Developing applications today comes with lots of choices and plenty to learn, whether you’re exploring serverless computing or managing a raft of APIs. In today’s post, we’re sharing some of our top videos on what’s new in application development on Google Cloud Platform (GCP) to find tips and tricks you can use.
This demo-packed session walks you through the use of Knative, our Kubernetes-based platform for building and deploying serverless apps. This session goes through how to get started with using Knative to further the goal of focusing on writing code. You’ll see how it uses APIs that are familiar from GKE, and auto-scales and auto-builds to remove added tasks and overhead. The demos show how Knative spins up prebuilt containers, builds custom images, previews new versions of your apps, migrates traffic to those versions, and auto-scales to meet unpredictable usage patterns, among other steps in the build and deploy pipeline. You’ll see the cold start experience, along with preconfigured monitoring dashboards and how auto-termination works.
The takeaway: Get an up-close view into how a serverless platform like Knative works, and what it looks like to further abstract code from the underlying infrastructure.
You have a lot of key choices to make when deciding how and which technology to adopt to meet your application development needs. In this session, you’ll hear about various options for running code and the tradeoffs that may come with your decisions. Considerations include what your code is used for: Does it connect to the internet? Are there licensing considerations? Is it part of a push toward CI/CD? Is it language-dependent or kernel-limited? It’s also important to consider your team’s skills and interests as you decide where you want to focus, and where you want to run your code.
The takeaway: Understand the full spectrum of compute models (and related Google Cloud products) first, then consider the right tool for the job when choosing where to run your code.
Kubernetes empowers developers by making hard tasks possible. In this session, we introduce Kubernetes as a workload-level abstraction that lets you build your own deployment pipeline, and starts with the premise that rather than making simple tasks easier. The session walks through how to deploy containers with Kubernetes, and configuring a deployment pipeline with Cloud Build. Deployment strategy advice includes using probes to check container integrity and connectedness, using configuration as code for a robust production deployment environment, setting up a CI/CD pipeline, and requesting that the scheduler provision the right resources for your container. It concludes with some tips on preparing for growth by configuring automated scaling using the requests per section (RPS) metric
The takeaway: Kubernetes can help you automate deployment operations in a highly flexible and customizable way, but needs to be configured correctly for maximum benefit. Help Kubernetes help you for best results.
There’s a lot of advice out there about APIs, so this session recommends focusing on what your goals are for each API you create. That could be updating or integrating software, among others. Choose a problem that’s important to solve with your API, and weigh your team and organization’s particular priorities when you’re creating that API. This session also points out some areas where common API mistakes happen, like version control or naming, and recommends using uniform API structure. When in doubt, keep it simple and don’t mess up how HTTP is actually used.
The takeaway: APIs have to do a lot of heavy lifting these days. Design the right API for the job and future-proof it as much as you can for the people and organizations who will use it down the road.
This session takes a top-to-bottom look at how we define and run serverless here at Google. Serverless compute platforms make it easy to quickly build applications, but sometimes identifying and diagnosing issues can be difficult without a good understanding of how the underlying machinery is working. In this session, you’ll learn how Google runs untrusted code at scale in a shared computing infrastructure, and what that means for you and your applications. You’ll learn how to build serverless applications that are optimized for high performance at scale, learn the tips and pitfalls associated with this, and see a live demo of optimization on Cloud Functions.
The takeaway: When you’re running apps on a serverless platform, you’re focusing on managing those things that elevate your business. See how it actually works so you’re ready for this stage of cloud computing.
Here’s a look at what serverless is, and what it is specifically on GCP. The bottom line is that serverless brings invisible infrastructure that automatically scales, and where you’re only charged for what you use. Serverless tools from GCP are designed to spring to life when they’re needed, and scale very closely to usage needs. In this session, you’ll get a look at how the serverless pieces come together with machine learning in a few interesting use cases, including medical data transcription and building an e-commerce recommendation engine that works even when no historical data is available. Make sure to stay for the cool demo from the CEO of Smart Parking, who shows a real-time, industrial-grade IoT system that’s improving parking for cities and drivers—without a server to be found.
The takeaway: Serverless helps workloads beyond just compute: learn how, why, and when you might use it for your own apps.
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