To get some serious work done, we usually need to prepare for it. “Baby steps first,” they say. In our niche, these “baby steps” would be countless small jobs that need to be done before we can start with our main project. Proper preparation(try saying this 5 times fast) is the key to success, but after we’ve achieved our primary goal, there will always be something to do to keep it steady and flowing.

Welcome to the Serverless world. One of the first things you’ll hear about is AWS Lambda - and you’ll continue to keep hearing about it! While architecture can be serverless without Lambdas involved, it’s very often the key component within a serverless application. In the first post of this 3-part AWS Lambda Handbook series, we run through what is AWS Lambda, dialling back to basics with the various terminology, how to create a Lambda function and how to run it.

We have explored how we can deploy Machine Learning models using AWS Lambda. Deploying ML models with AWS Lambda is suitable for early-stage projects as there are certain limitations in using Lambda function. However, this is not a reason to worry if you need to utilize AWS Lambda to its full potential for your Machine Learning project. When working with Lambda functions its a constant worry about the size of deployment packages for a developer.

In this article I’ll be sharing my own lessons learned with Dashbird in building reliable Well-Architected serverless applications and the highest impact areas to focus on no matter where you are in the Serverless journey.

Serverless applications, more often than not, have logic distributed over multiple functions and services, which with growth and agents and wrappers attached, can get more complex and costly. This is where Serverless monitoring comes in to help. But what is Serverless monitoring? Serverless monitoring allows developers to gain important insight on what happens during each execution and event, errors become more easily visible and measuring resource consumption for each invocation is possible.

If you’ve heard of the term “serverless architecture” but you have no idea what it means, don’t feel bad. This buzzword (buzz-phrase?) has been on the rise for the past few years, and it doesn’t look like it’s going to stop. More and more cloud companies are trying to promote serverless architectures for businesses. There are plenty of benefits to using a serverless architecture for your business.

Want to know what actually goes on under the platform and behind the screens at Dashbird? We recently sat down for a Q&A with our CTO, Marek Tihkan, on leading and managing an engineering team. Today, we speak to Alex, one of the engineers on the Development team and the brain and elbow grease behind our newly launched Dashbird Atlas real-time 3D map of your entire serverless environment.

We’ve noticed interesting threads floating around the internet asking how would you explain serverless to a toddler. As it happens, we just turned three years old and to mark the occasion, we decided to take up the challenge and wrote a bedtime story, for serverless enthusiasts of all ages, about how serverless came to be, from the very beginning. It is a magical tale of the ingenious, life-changing journey that got us to a new universe called Serverless.

Another year of empowering DevOps teams has passed and what a year it’s been! I’d like to take a moment to reflect on the journey, the milestones and challenges this past year encompassed. The last year has been our most transformational to date. We’ve had a huge amount of ups and downs and I’m incredibly proud to say that we got through it and our organization is more resilient, more aligned in our vision and closer as a result.

We’re pleased and honored to be part of the Serverless revolution - continuously innovating to make processes and day-to-day tasks for serverless users more efficient, seamless and enjoyable. So let’s get right into the new and exciting stuff now! Earlier this year, Dashbird launched the very well-received Insights Engine designed to encourage a proactive approach when building and operating serverless applications.