The Distributed SQL Blog

Thoughts on distributed databases, open source and cloud native

Highly Available Prometheus Metrics for Distributed SQL with Thanos on GKE

In the last few years, Prometheus has gained huge popularity as a tool for monitoring distributed systems. It has a simple yet powerful data model and query language, however, it can often pose a bit of a challenge when it comes to high availability as well as for historical metric data storage. Adding more Prometheus replicas can be used to improve availability,

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Part 1: Deploying a Distributed SQL Backend for Apache Airflow on Google Cloud

Apache Airflow is a popular platform for programmatically authoring, scheduling, and monitoring workflows. Airflow has been deployed by companies like Adobe, Airbnb, Etsy, Instacart, and Square. The advantage of defining workflows as code is that they become more maintainable, versionable, testable, and collaborative. Airflow is used to author these workflows as directed acyclic graphs (DAGs) of tasks.

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Getting Started with Distributed SQL 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.

Getting Started with Distributed SQL on Azure Kubernetes Service how to tutorial

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

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,

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Bringing Distributed SQL to VMware Tanzu

VMware Tanzu, the newest offering from VMware’s stable of proven enterprise products, brings together a portfolio of open source projects for modernizing applications and automating infrastructure management. VMware Tanzu provides a managed Kubernetes environment on VMware vSphere or any public cloud of choice that allows a consistent way to provision and deploy the code for application developers.

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Automating YugabyteDB Deployments with Google Cloud Deployment Manager

This is the second post in the Getting Started with YugabyteDB on Public Cloud series. In our first post, we covered Automating YugabyteDB Deployments with AWS CloudFormation templates. In this post we will show you how to achieve the same with Cloud Deployment Manager templates when using Google Cloud.

For redundancy across multiple fault domains inside a single region,

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Basic CRUD Operations Using Hasura GraphQL with Distributed SQL on GKE

GraphQL is an MIT-licensed project originally developed at Facebook in 2012 and open-sourced a few years later. It is rapidly increasing in popularity with more than 29 million downloads to date. Why? Think of GraphQL as a query language for APIs and a runtime for fulfilling those queries with your existing data. GraphQL provides a complete and understandable description of the data in your API,

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Automating YugabyteDB Deployments with AWS CloudFormation

YugabyteDB is easy to get started with on the infrastructure of your choice including public cloud platforms, private cloud environments, and any Kubernetes distribution. For example, you can quickly customize and deploy in AWS thanks to CloudFormation templates. AWS CloudFormation is one of the many ways to automate a public cloud deployment in a consistent manner.

Before we dive in,

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Getting Started with pgbench and Distributed SQL on GKE

pgbench is a simple program for running benchmark tests on PostgreSQL. It runs the same sequence of SQL commands over and over, possibly in multiple concurrent database sessions, and then calculates the average transaction rate (transactions per second). By default, pgbench tests a scenario that is loosely based on TPC-B, involving five SELECT, UPDATE, and INSERT commands per transaction.

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