Systems run into problems all the time. To keep things running smoothly, we need to have an error monitoring and logging system to help us discover and resolve whatever issue that may arise as soon as possible. The bigger the system the more challenging it becomes to monitor it and pinpoint the issue. And with serverless systems with 100s of services running concurrently, monitoring and troubleshooting are even more challenging tasks.

While we know the many benefits of going serverless – reduced costs via pay-per-use pricing models, less operational burden/overhead, instant scalability, increased automation – the challenges of going serverless are often not addressed as comprehensively. The understandable concerns over migrating can stop any architectural decisions and actions being made for fear of getting it wrong and not having the right resources.

We’ve seen time and again how serverless architecture can benefit your application; graceful scaling, cost efficiency, and a fast production time are just some of the things you think of when talking about serverless. But what about serverless security? What do I need to do to ensure my application is not prone to attacks? One of the many companies that do serverless security, Protego, came up with an analogy I really like.

Engineering time is a precious resource. We often have to balance many tasks and often conflicting priorities. In this article, we’ll look at ten activities for which allocating more time can be beneficial. Let’s learn from the mistakes of others.

Handling large images has always been a pain in my side since I started writing code. Lately, it has started to have a huge impact on page speed and SEO ranking. If your website has poorly optimized images it won’t score well on Google Lighthouse. If it doesn’t score well, it won’t be on the first page of Google. That sucks.

Function as a service (FaaS) offerings like AWS Lambda are a blessing for software development. They remove many of the issues that come with the setup and maintenance of backend infrastructure. With much of the upfront work taken out of the process, they also lower the barrier to start a new service and encourage modularization and encapsulation of software systems. Testing distributed systems and serverless cloud infrastructures.

Here’s everything you need to know to get started with Dashbird – the complete solution for End-to-End Infrastructure observability , Real-time Error Tracking, and Well-Architected Insights. When working with AWS, One cannot emphasize enough the architectural best practices for designing workloads. One of those best practices is to design the solution in such a way that the monitoring of infrastructure and troubleshooting of errors and problems is achieved effortlessly.

As a startup, we always want to focus on the most important thing — to deliver value to our customers. For that reason, we are a huge fan of the serverless options provided by AWS (Lambda) and GCP (Cloud Function) as these allow us to maintain and quickly deploy bite-size business logic to production, without having to worry too much about maintaining the underlying servers and computing resources.

AWS Simple Storage Service (S3) is by far the most popular service on AWS. The simplicity and scalability of S3 made it a go-to platform not only for storing objects, but also to host them as static websites, serve ML models, provide backup functionality, and so much more. It became the simplest solution for event-driven processing of images, video, and audio files, and even matured to a de-facto replacement of Hadoop for big data processing.