Cloud Native

Distributed SQL Summit Recap: The Future of Data Infrastructure, A Telco Roundtable

Distributed SQL Summit Recap: The Future of Data Infrastructure, A Telco Roundtable

At the Distributed SQL Summit 2020, leaders and architects from notable enterprises in the telco industry joined us for a panel to discuss the future of software development, including important trends such as IoT, 5G, Edge, cloud, and their impact on data infrastructure. Our panelists included Puneet Devadiga from Rakuten Mobile, Hale Donertasli from Rakuten Mobile, Kartik Rallapalli from TracFone Wireless, and James Taylor from Comcast; the panel was moderated by Yugabyte’s head of Data Engineering,

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Distributed SQL Summit Recap: Mastercard’s Cloud Native Journey to Distributed Databases

Distributed SQL Summit Recap: Mastercard’s Cloud Native Journey to Distributed Databases

At the Distributed SQL Summit 2020, Ken Owens – Vice President, Cloud Native Engineering, Mastercard, presented the talk, “The Data Divide: An End User’s Cloud Native Journey to Distributed Databases.”

Because Ken has been working at the intersection of technology and financial services for more than 20 years, he brings a unique perspective to how cloud native and distributed systems can transform, what from the outside may appear to be a slow moving industry,

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Getting Started with Longhorn Distributed Block Storage and Cloud Native Distributed SQL

Getting Started with Longhorn Distributed Block Storage and Cloud Native Distributed SQL

Editor’s note: This post was originally published on the Rancher blog, and has been cross-posted here and updated as of July 21, 2020 to account for new versions of software available.

Longhorn is cloud native distributed block storage for Kubernetes that is easy to deploy and upgrade, 100 percent open source, and persistent. Longhorn’s built-in incremental snapshot and backup features keep volume data safe, while its intuitive UI makes scheduling backups of persistent volumes easy to manage.

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Getting Started with Distributed SQL on Red Hat OpenShift with YugabyteDB Operator

Getting Started with Distributed SQL on Red Hat OpenShift with YugabyteDB Operator

We are happy to announce that the YugabyteDB Operator is now certified and available as a Beta release on Red Hat OpenShift, a leading enterprise Kubernetes platform for deploying and managing cloud native applications. Achieving certification means that customers can deploy YugabyteDB on OpenShift with confidence because the YugabyteDB container image has been secured, validated, and is well-integrated to run on OpenShift. And the solution is backed by collaborative support between Red Hat and Yugabyte,

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Getting Started with YugabyteDB on Azure Kubernetes Service

Getting Started with YugabyteDB on Azure Kubernetes Service

Microsoft’s Azure Kubernetes Service (AKS) offers a highly available, secure, and fully managed Kubernetes service for developers looking to host their applications on containers in the cloud. AKS features elastic provisioning, an integrated developer experience for rapid application development, enterprise security features, and the most available regions of any cloud provider.

YugabyteDB is a natural fit for AKS because it was designed to support cloud native environments since its initial design.

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Spanning the Globe without Google Spanner

Spanning the Globe without Google Spanner

Open Source Geo-Distributed Relational Database on Multi-Cluster Kubernetes

Google Spanner, conceived in 2007 for internal use in Google AdWords, has been rightly considered a marvel of modern software engineering. This is because it is the world’s first horizontally-scalable relational database that can be stretched not only across multiple nodes in a single data center but also across multiple geo-distributed data centers, without compromising ACID transactional guarantees. In 2012,

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Cloud Native Tips and Tricks for YugabyteDB – March 27, 2020

Cloud Native Tips and Tricks for YugabyteDB – March 27, 2020

In this blog post, we answer some common questions from YugabyteDB users to help you in your own application development and deployment. We’ll also review upcoming events, new documentation, and blogs that have been published since the last post. Got questions? Make sure to ask them on our YugabyteDB Slack channel, Forum, GitHub, or Stackoverflow.

Before we dive in, we wanted to let you know that the Yugabyte team has been working from home in order to do our part with social distancing and to help with containment efforts.

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Distributed SQL Tips and Tricks – March 13, 2020

Distributed SQL Tips and Tricks – March 13, 2020

Welcome to this week’s tips and tricks blog where we recap some distributed SQL questions from around the Internet. We’ll also review upcoming events, new documentation, and blogs that have been published since the last post. Got questions? Make sure to ask them on our YugabyteDB Slack channel, Forum, GitHub, or Stackoverflow. Ok, let’s dive right in.

How can I UPSERT multiple rows with an update?

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Monitoring YugabyteDB with Prometheus and Grafana in Kubernetes

Monitoring YugabyteDB with Prometheus and Grafana in Kubernetes

Prometheus has matured into a robust time-series metrics monitoring solution since it was first open-sourced in 2012. CNCF incubated it as its second project after Kubernetes in 2016 followed by graduation in 2018. Today it is arguably the most popular option for monitoring Kubernetes cluster metrics as well as container-based applications. Combined with Grafana for visualization, it becomes a potent combination for dashboarding performance of applications. Nodes in a YugabyteDB cluster have exposed a Prometheus endpoint for easy metrics collection right from the inception of the open source project.

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Getting Started with Falco Runtime Security and Cloud Native Distributed SQL on Google Kubernetes Engine

Getting Started with Falco Runtime Security and Cloud Native Distributed SQL on Google Kubernetes Engine

Falco is an incubating CNCF project that provides cloud native, open source runtime security for applications running in Kubernetes environments. Falco monitors process behaviors to detect anomalous activity and help administrators gain deeper insights into process execution.  Behind the scenes, Falco leverages the Linux-native extended Berkeley Packet Filter (eBPF) technology to analyze network traffic and audits a system at the most fundamental level, the Linux kernel. Falco then enriches this data with other input streams,

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