At the microXchg microservices conference, held in Berlin, Adrian Cockcroft presented “Shrinking Microservices to Functions”. Key takeaways from the talk included: ‘serverless’ technologies enable rapidly developed functions-as-a-service (FaaS); and the biggest challenges for modern enterprise software development are connected with the people and process within an organisation.
After three months in beta, Google has announced the general availability of its Open API-based Cloud Endpoints (GCE) API management system, which aims to make it possible to build efficient, ready-to-scale API platforms, says Google.
In a recent article on the MSDN site, Daniel Meixler explores a complete DevOps lifecycle for an Internet of Things (IoT) application using Microsoft frameworks and components. The concepts can be generalized to other IoT platforms with some changes.
Microsoft has recently announced changes to its cloud workflow service, Flow, to enable teams to contribute and manage flows centrally. This new sharing capability is also available to SaaS and custom API Connectors. In addition to these collaboration features, Microsoft has also announced support for Gmail connectivity and integration with additional Microsoft Cognitive Services APIs.
A recent article compares some of the container orchestration options available today. They range from open-source ones that can be self-hosted, to containers-as-a-service offerings, which again range from startups to enterprise players.
MindMeld, a conversational AI company, has published The Conversational AI Playbook, a guide outlining the challenges and the steps to be made to create conversational applications.
What started out as an attempt to protect GitLab.com from spammers turned sour as engineer fatigue and a lack of backups took the site down for nearly 18 hours and the loss of six hours worth of production data.
Tracking "who did what" in a self-service public cloud can be challenging. With Google Cloud Audit Logging, Google captures log streams for seventeen services in Google Cloud Platform (GCP) .
The Twitter Engineering team has recently provided an insight into the evolution and scaling of the core technologies behind their in-house infrastructure that powers the social media service. Core lessons shared included: Architect beyond the original specifications; there is no such a thing as a “temporary change or workaround”; and documenting best practices has been a “force multiplier”.
Docker Inc. launched its answer to Amazon ECS into public beta at the end of last year: an AWS-compatible service for managing and orchestrating Docker containers. Now, Docker for AWS is generally available.
Amazon is the first cloud provider to support Windows Docker containers in their managed container platform - the AWS EC2 Container Service. The new beta service for Windows has several restrictions, but it paves the way to running multi-platform solutions across a single cluster of container hosts.
StorageOS aims to make container storage flexible by providing a single view of the underlying storage and exposing APIs for automation.
Docker Inc, has released version 1.13 of its open source Docker container engine project. This release includes significant restructuring of the Docker CLI, and the introduction of ‘clean-up’ commands to reclaim disk space. Alongside the launch of Docker 1.13, new releases of the supporting toolchain were also made, including: Docker Compose 1.10, Docker Machine 0.9.0, and Notary 0.4.3.
In late 2016, Microsoft announced the general availability of Azure SQL Database In-Memory technologies. In-Memory processing is only available in Azure Premium database tiers and provides performance improvements for On-line Analytical Processing (OLTP), Clustered Columnstore Indexes and Non-clustered Columnstore Indexes for Hybrid Transactional and Analytical Processing (HTAP) scenarios.
Google Cloud Platform has released an open source Zipkin server that allows Zipkin-compatible clients to send traces to Google’s own Stackdriver Trace distributed tracing service for analysis. This Zipkin/Stackdriver Trace integration is aimed at developers whose applications and services are written in a language or framework that Stackdriver Trace doesn’t officially support.