Google Cloud Platform is growing quickly, providing solutions for everything from cloud storage to managed Kubernetes to serverless computing. Since Google App Engine launched in 2008, Google’s suite of serverless products has expanded to help enterprises accelerate application development without having to manage or scale their own infrastructure.
A while ago, a merry bunch on Reddit at the subreddit r/WallStreetsBets (WSB) took on Wall Street. Ironically, through an app called Robinhood. As Alanis Morisette would say, “A little too ironic, don’t ya think?” You had to be in there and in the know at the right time to benefit from the situation. That’s why we built a serverless API to keep track of all the hot and trending stock chats on WSB, that will notify you when the next GME is about to blow up.
In 2021 it’s common practice for businesses to use a pay-as-you-go/use pricing model. It’s no different with Amazon. It’s also the primary reason why this article is such an important read for all those looking to reduce their AWS Lambda costs. In this article, we will go over six actionable strategies to optimize the cost relating to our AWS Lambda usage. One of the main reasons for choosing to move into the cloud is the ability to reduce costs.
This piece was originally three different blogs but is now one. In this piece, we lay out three ways you can improve your AWS Lambda performance. So much has been written about Lambda cold starts. It’s easily one of the most talked-about and yet, misunderstood topics when it comes to Lambda. Depending on who you talk to, you will likely get different advice on how best to reduce cold starts.
Serverless computing is becoming increasingly popular in software development due to its flexibility of development and the ability it affords to test out and run solutions with minimal overhead cost. Vendors like AWS provide various tools that enable businesses to develop and deploy solutions without investing in or setting up hardware infrastructures. In this post, we’ll cover the many different services that AWS provides for supporting serverless computing.
For decades, application development and operations teams have struggled with the best way to generate, collect, and analyze telemetry data from systems and apps. In 2010, we discussed our approach to telemetry and tracing in the Dapper papers, which eventually spawned the open-source OpenCensus project, which merged with OpenTracing to become OpenTelemetry.
Cloud MSPs or managed service providers are great at helping companies properly leverage the public cloud, typically handling cloud strategy, implementation and day-to-day operations for their customers. However, when it comes to things like customizable billing, analyzing cloud spend per customer, optimizing cost and increasing profit margins, MSPs are over-burdened with complex, manual processes.
We’re officially cool! Dashbird is extremely proud to be named as a Cool Vendor by Gartner in Monitoring, Observability, and Cloud Operations in their 28 April 2021 report on “Cool Vendors in Monitoring, Observability and Cloud Operations”. “Dashbird provides a novel approach to observability for serverless applications that run inside an AWS environment.
Datadog’s support of OpenTelemetry—a vendor-agnostic, open source set of APIs and libraries for collecting system and application telemetry data—has helped thousands of organizations implement monitoring strategies that complement their existing workflows. Many of our customers leverage OpenTelemetry for their server- and container-based deployments, but also need visibility into the health and performance of their serverless applications running on AWS Lambda.
