Systems | Development | Analytics | API | Testing

Deciding whether to run applications in containers or virtual machines used to entail analyzing which trade-offs you could accept in exchange for certain advantages. With Firecracker, we can leverage the benefits of both technologies. In this blog post, we are going to talk about why exactly Firecracker is setting the serverless computing world on fire and what you need to know about this emerging technology.

Field testing is a critical step in the last phase of mobile testing. After all regression tests pass, testers would go into the real environment to verify an application’s usability and behavior. The purpose of field testing is to determine how an application works before releasing it to end-users. Therefore, teams test to see how end-users use the application beyond the initial frequent use, in a real-world scenario. Testing is carried out using mobile networks only.

The past year saw an increase in technology upgrades and earlier adoption. As consistent leaders of global transformation, social media networks once again led the way—influencing the lives and work of people and businesses. While new social media tools and features introduced last year were already in development, these multi-billion dollar platforms continue to innovate. To stay ahead of the market you need to keep up with new social media trends.

Splunk is a technology that made processing huge volumes and complex datasets accessible to security and IT teams. Despite its strengths for monitoring and investigation, Splunk is a bit of a one-way street. Once it's in Splunk, it's not that easy to stream the data elsewhere in great volume. And it doesn’t mean it’s the best technology for all IT and Security use cases. Or the cheapest.

Mobile testing involves spotting bugs in a mobile application and fixing them – ranging from identifying sign-up issues, breaking in the payment process, or finding glitches in navigation before it hits the market. This testing can be done manually or with automation, and utilizing the right testing strategy helps meet all quality and usability requirements. Among the elements necessary for a seamless testing process is the selection of the right mobile testing devices.

The adoption of cloud-based solutions has become increasingly common. The proof for this is evident – according to Gartner, Inc., the worldwide public cloud services market is expected to grow by 6.3% in 2020, up to a staggering $257.9 billion in value. The Flexera 2020 State of the Cloud Report, released on April 28, 2020, states that more than 90% of respondents have adopted cloud computing, with the top three cloud service providers being – AWS, Azure, and Google Cloud Platform.

In the previous posts in this series, we have discussed Kerberos and LDAP authentication for Kafka. In this post, we will look into how to configure a Kafka cluster to use a PAM backend instead of an LDAP one. The examples shown here will highlight the authentication-related properties in bold font to differentiate them from other required security properties, as in the example below. TLS is assumed to be enabled for the Apache Kafka cluster, as it should be for every secure cluster.

Modern applications don’t function in isolation. To get the most out of the enterprise apps you build or buy, you’ll have to connect them to other applications. In other words, data engineers have to engage in effective application integration to achieve their business goals. Sometimes, this means connecting one application directly to another. But this is a rare occurrence in digitally transformed industries.

Building machine learning (ML) and deep learning (DL) models obviously require plenty of data as a training-set and a test-set on which the model is tested against and evaluated. Best practices related to the setup of train-sets and test-sets have evolved in academic circles, however, within the context of applied data science, organizations need to take into consideration a very different set of requirements and goals. Ultimately, any model that a company builds aims to address a business problem.

If anyone's ever been to AWS ReInvent in Vegas before, you'll know it's a crazy ride. This year we missed out (at least we have cleaner consciences and healthier wallets). But the high quality of content hadn't changed. We've been binging on sessions ‘til the bitter end (it officially ended Friday). So for our community, here is a summary of a few talks related to Apache Kafka.