The Software Development Life Cycle (SDLC) has multiple stages, which include some testing phases. System testing and acceptance testing are integral parts of the overall testing lifecycle. In system testing, we test the system as a whole. We integrate all the modules and components and verify if the system meets the expectations or not. Once we have successfully tested the system, the entire application can be handed over to the users to check for its acceptability.

The amount of big data that enterprises churn out is simply staggering. All this information is worthless unless organizations unlock its true value for analytics. This is where ETL proves useful. Traditional ETL (extract, transform, and load) remains the most popular method for moving data from point A to point Z. It takes disparate data sets from multiple sources, transforming that data to the correct format and loading it into a final destination like a data warehouse.

Spending two decades in the middleware field has given me deep insight into the evolution of this technology domain. I began my career as a software engineer in a platform group, building reusable components using technologies like object linking and embedding (OLE), the distributed component object model (DCOM) and common object request broker architecture (CORBA).

As a Solutions Engineer here at Kong, one question that frequently comes across my desk is “how can I transform a Kong logging plugin message into a format that my insert-observability-stack-here understands, i.e. ELK, Loki, Splunk, etc.?” In this blog, I’m going to show you how to easily accomplish converting a Kong logging payload to the Elastic Common Schema. In order to accomplish this task, we’re going to be running Kong Gateway in Kubernetes and using two Kong plugins.

At ObservabilityCON, we announced our first step towards launching a native integration between Grafana k6 load testing and Grafana Tempo tracing (k6 x Tempo) in Grafana Cloud. We created k6 x Tempo to help dev, testing, and operation teams analyze their performance test results more effectively and proactively improve the reliability of their business-critical applications.

From time to time, Kong’s Brad Drysdale and Ahmed Koshok exchange emails about the latest trends in tech. In this exchange, Brad and Ahmed discuss the continued quest for more innovation faster, the role of automation in API strategy, and more. from: Brad to: Ahmed date: Oct. 29, 2022, 6:58 PM subject: Elements for Building Cloud Native Applications Greetings from Australia, Ahmed!

Want to switch to GA4 but still have concerns about the platform? You’re not alone. We’ve talked to 40+ marketers about their most common concerns and how to overcome them.

Development is more reliable and streamlined with Docker. With Docker, developers can design fast, easy, and portable applications - both on desktops and in the cloud - by terminating redundant, mundane configuration tasks. Furthermore, to UIs, CLIs, APIs, and security, Docker's integrated end-to-end platform is built to incorporate across the entire application delivery pipeline. In Docker Containers, the HEALTH CHECK instruction determines their health status.

Data security (or data protection) is a term often used in the context of analytics and business intelligence (BI). It encompasses a number of different policies, processes and technologies that protect an company's cyber assets against data breaches and threats. But what does all of that really mean, in relation to BI specifically?

Managers of data teams add value through alignment. Learn the essential criteria for evaluating the success of data team managers.