What’s the point: Kong, Spring Cloud, TeamCity, Istio, and Databricks

What's the point

So much news, so little time. Learn more about what has happened in the last couple of days in this short-form news roundup covering current point releases and all.

Kong team celebrates 1.3 release

Service mesh Kong is now available in version 1.3. The new release is the first to natively support gRPC proxying, which is meant to help improve the operational flow, and ups observability among other things.

Kong can now also handshake with upstream services using certificates, match routes by any request header, and offer configuration properties to control the maximum number of proxied requests as well as the idle timeout of an upstream connection.

Spring Cloud Hoxton release train reaches second milestone

Milestone 2 of the Spring Cloud Hoxton has been released and includes new blocking and non-blocking load balancer client implementations. The new additions are meant as substitutes for Netflix Ribbon, since this has entered maintenance mode.

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Spring Cloud’s Contract component now comes with an incremental build option for Gradle, as well as one to generate stubs on the consumer side. On top of that contracts and stubs can be fetched directly from a folder without getting unpacked. The release notes give you the full picture.

TeamCity devs let you take a peak at what’s next

Users of JetBrains’ CI and CD server TeamCity can now take an early access preview of version 2019.2 for a spin. The tool comes with handy new additions such as code highlighting for a couple of build runners, a build preview which can be found in the build list, and a feature to compare builds side-by-side. 

The release is the first to let DevOps folks use Amazon launch templates. Other improvements tackle multi-node setups and the integration of containerisation tool Docker.

Istio reminds users of impending v1.1 EOL

Istio users who like their installations safe and stable are advised to slowly start thinking about upgrading should they still use version 1.1 of the service mesh. Starting on 19 September 2019, the Istio team will stop back-porting security and bug fixes for this specific release. According to the project’s support policy, the date means the end of the long term support for version 1.1, since Istio 1.2 was released on 18 June.

Databricks sprinkles some ML magic into the mix

Databricks announced this week the addition of new automated machine learning capabilities to its Unified Analytics Platform. Those are meant to offer “automation and augmentation” and “shorten time-to-value for data science teams”.

The offering spans an automated model search, automated hyperparameter tuning, the integration with Azure Machine Learning, and an AutoML toolkit. The latter is available via Databricks Labs custom solutions and supposedly provides users with an automated end-to-end machine learning pipeline.

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