Remove articles Simplifying-Distributed-Computing
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Breaking data silos: Liquid Reply’s journey to custom API observability with OpenTelemetry and Dynatrace

Dynatrace

Data is proliferating in separate silos from containers and Kubernetes to open source APIs and software to serverless compute services, such as AWS and Azure. Additionally, due to performance impact, Apigee’s distributed tracing only configures a probabilistic sampling rate, with a maximum rate of 50%.

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Introducing Percona Builds for Serverless PostgreSQL

Percona

The goal is to simplify the provisioning and management of database capacity. One approach is to separate compute and storage to allow for independent scaling. By separating storage and compute, Neon replaces the PostgreSQL storage layer with data nodes, and compute nodes are distributed across a cluster of nodes.

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Plan Your Multi Cloud Strategy

Scalegrid

In this article, we will explain the multi-cloud challenges and explain how using multiple cloud services can make your business more adaptable, ensure that your operations continue without interruption, and help you control your spending. They simplify how you orchestrate everything across the diverse ecosystem of cloud services.

Strategy 130
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Key Advantages of DBMS for Efficient Data Management

Scalegrid

This article cuts through the complexity to showcase the tangible benefits of DBMS, equipping you with the knowledge to make informed decisions about your data management strategies. ScaleGrid’s DBaaS solution simplifies database management by automating backups, scaling, and maintenance.

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Additional T-SQL Improvements in SQL Server 2022

SQL Performance

In this article, I focus on the distinct predicate and the approximate percentile functions. I’ll cover the other improvements in future articles since there’s a lot to say about those. I’ll be using the sample database TSQLV6 in the examples in this article. The DATETRUNC function. A set of bit manipulation functions.

Servers 142
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How To Build Your Own Mouseless Development Environment

Smashing Magazine

They knew a lot about Linux and the different distributions I could use. Note : The tools I advocate in this article work on Linux-based systems. This is a powerful tool that can simplify your workflow by automating away all the boring tasks. This horrible Linux distribution you need to install and configure entirely manually?

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In-Stream Big Data Processing

Highly Scalable

This article is an effort to explore techniques used by developers of in-stream data processing systems, trace the connections of these techniques to massive batch processing and OLTP/OLAP databases, and discuss how one unified query engine can support in-stream, batch, and OLAP processing at the same time. Fault-tolerance.

Big Data 154