Ephemeral Test Environments

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rakhirhif8963
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Joined: Mon Dec 23, 2024 3:15 am

Ephemeral Test Environments

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Together, TestOps and GitOps make testing processes more efficient, aligning them with modern agile development practices and increasing reliability.

The emergence of ephemeral test environments is a game changer. These environments are created on-demand and short-lived, providing a cost-effective way to test applications in a controlled environment that closely mimics production. Kubernetes makes creating and terminating these environments efficient and scalable. Testkube, for example, allows teams to test efficiently and reliably in these dynamically created environments, providing a fast feedback loop with less overhead and fewer running clusters, reducing costs for the company.

Towards Flexible Learning in an AI World
08.12.2023
Developer training is becoming increasingly tailored to spain mobile database preferences. InformationWeek interviews Peter Danieux, CEO of Secure Code Warrior, about how the field will evolve in the coming year and what role artificial intelligence will play in its evolution.

There has been a lot of enthusiasm lately about using AI for code development. AI can, after all, relieve development teams of the burden of repetitive and tedious tasks. It can suggest code, analyze and review products, and help optimize research initiatives.

In terms of pure productivity, AI cuts the time it takes to create and document code by nearly half, according to McKinsey. According to GitHub, more than 9 in 10 U.S. developers use AI-powered coding tools, citing benefits such as increased efficiency and freeing up more time to focus on more valuable and creative tasks rather than repetitive ones.

But over-reliance on unsupervised coding—or trusting AI to do all the work—leads to poor-quality code that’s vulnerable to cyberattacks. Beyond code-level vulnerabilities making their way into production, threat actors are taking advantage of AI tools in a variety of ways, from creating malware to engaging in social engineering attacks to exploiting generative AI’s tendency to “hallucinate” incorrect answers.
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