Development efficiency is critical in modern software environments – but it’s one of the top challenges for organizations. For many teams, lead time for changes (the length of time for a code commit to enter production) can take weeks due to manual processes. The standard software delivery lifecycle (SDLC) processes are brittle, slow, unreliable, and costly. And, there’s very little repeatability for the next deployment. However, it might surprise you to learn that developers aren’t spending the majority of their time writing code.
In a recent survey Harness CEO Jyoti Bansal conducted on LinkedIn, 80% of respondents said they are spending less than four hours coding a day. And, according to a survey on productivity by ActiveState, developers often find that their time is eaten up by a combination of tasks, including meetings, manual testing, and hunting down bugs in production. This work takes the developers away from what they were hired to do: innovate to support business objectives.
To improve efficiency, many teams are adopting new deployment patterns to eliminate unnecessary and repetitive tasks that add to development lead time. In software delivery, having a safe, fast, and repeatable way of getting your changes into production is critical, and that’s where having a deployment pattern can help. Organizations that adopt these patterns can speed time to production by 99%, taking weeks-long lead times down to just one hour. But which pattern is the best fit for your organization?
The Top 4 Deployment Patterns for Developer Efficiency
1. Continuous Deployment (CD)
Continuous deployment (CD) is a strategy that automates the deployment of code changes to production environments. Specifically, it involves automating the process of building, testing, and deploying code changes. Code is only deployed after predefined, automated testing and after passing approvals set by development teams, reducing risk and improving time-to-market. CD enables teams to quickly and reliably deploy updates to their applications, allowing them to respond quickly to customer feedback and market changes.
2. Pull Request Environments
A pull request (PR) environment is a temporary isolated environment where code changes can be deployed before being merged into the main code base. The changes are deployed in an environment that closely resembles the production environment to test for any potential issues without affecting customers. Also known as ephemeral environments, a link to is added to a pull request to enable changes to go live for review by the development team, enabling rapid iteration. These environments are typically created by CI/CD solutions.
GitOps is an approach for companies looking to simplify deployments of cloud-native applications. The development team’s Git repository is the single source of truth to automate infrastructure. GitOps provides developers with a tool to create and deploy new software features and services while achieving the desired state of the system. The foundational elements of GitOps include declarative infrastructure, version control, automated change approvals, and software agents.
4. Multi-Service Environment
A multi-service environment, or multi-service deployment, is the process of deploying multiple services or applications on the same infrastructure across multiple environments. This type of deployment involves using various technologies such as containerization, orchestration, and automation to deploy multiple services on shared infrastructure. A multi-service environment enables developers to quickly deploy new applications or make changes to existing ones without any downtime or disruption in service.
Learn More About the Deployment Patterns
This blog was just a snapshot of the insights shared with our attendees. Want to learn more about these deployment patterns, their pros and cons, and how they improve development efficiency? Watch the full webinar or download the ebook today!