Cassandra, DataStax, ScyllaDB, CosmosDB, RedShift - they all scale horizontally and with you will pay more as you add nodes - even if the SW is free, the compute time is not. Use Gatling to forecast your budget needs so you don’t surprise your CFO.
The next generation of React, aka Fiber, is eagerly anticipated. Expero's front-end team chimes in with their first impressions. If you’re like us, you’re eagerly awaiting the release of the new version of React (commonly referred to as React Fiber). We don’t intend to comprehensively go into the differences between React Fiber and the current React architecture (code named React Stack). However, when upgrading React, explicitly deprecated features tend to be pretty straightforward and easily called out with tooling like eslint. Still, some changes can be more insidious as they may have side effects that will be difficult to spot or reliably reproduce.
In this blog post, I'll discuss the process of building a micro service that is backed by a graph database and the technologies leveraged to accomplish it. I'll be building this microservice in Java using Maven for its declarative dependency management and build process and Dropwizard for its straightforward architecture and configuration, and then connect everything up to an Apache Tinkerpop enabled Graph Database.
We get asked that question a lot given our early customer work with Titan evaluations, participation in the JanusGraph project and usage of Apache TinkerPop while concurrently being a premier DataStax Graph partner.
As a user researcher, I’m always inclined to say, “Test everything, all the time!” when people ask, “What/when/how should we validate with users?” That’s my pie in the sky: the place where there’s all the time and all the budget in the world to get every last detail or spec just right for the good of the user, the product, and, ultimately, the business. But that’s not real life. Projects run on strict budgets and tight timelines, and there’s not always a lot of wiggle room.
Do you remember the first time you saw a commercial about “the Cloud?” That was one of the pivotal moments for technology buzzwords going mainstream. It’s been a nonstop thrill ride since then: Web 2.0. Internet of Things. Big Data. Machine Learning. Like “the Cloud,” the term “machine learning” is thrown around a lot, but it’s not entirely clear who it is useful to. People who follow it are aware that machine learning techniques were used by Google to create an unstoppable Go playing machine, and that it allows computers to drive with abilities getting closer to human drivers by the day.
Product owners and stakeholders have a tendency to skip over discovery research and go straight to design—and then skip over validation research and go right to release. One of the main drivers behind this tendency is the fact that looking at designs is fun. Looking at numbers and bulleted lists of findings is not (as much) fun (for stakeholders). With designs, they get to see their product progressing and growing from inception to build. Data is more behind-the-scenes; it may drive design, but so what?
What are the next big trends in UX? At our recent Expero Summit, we discussed many advances that promise to transform how users interact with technologies. As augmented reality and other technologies take substantive form, it’s more and more about what the user needs from these amazing technologies and less about how cool the technology actually is. It’s a given that the technology is only going to get cooler. What’s not as obvious is whether the user is ready for it.
OrientDB is one of several popular graph data stores on the market today. It provides a multi-model approach with the powerful nature of a graph database and the flexibility of a document data store. If you have decided to build out your multi-tenant application on top of OrientDB, you are in luck as it has several built-in, out-of-the-box methods for handling multi-tenancy.
How do you handle customer #2? You delivered an MVP of some hosted software for customer #1. Your brother-in-law knows a guy who has a similar problem and after a lunch meeting, now you need to add customer #2 to your incubating SaaS tool. Of course customer #1 and customer #2 shouldn’t be able to see each other’s data, but you don’t necessarily want to install and configure everything all over again just because you added another customer.
Neo4j is the most popular graph data store available today. It leverages graph technologies to help build modern high-performing applications, but it does not have any native multi-tenant support. However, you may have decided to build out your multi-tenant application and that Neo4j is the right graph data store to fit your needs. In any multi-tenant system, the trick (from a data-store side) really comes down to how to isolate one tenant’s data (physically or logically) from another tenant’s.
So you’re going to build a multi-tenant application and now it’s up to you to figure out how to make it all work. Ask any software engineer who has built one and they will tell you that multi-tenant applications are inherently more complicated than single-tenant applications. That complexity comes from the added overhead required to ensure that your tenants’ data are secured and isolated from one another (e.g., Tenant 1 can’t see Tenant 2’s customer list) and that large tenants don’t adversely affect other tenants in the same environment (e.g., Tenant 1 does not use all the resources, thereby slowing the performance for Tenant 2). The overhead caused by these requirements may take the form of either operational or developmental complexity, but the key to building an effective system in any multi-tenant scenario is to reduce that complexity.
We all know how awesome user personas are. They help all the king’s men—designers, researchers, product owners, stakeholders, investors, on and on—understand a particular user type’s behaviors, needs, goals and motivations.
As Agile principles and Lean methodologies continue to take center stage in product management and strategy, it’s easy to get caught up in daily scrums and design iterations and shoot right past the user research (UR).
If you know anything about Expero, you know we specialize in solving “complex problems.” This means we’re not working on your average brochure website or e-commerce app. We’re tackling apps and softwares targeted to niche domains with expert end-users who have very specific needs and goals to solve their very complicated problems.
Over the past few months I got my first chance to work with Kafka Streams. For those who don’t know, Kafka Streams is a new feature in Kafka 0.10.0 that adds stream processing capabilities into the existing Kafka platform.
Continuous Discussions is a weekly online panel discussion which is sponsored by Electric Cloud and discusses a variety of topics around Agile, Continuous Delivery and DevOps with a range of different speakers.
In this post we will examine a simple scenario involving the deployment of a .NET based web application to an Azure Web App using Azure Key Vault for secrets management. All the code used for this blog post can be found here.
As a user researcher, I am, of course, an evangelist of all things research. I love research! I love reading everything and learning everything and understanding everything I possibly can about a subject. Infographics are neat but I want more more more information! Give it to me—all of it! As a user researcher, I also, of course, realize that not everybody feels the same way. Often including clients.
Q: I am the only Information Architect + Designer in an IT Solutions company. I am also fresh out of college. How can I introduce some processes to work with the programmers / coders who are working on Enterprise Solutions?
Q: Breadcrumb trails seem to be common navigation aids. But in which ways and how often are they really used? Is it enough to rely only on the breadcrumb trail to tell the user where she is in the site hierarchy (for example when she arrives via a deep link), or do you still need to do that with headings, etc.?
Q: Our web-based application currently requires two logins to use: one for the application and one for each module under the application. I’m having trouble convincing others on the team that we should just have one login. What do you think?
Q: The web team at our company wants me to figure out the best way to add a 6th level of navigation to our website. Is the best way to do this to add this level of navigation sub-nested under the 5th level on the left-hand side of the page?