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This post was originally published in JAXenter.com.
Serverless is a relatively novel concept and cloud architectural model but has been advancing very quickly over the past 5 years. In this article, we’ve compiled a list of recent changes that are likely to shape how development teams use Serverless in practice.
In this article, we’ll be heavily focussing on AWS serverless services. The cloud provider has been investing heavily in the advancement of Serverless. Many of the factors behind the trends we see are affected by this.
With API Gateway HTTP API now generally available, it becomes easier and cheaper for developers to use an API Gateway privately to connect multiple cloud components while still keeping a healthy level of decoupling and black-box design. This is an important architectural practice that is part of the good practices around the Serverless trilemma.
DynamoDB is the leading serverless database offering right now on the market. Although it attracted some bad press in the past, the AWS team did an outstanding job over the past two years and most of its limitations are now gone.
For development teams that are still concerned about vendor lock-in, AWS has launched Cassandra Serverless. When generally available, it will be a compelling reason to move towards a serverless persistence model. Since the application would be tied to an open-sourced database API, a migration to another infrastructure would be facilitated in comparison with DynamoDB.
The argument that the Serverless computing model was too expensive for low-value, high-volume workloads will have a hard time holding up now that Fargate offers a Spot versionwith up to 70% savings. Fargate is already a great tool, but it would be amazing if we ever see a Lambda Spot as well.
AWS is pushing forward the EventBridge model, having recently released the Schema Registry in general availability. It greatly simplifies the process of building serverless event-driven data pipelines and will be a compelling reason for Architects, Developers, and CTOs to push its adoption for more resilient and easier to maintain architectural designs.
Speaking of architectural design improvements, the Well-Architected framework is getting traction among the Serverless developer community. To support the Operational Excellence pillar, Dashbird has launched a centralized monitoring tool for multiple cloud resources with issue detection, automated alerting, and best-practices insights to improve the architectural design. If you don’t want to be left behind, check it out now for free, no credit card required.
Today we are announcing a new, updated pricing model and the end of free tier for Dashbird.
In this article, we’re covering 4 tips for AWS Lambda optimization for production. Covering error handling, memory provisioning, monitoring, performance, and more.
In this article we’ll go through the ins and outs of AWS Lambda pricing model, how it works, what additional charges you might be looking at and what’s in the fine print.
Dashbird was born out of our own need for an enhanced serverless debugging and monitoring tool, and we take pride in being developers.
Dashbird gives us a simple and easy to use tool to have peace of mind and know that all of our Serverless functions are running correctly. We are instantly aware now if there’s a problem. We love the fact that we have enough information in the Slack notification itself to take appropriate action immediately and know exactly where the issue occurred.
Thanks to Dashbird the time to discover the occurrence of an issue reduced from 2-4 hours to a matter of seconds or minutes. It also means that hundreds of dollars are saved every month.
Great onboarding: it takes just a couple of minutes to connect an AWS account to an organization in Dashbird. The UI is clean and gives a good overview of what is happening with the Lambdas and API Gateways in the account.
I mean, it is just extremely time-saving. It’s so efficient! I don’t think it’s an exaggeration or dramatic to say that Dashbird has been a lifesaver for us.
Dashbird provides an easier interface to monitor and debug problems with our Lambdas. Relevant logs are simple to find and view. Dashbird’s support has been good, and they take product suggestions with grace.
Great UI. Easy to navigate through CloudWatch logs. Simple setup.
Dashbird helped us refine the size of our Lambdas, resulting in significantly reduced costs. We have Dashbird alert us in seconds via email when any of our functions behaves abnormally. Their app immediately makes the cause and severity of errors obvious.