvement. A delay between feedback incorporation and the time when feedback was received will inversely affect customer satisfaction.

6. Repeatable processes simplify the creation of delivery workflows

Releasing code must be simple and easy. Pipelines that are templatized provide the ability to configure and set up pipelines quickly while maintaining security and compliance standards. It also helps in managing hundreds of pipelines through a management tool.

What value does Continuous Delivery bring?

High-performance teams equipped with the CD framework can achieve outstanding results to their counterparts who are not using a continuous delivery framework. Organizations who want to stay a step ahead of the competition must adopt the best practices of continuous delivery.

1. Reduced Risk for Releases

Continuous delivery frameworks enforces a template process that is repeatable and automated. This reduces the risk in software deployments and makes it a straightforward process. It empowers developers to perform updates anytime and on-demand. With advanced deployment strategies, continuous delivery has eliminated the chances of encountering errors in production.

2. Fast GTM

Code not delivered is money burnt. In a traditional environment, a software delivery could take up to weeks or months. Think about the Operating system updates 10 years back and compare that with now. By performing the testing, provisioning and deployment as a daily activity in an automated phased and repeatable way, large amounts of rework. can be avoided.

3. Better Quality software

With the delivery process automated, engineers and developers get more time to invest in their code writing. Writing code. Automated security, test, and performance checks help developers to troubleshoot errors at the beginning of the deployment pipeline. This ensures high-quality code updates and thus better quality products.

4. Reduced Costs

In a traditional delivery framework, delivering updates is an arduous task. But investing in an automated deployment pipeline will substantially reduce the cost of delivering updates throughout the lifetime of the product. We can achieve this by simply eliminating the fixed overhead costs.

5. Customer-Centric products

A CD framework has enabled development teams to work in small batches. This smaller deployment cycle means developers can get feedback from customers as soon as they have released an update. Teams get to engage actively with users and can observe the outcomes of their updates first-hand. This step by strep incremental update process with feedback loop ensures that all the right things get added to the product. With the help of deployment strategies, we can minimize customer impact.

6. Confident Teams

Continuous delivery frameworks simplify the software delivery process and with deployment strategies, such as Canary that work without demanding a heavy toll on infrastructure and give developers the confidence to experiment and innovate more.Even after a successful continuous delivery implementation some SRE’s still struggle with a slow pipeline. These occur because of a variety of reasons. Read the blog on tackling slow pipelines to understand what might be causing the issues.

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How do I get started?

Before initiating a continuous delivery transformational journey, one imagines the journey will be linear and smooth. But in reality, there will be many challenges that we would need to face. There will be many hurdles to overcome. Evaluating one’s journey will throw light on an organization’s current bearings. In addition, it opens the possibility of potential areas for improvement. Read more on our blog titled Is your DevOps Journey heading the right way? On how you could assess if you are taking the right steps. In the CD journey, we are going to rely heavily on measuring metrics on some critical outcomes to ensure that we deliver software and services fast and reliably. These metrics are essential to make a convincing case for transforming a continuous delivery platform, as it offers a significant improvement qualitatively and quantitatively on business outcomes. Understand how one can forecast the ROI of their transformative continuous delivery journey by analyzing the essential metrics prescribed by the DORA foundation.

Which Continuous Delivery tool do I select and why?

Most tools in the market boast of bringing about the desired outcome expected from a continuous delivery implementation. We have mentioned before that continuous delivery is a framework with multiple moving parts. Many organizations over the years have tried to align to the desired continuous delivery state by implementing a patchwork of tools to improve efficiency. But this amalgamation of multiple tools in an interconnected pipeline delivery becomes a security threat and is not scalable on demand. So it is important that one chooses a platform that can tick all the boxes and provide all the necessities and beyond in one integrated platform.

Things that one must keep an eye out for while selecting a Continuous Delivery platform are:

  • Easy setup and configuration
  • Visibility and collaboration
  • Software integration and extensibility
  • Build and deployment environment support
  • Security and compliance
  • Workflow flexibility
  • Performance, uptime, and scalability

Our product OpsMx Enterprise for Spinnaker not only checks all these boxes not only meets all the above-mentioned criteria but also provides you an added layer of intelligence called Autopilot, that leverages Machine learning algorithms to give you a risk-free and trouble-free deployment experience. We at OpsMx can implement it for your DevOps team in less than 15mins. In addition, OpsMx provides 25+ sample pipelines for free so that any organization can start deploying into their target environment on their Day-1 of operation.

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