January 2025 Summaries

Dagger Cloud v3 introduces a new user interface that provides a more consistent user experience across all Dagger interfaces, better overall performance, and faster delivery of new features. The new UI is built on WebAssembly (WASM), allowing for a unified and high-performance experience. Dagger Cloud v3 also improves error readability, providing highlighted error messages in the trace view, making it easier to spot issues immediately. Additionally, the new version includes better CI integration, with traces sent from the same CI workflow automatically grouped together, and a clearer status indicator for each step in the pipeline. The UI now shows two feeds side-by-side: traces from CI, and traces from your team's local dev environments, providing a bird's eye view of every pipeline running in your organization, and their status, in real time. Furthermore, Dagger Cloud v3 includes better support for large traces, with faster loading times and smoother experiences. The new version also introduces breadcrumbs for easier navigation within traces, making debugging faster by letting you trace the root cause of the error easily. Finally, Dagger Cloud v3 allows users to toggle between dark mode and light mode based on their preference.

GPUs are a critical tool for tasks like machine learning, data processing, and high-performance computing, but integrating them into CI/CD pipelines presents unique challenges. These challenges include the cost and accessibility of GPUs, which can be expensive and difficult to share across containers, as well as limited use cases that often lead to underutilized GPU resources. To simplify GPU integration, Dagger is making it easier to use remote runners like Fly.io and Lambda Labs to run GPU-enabled pipelines on-demand, saving time, cost, and headaches. With the latest updates to its documentation, users can offload GPU-specific tasks to these remote runners while keeping the rest of their pipeline local, deploying resources only when needed, persisting caching across runs, and managing infrastructure agnosticity. To see GPU integration in action, Dagger provides a demo that walks through a practical example using Fly.io and Lambda Labs, allowing users to integrate GPU steps seamlessly without breaking their existing workflows.

Civo and Dagger showcased how Civo's managed cloud services and Dagger's CI/CD framework combine to create a highly scalable, cache-optimized development workflow. This approach has been used internally by Civo for over a year. It involves spinning up Dagger engines within Kubernetes clusters to handle pipelines more efficiently, scaling nodes up or down based on workload. Faster caching with S3-compatible object storage is also used to ensure that ephemeral engines can quickly access previous runs' cache data, cutting build times significantly. Additionally, using local NVMe drives and optimized network transport within Civo's cloud provides lightning-fast cache read/write speeds without hidden fees. The demo featured a ready-to-use Terraform configuration that provisions the Kubernetes cluster, object storage, and Dagger engine, allowing users to adapt it to their workflows in minutes. This approach matters for CI/CD pipelines as it enables ephemeral runners to access cached data across nodes, allows for highly optimized workflows tailored to monorepos or microservices pipelines, and saves costs during off-peak hours without sacrificing build performance when demand spikes. The Dagger team is hosting an interactive workshop at Civo Navigate in San Francisco this February, offering a 25% discount to attendees who use the code DAGGERCIVONAV25P at checkout.

Today's announcement is about integrating Dagger and GitHub Actions, made possible by a new partnership with Depot. Running Dagger on GitHub Actions is easy but running it at optimal performance was not, due to the lack of persistent caching in stock runners. This integration now allows users to leverage Dagger's cache without self-hosting their CI, making it easier to integrate Dagger into workflows without sacrificing performance. The combination of Dagger and Depot's GitHub Actions runners provides a simple setup with pre-installed Dagger, efficient caching, and distributed caching out of the box, making it an attractive option for developers. This is just the beginning of the Dagger Powered program, which aims to partner directly with infrastructure providers to meet developers where they are.

The company Dagger has made significant strides in its mission to deliver a single integrated platform for orchestrating the delivery of applications to the cloud. In 2024, they introduced groundbreaking capabilities, improved developer experience, and enhanced performance and reliability. They also launched the Daggerverse, a searchable library of reusable functions, and introduced interactive debugging, making it easier for users to debug their pipelines. Additionally, they made Dagger Cloud free for individuals and very cheap for small teams, and added enterprise-readiness features such as SOC2 certification. The community has been actively contributing to Dagger's growth, with 9 SDKs available across multiple programming languages. In 2025, Dagger plans to continue improving its platform, including faster file synchronization, better error messages, and a new way of working with the Dagger Engine.