No matter how elegant your code is, how solid is your test suite, and how well-developed your system architecture is, the only way your products can impact customers and give positive business is if you deploy it. Before deploying your code, it’s just a philosophical theory or an intellectual exercise.
Even though this is an integral part of the process, customers and businesses don’t care about it. Deployment turns your intellectual work into something plausible and economically sustainable. That’s why companies want to deploy code as quickly as possible.
But focusing on speed usually leads to glitches, bugs, poor tests, and security issues. Luckily, there are ways you can speed up your deployment without cutting corners and disrupting software quality.
Use software distribution platforms
As organizations and projects grow, distributing, managing, and deploying software manually while switching through multiple distribution methods becomes impossible. Software distribution platforms are a relatively new service offering a centralized and automated distribution to handle these processes easily and have a complete overview of the software within your ecosystem.
In other words, you’re outsourcing this part of your work. With a centralized and automated distribution platform, you can save effort and time by automation backups, deployment, and distribution. You reduce errors with automation and maintain a centralized repository for all your software packages with easy access and excellent security.
All your software templates are automatically updated, and users can install software on their devices silently without affecting their use.
Set up a secrets strategy
They should also oversee related secrets when making configuration changes with dynamic services. All the unknown should be passed down to containers during runtime. With a unified secrets strategy, you can ensure that build and runtime secrets don’t get confused, ensuring smooth development and testing.
You only need build secrets, while packaging and runtime secrets are required after deployment. Simply put, development teams should deliver only crucial secrets to their app. All your teams must use the same strategy across all your environments because this makes it easy to track them.
If you add a bit of flexibility to them, you will have an easier time deploying and testing. Ultimately, the focus should be on how secrets are used, not their source.
Gather deployment metrics and analyze them
Kubernetes clusters come with distributed services designed to support various dynamic applications. That’s why you need to have all the essential deployment metrics at your disposal so you can allow applications to adjust to your current traffic.
Metrics are vital for acquiring essential information quickly without using kubectl, informing resource limits, and understanding traffic patterns. These metrics also allow you to continuously monitor the performance of your applications and, more importantly, measure your deployment’s success.
You can use these metrics to recognize issues within the deployment process and fine-tune your approach for future applications.
Set resource limits for your applications
When deploying apps in environments like Kubernetes, there are no resource limits by default. If there are no limits, applications often consume whole clusters and disrupt your overall performance in production.
Every app must have resource limits, and even though developers shouldn’t necessarily handle this on their own, they should know the recommended memory and CPU limits for their applications. When doing this, you should consider load bursts and average traffic to avoid losing essential users.
Various deployment tools provide elasticity regarding resource usage, but they aren’t great by default and can’t find the right balance for your needs. Developers also need to consider the resource limits depending on their coding language.
For example, all Java products are known for their memory limit issues.
Keep your non-production and production clusters separate
Even though having one large cluster for everything is handy, it can create issues around security, resource consumption, and speed. Setup up a minimum of two clusters, one for non-production and the other for production resources.
Having separate clusters prevents communication between the pods in them. Even though multi-tenancy is real, it requires a lot of effort and knowledge to achieve. That’s why it’s better to create multiple clusters. Some teams even create dedicated clusters for developers, shadows, tools, and production.
Conclusion
The main story in development for a decade has been about achieving agility, with DevSecOps and CI-CD being a vital part. However, there’s still a lot of friction with deployments. Deployment affects how teams work toward delivering software, and that’s why it’s crucial to refine the process and improve its results.