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DevOps

The latest News and Information on DevOps, CI/CD, Automation and related technologies.

Track the status of your SLOs with the new monitor uptime and SLO widget

Service level objectives are an important tool for maintaining application performance, ensuring a consistent customer experience, and setting expectations about service performance for both internal and external users. We are very pleased to announce the availability of a new monitor uptime and SLO widget that makes it simple to monitor the status of your SLOs and communicate that status to your teams, executives, or external customers.

When to use Lambda layers

AWS introduced Lambda Layers at re:invent 2018 as a way to share code and data between functions within and across different accounts. It’s a useful tool and something many AWS customers have been asking for. However, since we already have numerous ways of sharing code, including package managers such as NPM, when should we use Layers instead? In this post, we will look at how Lambda Layers works, the problem it solves and the new challenges it introduces.

Tackle Serverless Observability Challenges with the New Stackery-Epsagon Integration

Stackery is a tool to deploy complete serverless applications via Amazon Web Services (AWS). Epsagon monitors and tracks your serverless components to increase observability. Here’s how they can not only work together but improve each other. Let’s start with a scenario: it’s late in the day on Thursday, traffic to your site is way up, and you have reports of problems.

GTC 2019 Accelerating AI Performance, Ease of Use with Ubuntu and NVIDIA DGX

Carmine Rimi of Canonical and Tony Paikeday, NVIDIA, discuss the need for flexibility, performance, and ease of use in AI development solutions. They continue to address how NVIDIA's DGX platforms and Ubuntu emphasize accessibility for these data scientists and engineers, allowing them to get up and running quickly with familiar technology.

Deploy Your First Deep Learning Model On Kubernetes With Python, Keras, Flask, and Docker

This post demonstrates a *basic* example of how to build a deep learning model with Keras, serve it as REST API with Flask, and deploy it using Docker and Kubernetes. This is NOT a robust, production example. This is a quick guide for anyone out there who has heard about Kubernetes but hasn’t tried it out yet. To that end, I use Google Cloud for every step of this process.

Understanding the Kubernetes Node

With over 48,000 stars on GitHub, more than 75,000 commits, and with major contributors like Google and Red Hat, Kubernetes has rapidly taken over the container ecosystem to become the true leader of container orchestration platforms. Kubernetes offers great features like rolling and rollback of deployments, container health checks, automatic container recovery, container auto-scaling based on metrics, service load balancing, service discovery (great for microservice architectures), and more.

Developer's Guide to Cognito with Stackery

Cognito is AWS’s cloud solution for authentication – if you’re building an app that handles users with passwords, you can use AWS to handle the tricky high-risk security issues related to storing login credentials. No need to go it alone! Pricing is based on your number of monthly active users, and the first 50k users are free. For apps I’ve worked on, we would have been very pleased to grow out of that free tier.