In the previous part (Part 1), we learnt about how to get started with Lighthouse CI, what are the different commands available, how to run your first scan and compare the results against a baseline. In this part (Part 2), we continue to look at how to set up a Lighthouse server on Azure so that we can upload the scan results, see trends and compare the scores of your site at different points in time.
We ran our scans and we have validated that the scores are above our baseline. You know what would be nice? The ability to see the results on a dashboard with historic data from every scan and ability to link them to a specific commit and build/release in your pipeline. This is exactly what the Lighthouse server enables us to do. To install the Lighthouse server, run
npm install @lhci/server and then run
lhci server with the below configuration in place to start the server locally on port 9001 which stores the result in a SQLLite Database. …
This blog post shows you how to get started with Lighthouse CI, what are the different configurations and commands available to you and how to run your first scan and compare the results against a baseline that you specify.
Azure Cosmos DB is Microsoft’s globally distributed, multi-model, NoSQL database service. Cosmos DB enables you to elastically and independently scale throughput and storage across any number of Azure regions worldwide. Here are some of the tools that are available to make you more productive with CosmosDB.
Using the Cosmos DB data migrator, you can import from JSON files, CSV files, SQL, MongoDB, Azure Table storage, Amazon DynamoDB, and even Azure Cosmos DB SQL API collections into a new Cosmos DB instance. …