Selecting the right deployment strategy for you project is a critical step in the software development lifecycle. It can be the difference between a smooth deployment and a disaster. This guide will help you understand the best practices for deploying to production.
Blue/Green Deployment
This method is a good strategy to choose if you require zero downtime. It involves running two identical production environments, one of which is live and the other is idle. When you need to deploy a new version of your application, you can switch the traffic from the live environment to the idle environment. This way, you can test the new version in production without affecting the live environment. If the new version has any issues, you can easily switch back to the live environment.
You can even roll this out slowly by switching a small percentage of the traffic to the new environment and gradually increasing it.
The challenge with this method is that it requires a lot of resources to maintain two identical environments. It also requires a lot of automation to switch the traffic between the two environments. However, if you require zero downtime, this is the best strategy to choose.
Canary Deployment
This method is similar to blue/green deployment, but it involves rolling out the new version to a small percentage of users. This way, you can test the new version in production without affecting all users. If the new version has any issues, you can easily roll back to the previous version.
The challenge with this method is that it requires a lot of automation to roll out the new version to a small percentage of users and gradually increase it. However, if you want to test the new version in production without affecting all users, this is the best strategy to choose.
A/B Testing
This method is similar to canary deployment, but it involves rolling out the new version to a small percentage of users and comparing it with the previous version. This way, you can test the new version in production and compare it with the previous version to see which one performs better.
The challenge with this method is you need to understand how to measure the performance of the new version and compare it with the previous version. You need to define your success criteria and ensure this is the important metric you use. You also need to understand what timeframe you want to measure the change and when to increase the percentage.
A/B Testing is a great tactic when you want to make sure that your change is positively impacting your users. It's also a great way to test new features and see how they perform in the real world. For example if your team had an idea for a new feature but the customers didn't like the new feature, you can easily roll back to the previous version.
Feature Toggles
This method involves deploying the new version to production but not enabling it for all users. Instead, you can enable the new version for a small percentage of users or for specific users. This way, you can test the new version in production without affecting all users. If the new version has any issues, you can easily disable it for all users.
This method works well if you have a new feature that you want to test in production without affecting all users. Having something like a cookie that can set to enable the feature means only selected users will see the new feature.
You can use this as a way of beta testing new features to get feedback from your users.
Infrastructure as Code
This method involves defining your infrastructure in code and using automation to deploy it to production. This way, you can easily replicate your production environment in other environments, such as staging and development. You can also easily roll back to a previous version of your infrastructure if you need to.
This method is very important to ensure that you can test your deployment process in a lower environment before deploying to production. It also ensures that you can easily replicate your production environment in other environments. You hear a lot of cases where everything is working in staging environment but broken in production.
Continuous Integration/Continuous Deployment (CI/CD)
This method involves automating your deployment process so that you can deploy to production as soon as your code is ready. This way, you can easily roll out new versions of your application to production without any manual intervention.
There are lots of tools these days that allow you to do this, many of them are attached to your code repository like Github actions, Gitlab CI, CircleCI, TravisCI, Jenkins, etc. There are plenty of resources to help you get started with CI/CD.
CI is the method of ensuring that all code is tested and integrated into the main branch. CD is the method of ensuring that all code is deployed to production as soon as it's ready.
Containerization
This method is similar to infrastructure as code depending on the large of your application. It involves packaging your application and its dependencies into a container image and using automation to deploy it to production. This way, you can easily replicate your production environment in other environments, such as staging and development. You can also easily roll back to a previous version of your container image if you need to.
This methods makes it very easy to replicate your development environment in production.
It also makes upgrading your applications system code very easy. For example if you need to upgrade Linux or Nginx you can do this locally by changing your docker base image, check if your application still works and then deploy to production.
Ensure that the resources assigned to the container are enough to handle the amount of traffic that the application is serving.
Monitoring
Monitoring is a practice that is very very important to your application, it's often a forgotten step, until something goes wrong. You should be monitoring your application in production to ensure that it's working as expected. You should be monitoring things like response times, error rates, and resource usage. You should also be monitoring your infrastructure to ensure that it can handle the amount of traffic that the application is serving. You might find out that your environment has too much resource and you can reduce this to save money.
You can use tools like New Relic, Datadog, Prometheus, Grafana, etc to monitor your application and infrastructure.
Load Testing
Load testing is a practice that you should be doing before deploying to production. You should be testing your application under load to ensure that it can handle the amount of traffic that it's serving. You should be testing things like response times, error rates, and resource usage. You should also be testing your infrastructure to ensure that it can handle the amount of traffic that the application is serving.
Logging
Logging is a method that you need to develop in software development. You should be logging everything that happens in your application so that you can debug issues in production. You should be logging things like errors, warnings, and informational messages. You should also be logging things like request and response times, and resource usage. You can use tools like ELK, Splunk, Sumo Logic, etc to log your application.
When something goes wrong in production and you can not replicate it the logs are going to be the only way you'll be able to figure out what is happening in production.
If you are using a cloud provider like AWS, Azure, GCP, etc you can use their logging services to log your application.
If you're using Laravel you can easily use the Log facade to output the logs to a file, you can also use Monolog to output the logs to a file or a service like AWS CloudWatch.
Here is an example of how you can use the Log facade in Laravel:
Log::debug('This is a debug message');
Log::info('This is an informational message');
Log::warning('This is a warning message');
Log::error('This is an error message');
Alerting
Alerting from your applications can only happen after you have the monitoring and the logging setup. You need to have the monitoring setup inorder to alert on increase use of resource, you need to have the logging setup in order to alert on a specific error.
With the monitoring you can should be alerting with things like response times, error rates, and resource usage.
With the logging you can setup log metrics and alert on these metrics. For example you can alert on the number of 500 errors in your application. You can have a log for failing payments and then feed this into log metrics and alert when this goes over a certain threshold within a certain time frame.
You can use tools like PagerDuty, OpsGenie, VictorOps, etc to alert on your application.
If you are using a cloud provider like AWS, Azure, GCP, etc you can use their alerting services to alert on your application.
If you have a 24 hour application then alerting is required in order to have an on-call procedure. Tools like PagerDuty can be used to alert the on-call person when something goes wrong. PagerDuty will notify the on-call person via SMS, Email and even a phone call. This will ensure that someone is always available to fix the issue, if you have a ecommerce site or a 24 hour application then this is a must. But you have to make sure that the logging and monitoring is setup correctly.
Conclusion
Selecting the right deployment strategy for your project is a critical step in the software development lifecycle. It can be the difference between a smooth deployment and a disaster. The best strategy to choose depends on your requirements and the resources you have available. You should also be monitoring and logging your application in production to ensure that it's working as expected. You should also be alerting on your application to ensure that someone is always available to fix the issue.