Operations | Monitoring | ITSM | DevOps | Cloud

Code analysis tools are essential to gain an overview and understanding of the quality of your code. This post is going to cover the following While these tools target similar use cases, they differ in their implementation, ease of use, and documentation just to name a few. This post provides an overview of each tool as well as a detailed comparison to help analyse and decide which tool is best suited for your needs.

Kubernetes applications are increasingly making their way to the edge and embedded computing. Storage will quickly follow as the applications that rely on this edge infrastructure become more advanced and naturally carry more state. According to a study by McKinsey and Company, a “connected car” processes up to 25GB of data per hour.

Choosing a software solution means checking the right boxes, and being “cloud native” has bubbled to the top of most lists. But cloud native is a box built of boxes of its own. For a CI/CD solution like JFrog Pipelines, cloud native starts by being “born in the cloud” to natively execute in, build for, test in, and deploy to cloud computing environments. But what boxes does a CI/CD solution really need to tick to complete that larger cloud native box?

This is a follow up to a blog series where we explore DIY cloud cost management, monitoring, and optimization tools. In the first, we investigated how Lyft, Netflix, Segment, Expedia, and Slack built theirs. Check it out here. “Build versus buy” is the eternal question for every engineering and DevOps team setting out to solve a technical problem. In the cloud cost monitoring and optimization world, both options can take on many forms.

Within just five years, Kubernetes and containers have redefined how software is deployed. Researchers expect the container market to grow by 30% year over year to become a 5 billion industry by 2022. But what is the reason behind this mass adoption of container technology in the enterprise? Download whitepaper Containers are more resource efficient than virtual machines or other legacy app architectures.

If you strip the buzzwords and TLAs from the definition of DevOps? You’ll find that the roles and tasks involved aim mostly for more uptime and less downtime in the SDLC (software development lifecycle). The first step to achieving that is becoming aware of downtime as it happens with the help of monitoring solutions. Only then can you respond and resolve the issue in a timely manner that minimizes the dreaded and expensive downtime of software development teams.

Chaos Engineering is one of the hottest new approaches in DevOps. Netflix first pioneered it back in 2008, and since then it’s been adopted by thousands of companies, from the biggest names in tech to small software companies. In our age of highly distributed cloud-based systems, Chaos Engineering promotes resilient system architectures by applying scientific principles. In this article, I’ll explain exactly what Chaos Engineering is and how you can make it work for your team.

Hello, Puppet friends! It’s been a few months since we rolled out the latest major version of the Puppet platform, bumping PuppetDB, Puppet Server and Puppet Agent to “7.0.0.” First, we’d like to extend our gratitude to our vibrant Puppet community, who helped us immensely in locating and fixing some annoying bugs that managed to sneak through the release. We promptly provided follow-up releases, so be sure to check out the latest available versions for your operating system.

You may have spotted some news last week from PCCW Global that both its international network and the Console Connect digital platform have recently received MEF 3.0 certification. Besides demonstrating to our customers and partners that Console Connect is aligned with the latest and highest network standards, this news also highlights the work that we are doing behind-the-scenes to help advance network automation and on-demand services globally. Read more…