Are your tests in Jira growing in complexity? Do you feel you could be more efficient with reusing tests? Does ensuring consistency and standards across projects still feel like a struggle with your existing test management tool? Enter Zephyr Scale, a structured and highly configurable test management solution for teams looking to advance their testing in Jira. Need to see it to believe it? Join us for a quick, around-the-app tour of Zephyr Scale.

In this article, we’re going to build a fun and simple gRPC server in Node.js. Then we’ll demonstrate how to use Insomnia to make gRPC requests on our server. First, let’s briefly cover some core tech concepts. If you’re already familiar with the basics, skip ahead to the tutorial or watch the video below.

whenever we go to a website, whether it's an online store to buy clothes or to check the status of our bank account, we need to type the URL into the browser. When you click on the relevant page, a request is sent to the server, and the server always responds with the HTTP three-digit code. This HTTP status code tells us if our request was successfully completed or whether there was an error that prevented the server from serving the content that users or visitors were trying to access.

In our world of streaming applications, developers are forever climbing a steep learning curve to stay successful with technologies such as Apache Kafka. There is no end to the debt and the detail you need to manage when it comes to Kafka - and particularly since it doesn’t come with guardrails to help you out, the stakes for making mistakes are high.

Chronicle, Google Cloud’s security analytics platform, is built on Google’s infrastructure to help security teams run security operations at unprecedented speed and scale. Today, we’re excited to announce that we’re bringing more industry-leading Google technology to security teams by integrating Chronicle with Looker and BigQuery.

Real-time analytics can keep you up-to-date on what’s happening right now, such as how many people are currently reading your new blog post and whether someone just liked your latest Facebook status. For most use cases, real-time is a nice-to-have feature that won’t provide any crucial insights. However, sometimes real-time is a must. Let’s say that you run a big ad agency.

Most companies offering any kind of service or product answer this question from consumers or potential clients all the time: "How much does it cost?" Or, the much harder question: "How much will it cost if I choose these services with these extras for my particular company/house/yard/situation, etc.?" The tough part is that pricing services or software usually involves too many variables.

Working with raw or unprocessed data often leads to poor decision-making. This explains why data scientists, engineers, and other analytic professionals spend over 80% of their time finding, cleaning, and organizing data. Accordingly, the ETL process - the foundation of all data pipelines - devotes an entire section to T, transformations: the act of cleaning, molding, and reshaping data into a valuable format.

Data warehouses are a particular kind of database. Learn how they are uniquely suited to analytics.

At Ably, we run a large scale production infrastructure that powers our customers’ real-time messaging applications around the world. Like in most tech companies, this infrastructure is largely software-based; also like in most tech companies, much of that software is deployed and runs in Docker containers.