Security | Threat Detection | Cyberattacks | DevSecOps | Compliance

To reduce the risk of data loss, organizations rely on proven backup strategies. In this guide, we explain what the 3-2-1 backup rule is, how it works, and how to apply it correctly. Topics discussed in this piece: click to expand What is the 3-2-1 backup rule? Three data copies Two different media One off-site copy Is the 3-2-1 backup rule still the industry best practice? Ever heard of the 3-2-1-1-0 backup rule? Alternative 4-3-2 strategy How do these compare against each other?

DevOps has become an important practice for companies looking to efficiently meet customers’ expectations, accelerate software delivery, and optimize resources. Companies that embrace the DevOps culture can smoothly merge their development and operations teams, resulting in faster releases and better development.

Choosing different IT services is like choosing a car. Apparently, all cars have four wheels, an engine, and they can be driven. But in the end, differences are much bigger, and the final choice depends on many factors. Of course, we always take into account the price, but not only. First of all, the choice depends on the purpose and usability. After all, we will not take a sports car to drive on muddy forest roads. Personal preferences and habits also matter.

Cyber crime gets more advanced, and threat actors increasingly target backups with ransomware attacks. If an organization is left with erased or corrupted data and has no access to backup copies, there is no chance of recovery. This allows the attackers to demand ransom payments averaging at over 10 million dollars as of 2025. That is why your backup and disaster recovery strategy should be reliable and secure to keep your environments protected and guarantee business continuity.

Every IT stack may look tidy on a diagram. If so, then it’s tempting to assume everything works fine. And yet, systems rarely fail as a whole. Usually, it’s a part or functionality. For instance, anyone who ever untangled a broken workflow in GitHub, GitLab, Bitbucket or Azure DevOps, or a corrupted field in Jira, knows it too well. And that’s the quiet tension (“to fix one little thing”) inside every modern backup strategy.

Modern organizations often use GitLab as a core version control system (VCS), making it one of the most essential systems for DevOps. Given the critical nature of the data stored here, thorough evaluation of risks and implementing data protection best practices are a must. According to the Shared Responsibility Model, GitLab provides security for the underlying infrastructure, while the user’s duty is to keep data protected. More about GitLab’s Shared Responsibility Model.

Artificial Intelligence is everywhere nowadays. It helps teams to be more productive, but at the same time, it can threaten your critical project management data. The introduction of AI into Jira opened up new paths for attackers to exploit, new vulnerabilities coming up internally, and human errors. So, in this article, let’s speak about AI data loss in Jira and what measures to take to protect your sensitive data in Jira Cloud.

Artificial Intelligence is everywhere nowadays. It helps teams to be more productive, but at the same time, it can threaten your critical project management data. The introduction of AI into Jira opened up new paths for attackers to exploit, new vulnerabilities coming up internally, and human errors. So, in this article, let’s speak about AI data loss in Jira and what measures to take to protect your sensitive data in Jira Cloud.

For many DevOps and ITSM workflows, Jira is the nerve center. It’s relied upon by thousands of teams for everything from agile sprint planning to enterprise-scale incident management. However, beneath the robust interface and powerful automation, your Jira data remains fragile – far more than you think. Scenarions around Jira data loss aren’t a theory. At least nowadays, when such things happen it’s quickly and quietly.

Both large and small projects need to be managed in some way. It is essential to track the progress and statuses of key tasks. Projects can be managed using “ancient” methods – on a piece of paper, a blackboard, or using colored cards… but why if there are many better ways? The problem actually arises when we want to scale up. Then, organizations would require more storage space as there would be much more data, tasks and statuses.