Releasesby GlyphDataflow has updated and expanded its pipeline update features for streaming jobs: - Automated...
Dataflow has updated and expanded its pipeline update features for streaming jobs: Automated stop-and-replace updates : You can perform automated, declarative stop-and-replace updates to streaming jobs. Parallel updates with the same job name : When you perform automated parallel updates, you can use the same job name for the new replacement job.
Also shipped Jun 15, 2026Google Cloud in June 2026 →
The following Anthropic models are deprecated from DigitalOcean Inference as of 15 June 2026: Claude Opus 4...
The following Anthropic models are deprecated from DigitalOcean Inference as of 15 June 2026: Claude Opus 4 Claude Sonnet 4 Migrate to Claude Opus 4.8 (anthropic-claude-opus-4.8) and Claude Sonnet 4.6 (anthropic-claude-4.6-sonnet), …
Snapshots is now in Open Beta
Get screenshot diffing in CI to catch unintended visual changes. Works for any platform with a frontend.
Dashboard Search for APIs Now in Beta
__Dashboard Search for APIs is now available in Public Beta!__ Find your API faster without scrolling through paginated lists. Dashboard users can now __search APIs in real time by ID, identifier or name.__ Rolling out progressively to Public Cloud tenants starting this week, with broader availability in the coming weeks.
API Deprecation Notice
API Deprecation Notice We retired a few legacy items from the Exa API: /research endpoint : replaced by /search with type: "deep-reasoning" . resolvedSearchType and highlightScores (response fields) : returned null from April 15, removed May 1. startCrawlDate / endCrawlDate (deprecated request parameters) : silently ignored from April 15.
Exa Pricing Update
Exa Pricing Update We simplified and lowered pricing. Contents for the first 10 search results are now included for free, and the new pricing applies automatically with no action needed. Search with contents : $7 per 1k requests (10 results, text + highlights included); $1 per 1k additional results. Summaries : $1 per 1k, on both search and contents.
Week 25
Address data collection The Collect Data task has a new address type. Add it to an agent and it walks the caller through providing a complete mailing address (street, city, postcode, country) in one structured step, validating the input and writing the parsed fields back onto the contact.
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Dataflow now supports NVIDIA RTX Pro 6000 GPUs
Dataflow now supports NVIDIA RTX Pro 6000 GPUs. You can use this GPU model to run your Apache Beam pipelines on Dataflow. RTX Pro 6000 GPUs are recommended for large, medium, and small model inference workloads. To configure your workers with this GPU model, set the accelerator type to nvidia-rtx-pro-6000 .
You can now use Hyperdisk Balanced disks for Dataflow worker VMs
You can now use Hyperdisk Balanced disks for Dataflow worker VMs. With Hyperdisk Balanced disks, you can provision IOPS and throughput independently of disk size by using the diskProvisionedIOPS and diskProvisionedThroughput pipeline options (Java SDK) or disk_provisioned_iops and disk_provisioned_throughput_mibps pipeline options (Python and Go SDKs).
You can now pause a Dataflow batch job using the pause_on_failure service option
You can now pause a Dataflow batch job using the pause_on_failure service option. This feature lets you preserve the state of your batch pipeline job, address external issues, and resume processing without losing completed work. You can use this option to automatically pause a job on failure, or use this feature to manually pause a job when you chose to.
Dataflow job builder now supports external Iceberg REST Catalogs as a source
Dataflow job builder now supports external Iceberg REST Catalogs as a source. You can now ingest data from external Apache Iceberg REST catalogs (IRC) directly into Lakehouse tables using Dataflow's job builder UI without writing code. For more information, see Import data from external Iceberg catalogs to Lakehouse using Dataflow .
When you use min_ram or cpu_count resource hints for pipeline steps that don't require accelerators, Auto VM...
When you use min_ram or cpu_count resource hints for pipeline steps that don't require accelerators, Auto VM Selection (Instance Flexibility) is enabled automatically. With Auto VM Selection, workers are provisioned from a curated list of machine types that meet your RAM and CPU requirements.
Dataflow support for the C4A machine series of Arm processors is now generally available
Dataflow support for the C4A machine series of Arm processors is now generally available. Arm-based VMs are optimized for power efficiency and can provide improved price-performance for many workloads. For more information, see Use Arm VMs on Dataflow .
Dataflow Auto VM Selection now supports 4th generation Compute Engine machine series
Dataflow Auto VM Selection now supports 4th generation Compute Engine machine series. When Auto VM Selection is enabled, the service prioritizes these newer generation VMs for improved performance.
Dataflow now supports streaming high availability for Streaming Engine jobs ( Preview )
Dataflow now supports streaming high availability for Streaming Engine jobs ( Preview ). When you enable the requires_high_availability service option, Dataflow replicates backend state across multiple zones in a region to protect your job from single-zone failures. For more information, see Streaming high availability .