Why You Should Go Serverless for DevOps

Over the last decade, DevOps has become an important part of software engineering culture, influenced by the wide adoption of microservices, containers and cloud computing. A recent step in the evolution of cloud-based and microservice architecture is the serverless computing – a code execution model where the cloud provider takes total responsibility for the operating system and hardware management.


Announcing: Epsagon, First Provider of Distributed Tracing for AWS AppSync

Today Epsagon is announcing the integration of its automated, distributed tracing solution for monitoring and troubleshooting cloud microservices (containers and serverless) with AWS AppSync, which simplifies application development by letting developers create a flexible API to securely access, manipulate, and combine data from one or more data sources.


The why, when and how of API Gateway service proxies

Serverless Hero Yan Cui explains when and why you should use API Gateway service proxies, and introduces an open source tool to make it easy to implement. One of the very powerful and yet often under-utilized features of API Gateway is its ability to integrate directly with other AWS services. For example, you can connect API Gateway directly to an SNS topic without needing a Lambda function in the middle. Or to S3, or any number of AWS services.


Serverless Framework Flaws: 7 Common Security Threats to Look Out For

According to a study by Gartner, 2019 will be the year of the cloud. The study estimates that global public cloud-related revenues will climb 17.5% this year. While it seems like every year is the “year of the cloud,” there is something about this year in particular that sets it apart; the year of serverless. The introduction of the serverless framework is one of the most logical steps in the evolution of the cloud.


Automatically trace MongoDB commands from AWS Lambda

If you’re using AWS Lambda to send commands to MongoDB Atlas (or considering it), IOpipe recently added MongoDB auto-tracing to help developers gain real-time visibility and faster debugging for their database connections. One of the biggest challenges for developers and engineering teams building serverless applications on AWS Lambda is gaining whole event observability — particularly when it pertains to functions that make calls outside of the AWS ecosystem.


Zipkin or Jaeger? The Best Open Source Tools for Distributed Tracing

Since the beginning of software programming, developers and operations teams have had to find and solve problems. They’ve had to attend to defects (on different dev environments) and incidents (on production), investigate their root cause and prepare a solution according to their findings.


Tracing for Everyone: Business Flows Simplified

When we started designing our OpenTracing-compatible distributed tracing engine Otto, we didn’t want to limit it to only AWS services. Therefore, we provided a general infrastructure for linking different invocations connected to each other via traces. What does this mean? Well, let’s start by defining what a “trace” is: A trace is set of invocations that are connected to each other in a flow.

What is Thundra?

Thundra offers full observability for AWS Lambda environments with aggregated logs, metrics, and distributed and local traces. It helps you discover bottlenecks in your serverless environment and take rapid actions when unexpected situations occur. You can minimize your cold starts, understand the root cause of the errors in your AWS Lambda functions or any other resources and see where exactly things went wrong.

Monitor Lambda cold start durations with CloudWatch

When you look at an X-Ray trace for a Lambda cold start, you will see an Initialization subsegment. This subsegment represents “the function’s initialization code that is run before the handler”. This is where the runtime would resolve any dependencies, or initialize global variables. These are executed only once, so they don’t have to run on every invocation. The more dependencies you have, the longer this initialization step takes.