Operations | Monitoring | ITSM | DevOps | Cloud

Learn the key differences between MongoDB and Elasticsearch, and understand when to use each for your database and search needs.

As businesses realized the potential of artificial intelligence (AI), the race began to incorporate machine learning operations (MLOps) into their commercial strategies. But the integration of machine learning (ML) into the real world proved challenging, and the vast gap between development and deployment was made clear. In fact, research from Gartner tells us 85% of AI and ML fail to reach production.

We’ve all been there: working a feature that spans multiple Git repositories, doing your best to coordinate pull requests and save the reviewers from “review-hell” as they try to piece together how everything fits across the repositories… When a change impacts more than one microservice, the coordination can become a mess of disconnected PRs spanning many repos, each dependent on the other to avoid breaking something critical.

Bitbucket Pipelines is excited to announce support for CI/CD third-party secrets – a powerful new feature that enables you to seamlessly retrieve secrets directly from your preferred secret store. This enhancement ensures your workflows remain efficient and secure. Now, you can set up your own integration and customize the utilization of your secrets to suit your needs.

2024 is coming to a close, and while many teams are slowing down in preparation for the holidays, we’ve been cooking up tons of new features. We’ve extended our platform support to the Istio service mesh, added a brand new experiment type for testing artificial intelligence (AI) and large language model (LLM) workloads, and made it easier to onboard Kubernetes clusters. We’ve also made our Linux and Windows agents more robust and performant.

Service meshes like Istio have become an essential way to securely and reliably distribute network traffic, especially with ephemeral, service-based architectures such as Kubernetes. However, their constantly shifting nature can interfere with targeting specific services for resilience tests. Infrastructure-based testing is designed to target specific IP addresses, allowing precision testing of applications, VMs, and nodes.

The Kubernetes ecosystem is undergoing a significant transformation, and the trends emerging at KubeCon highlight just how dynamic this space has become. Traditional Application Performance Monitoring (APM) providers are rapidly shifting focus to Kubernetes Performance Monitoring (KPM), reflecting the growing need for specialized observability in increasingly complex environments.

The modern software development lifecycle comprises two key phases: continuous integration (CI) and continuous delivery or deployment (CD). In both stages, automation reduces manual labor, minimizing human errors. That enables DevOps teams to focus on mission-critical work instead of continually fixing mistakes. Automating CI/CD also provides a check and balance system for rolling back errors. Aside from ensuring optimal system performance, this also improves other areas, like security and compliance.

In a DevOps setting, incident management is all about quickly identifying, analyzing, and fixing issues that disrupt IT services. Unlike traditional IT Service Management (ITSM), which often works in isolated teams, DevOps encourages collaboration between development, operations, and business teams. This teamwork ensures that when problems like server outages or software bugs occur, they are handled swiftly and effectively. DevOps incident management is all about being agile and flexible.