Testing practices are shifting left and right, shaping the way software engineering is done. In addition to the many types of tests described in this Deeper Look, test-driven development (TDD), progressive engineering and chaos engineering are also considered testing today. TDD TDD has become popular with Agile and DevOps teams because it saves time. Tests … continue reading
Rapid innovation and the digitalization of everything is increasing application complexity and the complexity of environments in which applications run. While there’s an increasing emphasis on continuous testing as more DevOps teams embrace CI/CD, some organizations are still disproportionately focused on functional testing. “Just because it works doesn’t mean it’s a good experience,” said Thomas … continue reading
A couple of years ago, there was a lot of hype about using AI and machine learning (ML) in testing, but not a lot to show for it. Today, there are many options that deliver important benefits, not the least of which are reducing the time and costs associated with testing. However, a hands-on evaluation … continue reading
AI and machine learning (ML) are finding their way into more applications and use cases. The software testing vendors are increasingly offering “autonomous” capabilities to help customers become yet more efficient. Those capabilities are especially important for Agile and DevOps teams that need to deliver quality at speed. However, autonomous testing capabilities are relatively new, … continue reading
Organizations are moving to continuous testing (CT) out of necessity because business competitiveness demands faster release cycles. In fact, teams can’t deliver on the promises of DevOps and CI/CD if testing isn’t part of continuous processes and the pipeline. Forrester Research VP and principal analyst Diego Lo Giudice and some of his colleagues, recently published … continue reading
DevOps and CI/CD practices are maturing as organizations continue to shrink application delivery cycles. A common obstacle to meeting time-to-market goals is testing, either because it has not yet been integrated throughout the SDLC or certain types of testing are still being done late in the SDLC, such as performance testing and security testing. Forrester … continue reading
Cindy Sridharan’s popular “Distributed Systems Observability” book published by O’Reilly claims that logs, metrics, and traces are the three pillars of observability. According to Sridharan, an event log is a record of events that contains both a timestamp and payload of content. Event logs come in three forms: Plaintext: A log record stored in plaintext … continue reading
Traditional application performance management was built from the ground up to be for infrastructure operations and the emergent DevOps teams. They were not designed for product and engineering teams. But if you’re a developer, and you’re writing code to deliver to your customers in the form of an application or a service, you’d likely want … continue reading
Observability is the latest evolution of application performance monitoring, enabling organizations to get a view into CI/CD pipelines, microservices, Kubernetes, edge devices and cloud and network performance, among other systems. While being able to have this view is important, handling all the data these systems throw off can be a huge challenge for organizations. In … continue reading
In today’s modern software world, applications and infrastructure are melding together in different ways. Nowhere is that more apparent than with microservices, delivered in containers that also hold infrastructure configuration code. That, combined with more complex application architectures (APIs, multiple data sources, multicloud distributions and more), and the ephemeral nature of software as temporary and … continue reading
People have come to expect a certain level of performance from their applications, whether using a consumer application, such as a retail website, or using a business application to get their jobs done. But most monitoring solutions have not adapted to this collapsing of the consumer and business worlds into one, making it difficult for … continue reading
Gartner research describes three things that are required for a solution to be categorized as application performance monitoring: application discovery, diagnostics and tracing; data analysis; and digital experience monitoring. Digital experience monitoring, or DEM as it is sometimes called, is different from the other types of monitoring because it takes an outside-in view of the … continue reading
Monitoring your applications comes in many forms. There’s traditional application performance management, which begat AIOps, which begat observability. But are there really any differences? If so, where are they? Some believe these are marketing terms used to differentiate tools. Others point to it as more of an evolution of monitoring. All that said, the performance … continue reading
APM, as Gartner defines it in its Magic Quadrant criteria, is based on three broad sets of capabilities, and in order to be considered by Gartner an APM vendor, you have to have all three. Charley Rich, Gartner research director and lead author of its APM Magic Quadrant, explained: The first one is digital experience … continue reading
