Operations | Monitoring | ITSM | DevOps | Cloud

After getting a taste of DevOps’ benefits, enterprises naturally seek to widen its adoption. However, the tooling and processes that work for small-scale use cases often fall short when teams try to scale DevOps efforts. You must support all your different teams, toolsets, applications, processes, workflows, release cycles and pipelines — both legacy and cloud native.

A platform-agnostic way of accessing credentials in Python. Even though AWS enables fine-grained access control via IAM roles, sometimes in our scripts we need to use credentials to external resources, not related to AWS, such as API keys, database credentials, or passwords of any kind. There are a myriad of ways of handling such sensitive data. In this article, I’ll show you an incredibly simple and effective way to manage that using AWS and Python.

Marc Hornbeek is a DevOps consultant, author and advisor who playfully calls himself “DevOps the Gray” due to his 40-plus years of work in software development. We spoke with him about the convergence of IT operations and DevOps and what it means for the IT organization.

To put it bluntly, did someone die? In engineering, let’s hope your answer is a resounding no. So why do we continue to use the word ‘postmortem’?

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.