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Gautham Vijayan
Gautham Vijayan

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Full text search with Firestore & Meilisearch Deployment to Koyeb

In this post we will look into how we can deploy a Melli search instance on their own cloud server as well as deploy it on a Koyeb free instance and make a custom search interface to add full text search functionality to our application.

We can deploy Meilisearch to their own cloud provided solution as well as deploy their open source version to our own hosted solution in AWS, Digital Ocean, GCP, Koyeb etc.

First in order to create a Meilisearch cloud account go to this link and register.

They have a minimum pricing of 29 dollars per month, with which you can subscribe to it and immediately gain access to a Meilisearch instance which we can use it in our Backend APIs.

If you feel the cloud version is costly at an initial stage, there is a free open source alternative which you can use it to deploy your instance for free for the initial phase of your application.

I have tried GCP, but it was above 20 dollars per month, so in order to test the features, I went with Koyeb's free instance and eventually upgraded to a paid version as the amount of users increased.

So head to the below link and create an account.

After that you can create an instance in the region you prefer by providing a master key with which you will access the Meilisearch instance from your backend. The Master key is essentially a API key so keep it secure to access your instance and prevent unauthorised access. Wait for 5-10 minutes and the instance will be deployed.

After you have deployed your instance, you will be provided with a host url, which we will be using the next couple of posts to access the instance and add data points, make search request and apply full text search to the data we have uploaded there.

Below you can see the different deployment options where we can deploy our melli search instance.

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You can learn more about the deployments from the official melli search documentation with the below link.

Let's look into Meilisearch APIs in the upcoming posts.

You can view the complete code and see how the search interface works in a live demo below.

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