Developers and teams who want to deploy new code often and safely leverage feature flags to decouple code deployments from feature releases. Feature flags enable teams to release new features to a subset of users, making it possible to test a new feature’s impact on users and ensuring that developers can easily roll back the feature if it causes downstream issues.

KubeCon + CloudNativeCon is the premier event that focuses on cloud-native technologies and Kubernetes. This year’s European edition took place in person and was completely sold out, with 10,000 attendees. Datadog joined the event as a platinum sponsor, and several of our engineers delivered talks on various topics, ranging from etcd to image signing and verification. In this post, we’ll share more details on these talks, along with our takeaways from the event.

The pressure to release application features faster to meet the demands of customers presents a number of challenges, including unforeseen deployment delays, custom feature sets, and complex rollbacks when errors occur. To overcome these challenges, developers can use Flagsmith, an open source feature flagging and remote configuration service that allows developers to easily roll out and test new features for a specific subset of users.

When managing queues and services in streaming data pipelines that use technologies like Kafka and RabbitMQ, SREs and application developers often struggle to determine if these pipelines are performing as expected. Visibility into the performance of a streaming data pipeline, after all, requires visibility into every component of that pipeline.

As the complexity of modern software development lifecycles increase, it’s important to have a comprehensive monitoring solution for your continuous integration (CI) pipelines so that you can quickly pinpoint and triage issues, especially when you have a large number of pipelines running.

As organizations evolve and their stacks become more complex, they need increasingly robust visibility into their cloud-based infrastructure, services, and applications. Meanwhile, teams within these organizations tend to become more specialized and siloed. As they multiply across offices and time zones, these teams must be enabled to collaborate flexibly without muddling their distinct day-to-day priorities.

Azure App Service is a fully managed platform-as-a-service (PaaS) solution for deploying web applications, event-driven functions, RESTful APIs, and more. Azure App Service enables developers to quickly build and release services that scale dynamically—without worrying about provisioning and maintaining infrastructure. Last year, we released the Datadog extension for Azure App Service for deep visibility into your Windows.NET applications.

With the growing adoption of automated deployment tools, many organizations are releasing code more frequently. As releases increase, it’s important to ensure that you don’t accidentally introduce faulty deployments, which can have wide-ranging impacts on your infrastructure, application, and end-user experience, and can potentially lead to costly rollbacks.

In any type of organization and at any scale, logs are essential to a comprehensive monitoring stack. They provide granular, point-in-time insights into the health, security, and performance of your whole environment, making them critical for key workflows such as incident response, security investigations, auditing, and performance analysis. Many organizations generate millions (or even billions) of log events across their tech stack every day.

Complex systems require many different monitors to assess the health of their infrastructure and applications, creating a wealth of alerts that can be hard to track. Due to a lack of effective triage processes, many organizations page engineers for every alert that comes in, making it difficult to separate false positives from issues that actually require immediate attention.