Introduction to Epsagon Service Maps (Part 1)

Service maps are a visual and interactive depiction of how the services interact with each other. They also provide critical health information (such as latency, number of errors, etc.) for each service. As more and more applications are getting deployed as microservices, service maps have become increasingly important. In this blog, we will explore the importance of service maps in an observability solution and cover the basics of this feature in Epsagon.


How We Improved Epsagon's Trace Search Using Epsagon

Dogfooding, aka “eating your own dog food”, is a common practice of organizations using their own products for real-world scenarios. Organizations that do it right enjoy the advantages of early-stage use-case validation, bug hunting, and feedback. Developers who actively use their own product gain confidence and a deeper understanding of their clients. Dogfooding is something we at the Epsagon team pride ourselves on.


Serverless Monitoring is No Longer Finding a Needle in a Haystack

At Luther.ai, we use AWS Serverless Stack and Kubernetes for all the core real-time pipelines, and it is a data-driven execution across all AWS Services — ECS, Lambda, SQS, Fargate, etc. With hundreds of services and thousands of invocations, each day presents significant complexity to configure, monitor, review logs, measure latency, etc. For configuration and CI/CD, we use the Serverless Framework for packaging and deploying AWS Lambda functions.


Introduction to Serverless Machine Learning (Part 2)

In the previous post of our Serverless Machine Learning mini-series, we discussed how to develop and package a predictive model using scikit-learn. This was to prepare a model that could be used in the future to deploy to AWS Lambda, allowing a developer to call your serverless machine learning model like an API end-point without the need to design and implement an entire API.

Observability at Scale: Analyzing Billions of Microservices | DeveloperWeek Enterprise

As more enterprises adopt cloud-native environments and with the growing complexity of infrastructures and systems, understanding your modern architectures is crucial. At scale, with thousands of microservices, visualization becomes critical to understand performance, flow, and the health of applications. and In order to properly scale and still obtain full control, you have to have the right observability strategy and tools. In this talk, we'll go over the challenges, the solutions, and the tools to truly achieve end-to-end observability and get you scaling with confidence.

Visualizing and Analyzing APIs and Microservices in Distributed Environments | API World 2020

Modern, distributed applications are often seen as a graph of nodes and edges, each node representing a container, a function, or an API service. At scale, with thousands of small microservices visualizing and analyzing becomes critical to understand performance, flow, and the health of our applications. To accomplish that we need to learn about observability, distributed tracing, popular tools and frameworks, and more. In this talk, we'll go over the challenges, the solutions, the approaches, and the tools to help you understand your APIs and microservices.

Serverless + DevOps: A Perfect Fit | DeveloperWeek Cloud 2020

Serverless - Devs love it as it enables them to move much faster, but Ops tend to be suspicious towards it as it entails “loss of control” over your infrastructure. When making the DevOps transformation, these worlds seem to collide. But serverless is actually a great fit with the DevOps culture, and it can even help you make the transformation.