In recent years, monoliths have lost favor as microservices increased in popularity. Conventional wisdom says that microservices, and distributed systems in general, are hard to operate: There are often too many dependencies and tunables, multiple moving parts, and operational complexity.
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.
We had a blast at this year’s SREcon in Brooklyn, NY. The three-day event included meeting with integration partners and deepening our understanding of website reliability from a DevOps perspective.
cf-runagent is a component for triggering remote agent runs using the CFEngine network protocol. It does not allow for arbitrary commands to be executed, but rather asks the remote host to run the policy it already has. To trigger cf-runagent from other systems or web interfaces, you want to be able to run it as non-root.
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 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?
By monitoring the end-to-end user experience, IT professionals gain keen insights into application performance from the customer's perspective.
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.
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.
