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.

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.

Organizations today rely on cloud object storage to power diverse workloads, from data analytics and machine learning pipelines to content delivery platforms. But as data volumes explode and storage patterns become more complex, teams often struggle to understand and proactively optimize their storage utilization. When issues arise—such as unexpected costs or performance bottlenecks—these teams frequently lack the visibility needed to quickly identify and resolve root causes.

AWS VPC flow Logs and Azure NSG flow Logs offer network traffic visibility with different scopes and formats, but both are essential for multi-cloud network management and security. Unified network observability solutions analyze both in one place to provide comprehensive insights across clouds.

When computers are returned to a corporation, they don’t simply disappear into storage or landfills. Companies often implement structured processes to make the most of these devices while adhering to regulatory and ethical standards. Managing returned computers is a practical and pressing concern for corporations, whether dealing with employee's offboarding, end-of-life hardware, or upgrades. The process involves multiple considerations, from data security to environmental compliance.

Distributed Denial of Service (DDoS) attacks are intended to overwhelm a network or server and cause failure or work stoppage. DDoS attacks first appeared in the mid-1990s and continue to the present day. Far from going away, they have become more prevalent: in the first quarter of 2024, the number of DDoS attacks against web servers increased by 93% compared to the same period a year earlier. One survey found that nearly 70% of organizations experienced 20 to 50 DDoS attacks per month.

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.

In today’s digital-first world, organizations are constantly pressured to deliver faster, more reliable, and secure network services. Yet, with a staggering 65% of enterprise network activities still performed manually, the journey toward network automation is more critical than ever.

Like all organizations, Elastic deals with an ever-increasing volume of information and data, making it harder for our teams to keep information up to date and for employees to find answers from relevant resources. As a leading Search AI company, our approach to customer-first starts with customer zero — us. When our employees needed a better way to find the information necessary to do their jobs, we knew we could use our own technology to bring that vision to life.

We’re always interested in improving the signal-to-noise ratio of our internal telemetry at Honeycomb. In an effort to reduce the amount of noise in our logs, we looked at reducing and deduplicating the logs emitted by our infrastructure and applications.