Operations | Monitoring | ITSM | DevOps | Cloud

I’ve been leading software teams for more than 20 years and one thing I’ve learned about metrics is that leaders tend to put too much emphasis on engineering metrics alone, without considering the bigger picture. After speaking to a range of engineering industry leaders, and poring over millions of jobs processed from software teams worldwide, we found that the most insightful and relevant metrics fall into three categories: What metrics are meaningful for your team to measure?

DFI’s GHF51 mini industrial-grade motherboard, and the EC90A-GH mini fanless industrial computer, are the world’s first industrial computer products that have passed the Ubuntu IoT hardware certification and are equipped with high-performance AMD processors.

As CFO of Virtana, I face many of the same challenges as every CFO of a SaaS or enterprise software company today: cost containment, surprises, and an ever-escalating AWS bill. We all need help keeping these things in check. These challenges become even more difficult when your organization goes hybrid cloud. Fortunately, there are tools out there to help our teams help us manage these costs.

Flexibility is one of the cloud’s biggest benefits, but also one of its biggest challenges. When you have different teams using resources in the cloud and deploying instances at the click of a button, your cloud environment could easily become chaotic. Without a definitive plan governing your cloud operations, your costs will inevitably spiral out of control. A cloud cost strategy is your action plan for managing costs and staying profitable while working and building products in the cloud.

Like the historic space race, the competition to plant the flag of DevOps is blasting off. According to market intelligence firm IDC, global business will invest $6.8 trillion in digital transformation by 2023. Yet research also suggests that 70 percent of them will fail to meet their goals. JFrog was the first company to offer a universal, hybrid, end-to-end DevOps platform.

Bitbucket Pipelines provides a Docker caching feature that can help improve build times. However, the limitation is that only compressed caches under 1GB are saved and can be used. In this blog, we outline a process showing how you can use compressed caches that are larger than 1GB. With Docker versions >= 19.03, you can use the BuildKit feature. With BuildKit, you don’t need to keep the cache locally before building the Docker image since it caches each build layer in your image registry.

Support for including default values in custom pipelines has been a highly requested feature. We are happy to announce that this feature is now live. Providing a default value helps avoid errors when you manually trigger a custom pipeline. If you often rely on the same value for certain variables, it can be frustrating to get a failed build when you forget to specify the value or have a typo when providing the value.

Here’s a common situation that plagues many development teams. You run an application through your CI/CD pipeline and all of the tests pass, which is great. But when you deploy it to a live target environment the application just does not function as expected. You can’t always predict what will happen when your application is pushed live. The solution?