As the world is increasingly reliant on technology, software developers, cloud architects, and DevOps practitioners bear a responsibility similar to that of the health industry or to airplane pilots, for example. In this reality, cloud monitoring isn’t optional, it’s a matter of being professional. What is optional, however, is what monitoring solution to go for. Obviously, the one that best fits your specific needs but which one is it?

Non-Fungible Tokens, or short NFTs, are all the rage right now. Everyone and their pets are starting an NFT project. Some people got rich from using NFTs; others did not. Some say it’s the savior that will rip the power away from big corporations and give it back to the creators; others say it’s just a giant pyramid scheme.

In a serverless application, AWS Lambda functions are typically invoked by JSON-formatted events from other AWS services—like API Gateway, S3, and DynamoDB—and respond with JSON-formatted payloads. Having visibility into these function request and response payloads can provide context around your function invocations and help you uncover the root causes of Lambda function failures.

Python, used in around 53% of all Lambda functions, is the most popular language for doing Serverless. In this article, you’ll get an overview of the need-to-knows for error handling Python in AWS Lambda.

In recent times cloud computing has played a significant role in various domains. In this blog, we will look at how Serverless360 helps these domains fulfill their business needs. We will explore a global insurance provider’s business need with regional offices in several territories and partners in many countries who need to manage policies and contracts and submit claims from different countries to the customer to reduce the processing overhead and maximize automation opportunities.

Here’s a quick roundup of the newest product features, resources, and events from Lumigo.

It started with a simple question: Why did one query take 10 seconds, while another almost identical query took 5? At Honeycomb, we use AWS Lambda to accelerate our query processing. It mostly works well, but it can be hard to understand and led us to wonder: What was really going on inside this box called Lambda? These questions kicked off the development of CONCURRENCY, a new aggregate in the Query Builder that lets us look at how many spans are active at once.

AWS Graviton2 processors use the Arm architecture to provide high-efficiency, low-cost computing. AWS already offers the ability to provision EC2 instances powered by Graviton2, and Datadog is proud to partner with them for the launch of new Graviton2 compute resources for Lambda functions. In this post, we’ll discuss how Datadog can provide deep visibility into your Lambda functions across whichever platform you’re using.

Modern computing has come a long way in the last couple of years and the introduction of new technologies is only accelerating the rate of advancements. From the immense compute power at our disposal to lightning-fast networks and ready-made services, the opportunities are limitless. In such a fast-paced world, we can’t ignore economics.

AWS just announced support for AWS Lambda functions powered by AWS Graviton2 processors. These are 64-bit Arm-based processors that are custom built by AWS and offer a better price to performance ratio. In this post, let me take through what we have learnt about this new option and what it means for you.