Testing Methodology for the Cloud | Meryem Zid

In this episode of Simplyblock's Cloud Commute Podcast, QA engineer Meryem Zid shares her insights on building effective QA pipelines, emphasizing unit tests and end-to-end testing as essentials for software quality. She discusses using tools like LocalStack and Terraform for cloud testing and explores emerging trends like chaos engineering, advanced observability, and edge computing testing. Meryem views AI as a supportive, transformative tool for QA rather than a replacement for human expertise, and she encourages adopting a QA culture that values continuous learning and collaboration.

In this episode of Cloud Commute, Chris and Meryem discuss:

• How to build an effective QA pipeline, from unit tests to end-to-end testing.
• What is LocalStack, and how can it be used to test AWS cloud services locally?
• Challenges and benefits of using Terraform for Infrastructure as Code in QA processes.
• Why chaos engineering and advanced observability are key to the future of quality assurance.
• How AI can assist in testing, but why it will not replace human-driven QA strategies.

Interested to learn more about the cloud infrastructure stack like storage, security, and Kubernetes? Head to our website (www.simplyblock.io/cloud-commute-podcast) for more episodes, and follow us on LinkedIn (www.linkedin.com/company/simplyblock-io/mycompany/). You can also check out the detailed show notes on Youtube (https://youtu.be/qoyyT9whpZQ).

You can find Meryem Zid (Senior Testing Engineer at Adservio Group) on Linkedin: https://www.linkedin.com/in/meryem-zid-652852187/

About simplyblock:

Simplyblock is an intelligent database storage orchestrator for IO-intensive workloads in Kubernetes, including databases and analytics solutions. It uses smart NVMe caching to speed up read I/O latency and queries. Single system connects local NVMe disks, GP3 volumes, and S3 making it easier to handle storage capacity and performance. With the benefits of thin provisioning, storage tiering, and volume pooling, your database workloads get better performance at lower cost without changes to existing AWS infrastructure.

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