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Tag: Kubernetes

Five Benefits to Running a Distributed SQL Database in Kubernetes

Five Benefits to Running a Distributed SQL Database in Kubernetes

A distributed SQL database is a single logical relational database deployed on a cluster of servers. The database automatically replicates and distributes data across multiple servers. These databases are strongly consistent and support consistency across availability and geographic zones in the cloud.

At a minimum, a distributed SQL database has the following characteristics:

  • A SQL API for accessing and manipulating data and objects
  • Automatic distribution of data across nodes in a cluster
  • Automatic replication of data in a strongly consistent manner
  • Support for distributed query execution so clients do not need to know about the underlying distribution of data
  • Support for distributed ACID transactions

But should you run a distributed SQL database in Kubernetes?

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Tutorial: How to Deploy Multi-Region YugabyteDB on GKE Using Multi-Cluster Services

Tutorial: How to Deploy Multi-Region YugabyteDB on GKE Using Multi-Cluster Services

The evolution of “build once, run anywhere” containers and Kubernetes—a cloud-agnostic, declarative-driven orchestration API—have made a scalable, self-service platform layer a reality. Even though it is not a one size fits all solution, a majority of business and technical challenges are being addressed. Kubernetes as the common denominator gives scalability, resiliency, and agility to internet-scale applications on various clouds in a predictable, consistent manner. But what good is application layer scalability if the data is still confined to a single vertically scalable server that can’t exceed a predefined limit?

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Getting Started with YugabyteDB, Temporal, and the Temporal-Maru Benchmarking Tool

Getting Started with YugabyteDB, Temporal, and the Temporal-Maru Benchmarking Tool

“Does YugabyteDB integrate with temporal.io?” is a common question from developers. Temporal enables technologists to build highly reliable applications without having to worry about all the edge cases. Developers use Temporal not just because it is an open-source solution. They also use it to build workflows in code and operate resilient applications using developer-friendly primitives.

Temporal supports independent horizontal scaling of each of the Temporal Server services: Frontend, Matching, History, and Worker.

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Connecting a Spring Boot Application to YugabyteDB Managed and Deploying It to Kubernetes on minikube

Connecting a Spring Boot Application to YugabyteDB Managed and Deploying It to Kubernetes on minikube

Spring Boot is one of the most popular frameworks for building cloud native applications. It makes configuring an application easy and offers tons of starters to get you off the ground quickly. Each Spring Boot application is stand-alone and self-contained, which makes them easy to deploy in a distributed fashion – to containers or, even better, on Kubernetes.

YugabyteDB Managed (formerly Yugabyte Cloud) is Yugabyte’s DB-as-a-service and is a perfect match for Spring Boot applications,

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Introducing YugabyteDB 2.7: The Most Comprehensive Coverage of Kubernetes Environments for Microservices

Introducing YugabyteDB 2.7: The Most Comprehensive Coverage of Kubernetes Environments for Microservices

YugabyteDB is the distributed SQL database of choice for building mission-critical microservices that deliver new customer experiences, improve operations, and drive innovation. We aim to make your experience of deploying and running YugabyteDB on any infrastructure seamless, be it Kubernetes, VMs, or bare metal across private, public, and hybrid cloud environments.

With our latest release, YugabyteDB 2.7, we have added updates to give developers the scalability and resilience they need from systems of record for their microservices.

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Distributed SQL on Google Kubernetes Engine (GKE) with YugabyteDB’s Helm Chart

Distributed SQL on Google Kubernetes Engine (GKE) with YugabyteDB’s Helm Chart

The glory days of the heavy-weight hypervisor are slowly fading away, and in the last few years, containerization of applications and services is the new reality. With containerization, enterprises can prototype, deploy, and meet scale demands more quickly. To systematically and efficiently manage these large-scale deployments, enterprises have bet on technologies like Kubernetes (aka k8s), a powerful container orchestrator, to get the job done. Kubernetes was originally developed by Google, but it has been open sourced since 2014 and is today developed by a large community of contributors.

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Understanding How YugabyteDB Runs on Kubernetes

Understanding How YugabyteDB Runs on Kubernetes

As we reviewed in “Docker, Kubernetes and the Rise of Cloud Native Databases”, Kubernetes has benefited from rapid adoption to become the de-facto choice for container orchestration. This has happened in a short span of only 4 years since Google open sourced the project in 2014. YugabyteDB’s automated sharding and strongly consistent replication architecture lends itself extremely well to containerized deployments powered by Kubernetes orchestration. In this post we’ll look at the various components involved in getting YugabyteDB up and running as Kubernetes StatefulSets.

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Docker, Kubernetes and the Rise of Cloud Native Databases

Docker, Kubernetes and the Rise of Cloud Native Databases

Containerized Stateful Services Are Here

Results from the 2018 Kubernetes Application Usage Survey should put to rest concerns enterprise users have had around the viability of Docker containers and Kubernetes orchestration for running stateful services such as databases and message queues. Its exciting to see that nearly 40% of respondents are running databases (SQL and/or NoSQL) using Kubernetes. This number will continue to grow in the months ahead.

SQL and NoSQL Databases on Kubernetes (source: Kubernetes Application Survey,

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Orchestrating Stateful Apps with Kubernetes StatefulSets

Orchestrating Stateful Apps with Kubernetes StatefulSets

Kubernetes, the open source container orchestration engine that originated from Google’s Borg project, has seen some of the most explosive growth ever recorded in an open source project. The complete software development lifecycle involving stateless apps can now be executed in a more consistent, efficient and resilient manner than ever before. However, the same is not true for stateful apps — containers are inherently stateless and Kubernetes did not do anything special in the initial days to change that.

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