Cost-efficiency is one of the main pillars of the Serverless Well-Architected framework. Read-intensive applications can save money and improve efficiency by using cache systems. AWS Lambda’s internal memory could be used as a caching mechanism. A Lambda container remains alive after an invocation is served, even if it stays idle for some time. Whatever was loaded in the container’s memory will remain there for the next invocations.

The most common integration type for AWS API Gateway is with Lambda functions. The API service can integrate with virtually any other service that accepts HTTP requests, though. This opens up possibilities to use the API Gateway as a proxy to database queries, without any compute layer such as a Lambda function. The direct integration between API and database is perfect when Lambda serves only as an intermediator.

Dashbird, centralised observability and incident detection platform for serverless applications. Team Dashbird is proud to announce that we have achieved the AWS Lambda Ready designation, part of the Amazon Web Services (AWS) Service Ready Program. This designation recognizes that Dashbird’s serverless monitoring and debugging platform has demonstrated successful integration with AWS Lambda.

Both DynamoDB and MongoDB are NoSQL databases, but the similarities probably end there. In this article, we cover their strengths and weaknesses in 8 basic categories, so that you can decide which one suits best your needs. While the data model behind Mongo is more flexible for storage and retrieval, Dynamo is stronger in terms of scalability, consistent performance under heavy load, and infrastructure abstraction.

We recently wrote about the reasons why serverless apps fail and explored some ideas to make architectures more resilient and scalable. Some of these architectural designs can become expensive if we don’t consider the financial impacts of architectural decisions. With proper care and consideration to this aspect, it is possible to achieve the same value in terms of scalability and resiliency while keeping costs at a manageable level.

There is an interesting discussion going on around how Serverless is more of a spectrum rather than a binary choice. The move towards the Serverless-end of the cloud spectrum builds upon a decades-old trend, which is why Serverless is here to stay.

We’ve been monitoring 100,000’s of serverless backend components for 2+ years at Dashbird. In our experience, Serverless infrastructure failures boil down to: These isolated faults become causes of failure due to dependencies in our cloud architectures (ref. Difference of Fault vs. Failure). If a serverless Lambda function relies on a database that is under stress, the entire API may start returning 5XX errors.

Dashbird, a platform for serverless application monitoring, has raised $2.1 million in a seed round. The investment was led by Paladin Capital Group, with participation from Passion Capital, Icebreaker.vc and Lemonade Stand.

We recently wrote about why serverless applications fail and how to design resilient architectures. Being able to detect early-stage failure indicators can be invaluable. With proper monitoring, developers move from waiting for the system to crash and adopt a more proactive attitude in managing resource allocation and architecture design to avoid bottlenecks and performance degradation.

Cloud applications don’t just run flawlessly by way of magic. Many things can go wrong, and rest assured some will go wrong at one point. For small teams, this can be cumbersome and take a toll at the development speed. A monitoring system will detect these issues on behalf of the development team, so that they can act accordingly. At Dashbird, we think there’s much more to it, though, than just detecting and alerting issues, especially for small teams of developers.