Articles

Database Replication: Open-Source Tools and Options

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For the past few years, business systems have been generating large amounts of data and need tools to manage the data. One of the business requirements was to copy the primary data to secondary databases. Several popular tools are available in the market to replicate the data from master DB to secondary DB. This article will discuss various open-source tools for DB replication and stream-based replication for real-time.

Replication is the process of sharing/storing information in multiple places to ensure reliability, fault tolerance, and accessibility. The replication options are described as follows:

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From IBM Integration Bus to App Connect Enterprise Containers

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This article is part of a series. For the previous article, see Moving an App Connect Flow Using MQ onto Containers. 

One of the most common integration points is a database, and App Connect is well suited to connecting to a significant variety of datastores. One of the most common protocols used to connect to databases is ODBC, so that is the example that we will work through in this post. 

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How To Connect a Heroku Java App to a Cloud-Native Database

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Ahoy, matey! I’m back from a short vacation and ready to continue my pet project: geo-distributed messenger in Java! 

If you’re interested in how my dev journey began (and is going), check out the previous articles in this series:

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Using Embedded Milvus to Instantly Install and Run Milvus With Python

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Milvus is an open-source vector database for AI applications. It provides a variety of installation methods, including building from source code and installing Milvus with Docker Compose/Helm/APT/YUM/Ansible. Users can choose one of the installation methods depending on their operating systems and preferences. However, there are many data scientists and AI engineers in the Milvus community who work with Python and yearn for a much simpler installation method than the currently available ones.

Therefore, we released embedded Milvus, a user-friendly Python version, along with Milvus 2.1 to empower more Python developers in our community. This article introduces what embedded Milvus is and provides instructions on how to install and use it.

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Bring Streaming to Apache Cassandra with Apache Pulsar

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Twitch, YouTube, Instagram, Facebook — virtually every major brand nowadays uses live streaming to connect and engage their audience. For enterprises and developers building cloud-native applications, this growing trend creates a need for streaming technologies that can reliably handle the rush of massive amounts of data, while also being flexible and easy to manage for developers.

One such technology is Apache Pulsar® — an open-source, distributed messaging and streaming platform that’s easy to deploy, simple to scale, and packed with developer-friendly APIs. So the next question is: how can you stream from Pulsar to Apache Cassandra®, the powerful NoSQL database designed to support data-heavy applications in the cloud?

Join our beginner-friendly Pulsar workshop on YouTube and learn how to connect Pulsar with Cassandra for streaming! In this post, we’ll set the scene with an introduction to Pulsar and guide you through four hands-on exercises where you’ll use these free, cloud-native technologies: Katacoda, Kesque, GitPod, and DataStax Astra DB. Each exercise will also be linked to the step-by-step instructions on the DataStax Developers GitHub wiki.

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Building an E-Commerce API Using Nestjs, SQLite, and TypeORM

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Introduction

Nestjs is a cutting-edge Node.js framework for developing server-side applications that are efficient, dependable, and scalable. It is simple to integrate with NoSQL and SQL databases such as MongoDB, Yugabyte, SQLite, Postgres, MySQL, and others. It supports popular object-relational mappers such as TypeORM Sequelize and Mongoose.

In this tutorial, we’ll create an e-commerce application with SQLite and TypeORM. We’ll also look at Arctype, a powerful SQL client and database management tool.

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Managing Applications in Kubernetes With the Carvel Kapp Controller

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Any typical enterprise-grade application deployed on Kubernetes comprises several API resources that need to be deployed together. For example, the WordPress application, which is one of the example applications available on the Kubernetes GitHub repository, includes:

  • a wordpress frontend pod,
  • a wp-pv-claim persistent volume claim mounted to the frontend pod,
  • a wordpress-mysql MySQL database pod,
  • a mysql-pv-claim persistent volume claim mounted to the MySQL database pod,
  • two persistent volumes: wordpress-pv-1 and wordpress-pv-2 to serve the persistent volume claims,
  • services for the database and frontend pods.

Application (or app) is not a native construct in Kubernetes. However, managing applications is the primary concern of the developers and operations. Application delivery on Kubernetes involves upgrading, downgrading, and customizing the individual API resources. Kubernetes allows you to restrict the spread of your application resources through namespaces such that you can deploy an entire app in a namespace that can be deleted or created. However, a complex application might consist of resources spread across namespaces, and in such cases answering the following questions might be a challenge:

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OpenTelemetry in Action: Optimizing Database Operations

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Many software developers can attest that some of the most significant issues in their applications arise from database performance. Though many developers prefer to use a relational database for enterprise applications, typical logging and monitoring solutions provide limited signals to detect database performance issues. Rooting out common bad practices such as chatty interactions between the application code and the database is non-trivial.

As developers, we need to understand how our database is performing from the context of user transactions. Ideally, we would have a common tool that can monitor the performance of both the application and the database concerning user transactions. OpenTelemetry has emerged as a popular tool for application monitoring, but it can also be extended for monitoring databases.

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The Serverless Database You Really Want

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The dreaded part of every site reliability engineer’s (SRE) job eventually: capacity planning. You know, the dance between all the stakeholders when deploying your applications. Did engineering really simulate the right load and do we understand how the application scales? Did product managers accurately estimate the amount of usage? Did we make architectural decisions that will keep us from meeting our SLA goals? And then the question that everyone will have to answer eventually: how much is this going to cost? This forces SREs to assume the roles of engineer, accountant, and fortune teller.

The large cloud providers understood this a long time ago and so the term “cloud economics” was coined. Essentially this means: rent everything and only pay for what you need. I would say this message worked because we all love some cloud. It’s not a fad either. SREs can eliminate a lot of the downside when the initial infrastructure capacity discussion was maybe a little off. Being wrong is no longer devastating. Just add more of what you need and in the best cases, the services scale themselves — giving everyone a nice night’s sleep. All this without provisioning a server, which gave rise to the term “serverless.”

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MySQL Essentials

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This Refcard contains all things MySQL. From MySQL’s most important applications, popular features, common data types and commands to how to get started on Linux, this Refcard is a must-read for all developers, DBAs, and other tech professionals working in MySQL.
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