CloudFoundry vs Firebase

• Support for Orgs and Spaces that allow for managing users and deployables within a large organization.
• Easy deployment, deploying code is as simple as executing single line from CLI, thanks to build-packs.
• Solid and rich CLI, that allows for various operations on the instance.
• Isolated Virtual Machines called Droplets, that provide clean run time environment for the code. This used to be a problem with Weblogic and other application servers, where multiple applications are run on the same cluster and they share resources.
• SSH capability for the droplet (isolated VM's are called droplets), that allows for real time viewing of the App code while the application is running.
• Support for multiple languages, thanks to build-packs.
• Support for horizontal scaling, scaling an instance horizontally is a breeze.
• Support for configuring environment variable using the service bindings.
• Supports memory and disk space limit allocation for individual applications.
• Supports API's as well as workers (processes without endpoints)
• Supports blue-green deployment with minimal down time

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• Analytics wise, retention is extremely important to our app, therefore we take advantage of the cohort analysis to see the impact of our middle funnel (retargeting, push, email) efforts affect the percent of users that come back into the app. Firebase allows us to easily segment these this data and look at a running average based on certain dates.
• When it comes to any mobile app, a deep linking strategy is essential to any apps success. With Firebase's Dynamic Links, we are able to share dynamic links (recognize user device) that are able to redirect to in-app content. These deep links allow users to share other deep-linked content with friends, that also have link preview assets.
• Firebase allows users to effectively track events, funnels, and MAUs. With this simple event tracking feature, users can put organize these events into funnels of their main user flows (e.g., checkout flows, onboarding flows, etc.), and subsequently be able to understand where the drop-off is in the funnel and then prioritize areas of the funnel to fix. Also, MAU is important to be able to tell if you are bringing in new users and what's the active volume for each platform (Android, iOS).

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• Does not support stateful containers and that would be a nice to have.
• Supports showing logs, but does not persist the logs anywhere. This makes relying on Cloud Foundry's logs very unreliable. The logs have to be persisted using other third party tools like Elk and Kibana.

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• Attribution and specifically multi-touch attribution could be more robust such as Branch or Appsflyer but understand this isn't Firebases bread and butter.
• More parameters. Firebase allows you to track tons of events (believe it's up to 50 or so) but the parameters of the events it only allows you to track 5 which is so messily and unbelievable. So you're able to get good high-level data but if you want to get granular with the events and actions are taken on your app to get real data insight you either have to go with a paid data analytics platform or bring on someone that's an expert in SQL to go through Big Query.
• City-specific data instead of just country-specific data would have been a huge plus as well.

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• Positive impact, since it simplifies the deployment time by a huge margin. Without cloud foundry, deploying a code needs coordination with infrastructure teams, while with cloud foundry, its a simple one line command. This reduces the deployment time from at least few hours to few minutes. Faster deployments promote faster dev cycle iterations.
• Code maintenance such as upgrading a Node or Java version is as simple as updating the build-pack. Without cloud foundry, using web logic, the specific version only supports a specific version of Java. So updating the version involves upgrading the version of web logic that needs to involve few teams. So without cloud foundry, it takes at least few days, with cloud foundry, its a matter of few mins.
• Overall, happier Developers and thats harder to quantify.

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• Makes building real-time interfaces easy to do at scale with no backend involvement.
• Very low pricing for small companies and green-fields projects.
• Lack of support for more complicated queries needs to be managed by users and often forces strange architecture choices for data to enable it to be easily accessed.

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