gerbasic.blogg.se - Download puppeteer docker for free

Second-time browser launch is so much faster! But why? We can see that the first time our function starts in a few seconds, but then it launches the browser and opens a new tab. Wow, that's unexpectedly slow! Let's trigger it one more time to check how warmed-up lambda works:

Here are performance results for the first cold start run: You can find the full deploy bash script in the git repo containing all code and automation from this article.

Create an ECR repository to store docker image.

Create an S3 bucket to store our application template.

To deploy our Lambda function, we have to perform few steps:

open URL (provided as input) in this tab, and wait for loadĮnter fullscreen mode Exit fullscreen mode.

You can use it for web scraping, testing, and monitoring websites, especially when content is rendered via javascript. Our Lambda function will get an URL as an input and return text from the rendered webpage as output.

We will create and deploy a simple Lambda function based on a custom docker image and investigate the performance of this solution. Container support solves all these problems, and I decided to give it a try. It was hard to develop, test, and deploy. Previously there were no options for custom runtime in AWS Lambda, and additional binaries had to be added using Lambda layers. You can build your image based on any Linux distribution or using base images provided by Amazon. And AWS Lambda looks like a great tool for this task.Īt the end of 2020, AWS introduced Container Image Support for Lambda service. One of the recent tasks was to discover possible variants of covering high demand for headless Chrome instances for a short time (handle burstable workload). We're providing a highly scalable web scraping API. In it, people complained that their build passes 9 minutes on Travis-CI, whereas locally, due to caching images of the docker, the build finishes in a minute.I'm responsible for all the technical stuff at the ScrapingAnt. In general, there was a hot discussion of tasks with the docker inside. You cannot rely on reproducibility of your execution environment like with Docker images which are immutable. This means that when Travis updates their environment with newer versions of packages there are no guarantees that your CI builds continue working like before. Travis uses generic purpose VMs with many packages pre-installed and many add-ons ready to be installed. Judging by the RAW log, I see that the rest of the time was spent creating the environment (this time is not spent on Circle-CI and Cirrus-CI), and this happens every time again.

In total: 32.02 seconds! What? Where did 1 minute 11 seconds come from? Running of integration tests - 17.58 seconds.Installing dependencies through npm - 7.16 seconds.