Apache Ozone is a distributed object store built on top of Hadoop Distributed Data Store service. It can manage billions of small and large files that are difficult to handle by other distributed file systems. Ozone supports rich APIs such as Amazon S3, Kubernetes CSI as well as native Hadoop File System APIs.
A test framework is a set of guidelines which can be followed to create test cases and related processes. These guidelines can be about coding practices, storage and retrieval of test data and test results, interaction with external resources and many other things. A test framework usually contains internal libraries and reusable code modules which provide a foundation for test automation and can be leveraged to build test automation systems for different types of applications.
When I’m writing new software, one of the most important thoughts in my mind is how I’ll test to make sure it works. There are lots of ways to test software, and when you’re at your best, you should be using all of them. Sure, you should make sure that your QA team is able to verify that your code works before it goes live. You should make sure that the code passes acceptance tests, too.
The more time I spend working with data, and watching how our customers work with data, the more convinced I am of two things: 1) the power to do extraordinary things is embedded within data and 2) all of us working or dealing with data have a role to play in using our knowhow and technology to apply data to benefit humanity and tackle some of the biggest challenges of our lifetime – the environment, equality, education, health and safety.
In 2019, Google has rolled out lots of updates out of which March 2019 Core Update, June Core Update, September Search Reviews update, and BERT were the major ones. BERT update was intended to better understand long-tail and conversational search queries while June Core Update impacted the websites that failed to implement E-A-T (Expertise, Authority, and Trust) Guidelines. On September 16, 2019, Google released a new algorithmic update to review (crawl and index) review snippets/search results.
In his most recent blog post, Marco Palladino, our CTO and co-founder, went over the difference between API gateways and service mesh. I highly recommend reading his blog post to see how API management and service mesh are complementary patterns for different use cases, but to summarize in his words, “an API gateway and service mesh will be used simultaneously.” We maintain two open source projects that work flawlessly together to cover all the use cases you may encounter.
With the recent downturn on public stock markets due to COVID-19, a recession or depression is almost inevitable. It’s likely we see mass failures across retail, travel, entertainment, and other industry sectors. The spillover from coronavirus disease and the following shelter-in-place can have drastic consequences in the startup world.
If you take a long hard look at the DevOps movement, you will find it actually divides neatly into two sub-movements. The bigger and often noisier of the two is about technology, advocating for the latest and the greatest tools and techniques, be they Cloud, CI/CD, Serverless, or Containers. The smaller sister, however, is much different, stemming from Management Theorem and focusing more on processes.
Finding slow JavaScript code can be a tricky problem to solve. Small code changes can have a big impact on the performance of your code. Fortunately, many different approaches can help you nail down the exact source of the problem. In this post, you’ll learn about three methods that’ll bring you the results you’re seeking. You can trust manual code inspection, but that has its disadvantages.
