Service alarms are going off and you are on the hook to restore stability, but you need to prevent any more changes to production while you dig further. You could "freeze" production by announcing it in the office, sending a message on Slack, or sending an email to the affected teams, but that may not be enough or may require extra work that would distract you from debugging and fixing the problem.

In most of our blogs, we spend a TON of time going on about protecting our endpoints, looking at sysmon, checking the firewall, correlating IDS data and the like… Today, we're going to shift gears a bit and look at security from a different angle. Recently, there has been a tremendous focus on the shifting paradigm of a workforce that primarily resides in corporate offices, to a highly virtual workforce sitting at their kitchen tables.

In IT environments, all software applications and systems produce logs with varying levels of details or context about different events. These log files are automatically generated, and you can see them as a time-stamped record of events. Traditionally, organizations maintained logs locally or in a self-hosted setup. This was done primarily to meet various compliance mandates.

In agile development, planning, coding, and builds are an ongoing loop. But when a circle is broken, you can’t travel it at full speed. For users of Atlassian Bitbucket Server and Jira, JFrog’s integrations can help Artifactory bridge the gaps for continuous velocity. In a previous blog post, we discussed how to provide Jira information as a critical “why” in your build information.

History books will one day write about our time. What will they say? Worldwide pandemic caused governments to issue stay-at-home orders in 2020. People were advised to wear masks in public and keep six feet of distance. Rice, toilet paper, and household cleaners were impossible to find. It has been a major adjustment for everyone, to be sure. From the restaurant owners trying not to lose their businesses to the homeschooling parents trying not to lose their minds, we're all facing unique challenges.

If you’ve done your research, you probably know that Kubernetes is only one piece of the puzzle. Production grade deployments require a lot of moving pieces including logging and monitoring, governance, and more. You’ll also need some key extensions — some Kubernetes can’t go without, others that will make your life a lot easier. Let’s take a closer look.

Both DynamoDB and MongoDB are NoSQL databases, but the similarities probably end there. In this article, we cover their strengths and weaknesses in 8 basic categories, so that you can decide which one suits best your needs. While the data model behind Mongo is more flexible for storage and retrieval, Dynamo is stronger in terms of scalability, consistent performance under heavy load, and infrastructure abstraction.

Digital transformation and IT modernisation initiatives provide innovations to create a competitive edge and drive business growth. But they’ve also created increasingly complex environments that need to be managed by teams that are strapped for time and resources.

We’re excited to share that our Sumo Logic Continuous Intelligence Platform™ was recently recognized as the Data Analytics Solution of the Year by Data Breakthrough. We join an impressive list of innovative solutions and companies that are solving complex and critical problems and disrupting new markets and industries. Winning this achievement further validates our vision to provide a solution that is helping modern businesses thrive in today’s Intelligence Economy.

One of the challenges when you’re starting out with DevOps is getting the lay of the land. There are a lot of tools out there. And when one of the goals of DevOps is continually improving your processes, it’s important for you to understand how those tools might fit in your infrastructure. At the same time, you want to be efficient. You don’t want to add tools that overlap with one another. Or tools that cost more than other effective alternatives.