Operations | Monitoring | ITSM | DevOps | Cloud

Managing EU VAT with Stripe for a SaaS is not *that* hard

This is a short follow up to last week's story on Stripe Billing as a reader on Hackernews commented that it seemed we didn't handle VAT. We do, but I just left it out of the story. For those not familiar with handling EU VAT for SaaS companies: It's a bit of counter intuitive jungle. At least that's what some dedicated SaaS startups make you believe. Also, Stripe does not handle it at all. They give you a { taxRate: null } field for you to fill.

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.

Identification and Reconciliation

90 seconds with ServiceNow’s Identification and Reconciliation engine, a key tool to your complete CMDB. Configuration data is spread enterprise-wide, spanning multiple systems and sources, each with its strengths and weaknesses. To create a centralized database that can be used confidently by all teams this cornucopia of data needs to be pruned, consolidated, and maintained.

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.

Entity Extraction with spaCy

Entity extraction is, in the context of search, the process of figuring out which fields a query should target, as opposed to always hitting all fields. The reason we may want to involve entity extraction in search is to improve precision. For example: how do we tell that, when the user typed in Apple iPhone, the intent was to run company:Apple AND product:iPhone? And not bring back phone stickers in the shape of an apple?

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.

eG Innovations Named as a Top 10 Global Vendor for Continuous Application Performance Management

Continuous application performance management (CAPM) is a key focus area in the enterprise IT segment. With organizations increasing their focus on digital business services, monitoring and managing the application performance becomes paramount. When a digital business service is slow or down, it impacts the business adversely.