Introduction When you’re running MongoDB at scale with data distributed across multiple Pure Storage FlashArrays, achieving truly consistent backups becomes a critical and interesting technical challenge. In this post, I’m walking through an automated snapshot and recovery solution for a sharded MongoDB cluster running across two separate FlashArrays. While this demonstration uses two nodes for clarity, the same approach scales to N nodes across N arrays. The coordination mechanism remains identical regardless of cluster size.
As AI continues to evolve, many of us are looking for ways to leverage large language models (LLMs) without relying on cloud services. As we learned in my previous post “Using a Local Large Language Model (LLM): Running Ollama on Your Laptop”, running models locally gives you complete control over your data, eliminates API costs, and can be integrated seamlessly into your existing workflows. Today, I’d like to share how you can interact with local LLMs using PowerShell through the Ollama API.
You can now run powerful LLMs like Llama 3.1 directly on your laptop using Ollama. There is no cloud, and there is no cost. Just install, pull a model, and start chatting, all in a local shell.
Large Language Models (LLMs) have revolutionized how we interact with data and systems, but many assume you need significant cloud resources or specialized hardware to run them. Today, I want to walk you through getting started with Ollama, an approachable tool that lets you run large language models locally on your laptop.
In this post, the fifth in our series, I want to illustrate an example of using the T-SQL Snapshot Backup feature in SQL Server 2022 to seed Availability Groups (AGs) with storage-based snapshots. Efficiently seeding an Availability Group is essential for maintaining high availability and ensuring effective disaster recovery. With the introduction of T-SQL Snapshot Backup in SQL Server 2022, snapshots can now be created at the storage layer. This advancement significantly speeds up the initialization of secondary replicas, particularly in environments that handle large databases.
In this post, the fourth in our series, I want to share an example demonstrating SQL Server 2022’s T-SQL Snapshot Backup feature in a scenario where a database spans multiple storage arrays. If you’re dealing with multi-array environments, you’ll appreciate how this technique freezes database write I/O to take coordinated snapshots across volumes on two FlashArrays. In this post, I’ll walk you through the process, point out some of the script’s key elements, and show you how long the write I/O pause takes.
In this post, the third in our series on using T-SQL Snapshot Backup, I will guide you through using the new T-SQL Snapshot Backup feature in SQL Server 2022 to take a snapshot backup and then perform point-in-time database restores using that snapshot backup as the base, but this time using an Azure Virtual Machine. We will explore how to manage Azure storage-level operations, such as taking snapshots, cloning snapshots, and executing an instantaneous point-in-time database restore from the snapshot with minimal impact on your infrastructure.
In this post, the second in our series, I will guide you through using the new T-SQL Snapshot Backup feature in SQL Server 2022 to take a snapshot backup and perform point-in-time database restores using a snapshot backup as the base of the restore. We will explore how to manage storage-level operations, such as cloning snapshots and executing an instantaneous point-in-time restore of a database from the snapshot with minimal impact on your infrastructure.
Traditional SQL Server backups can struggle with large databases, resulting in longer backup times and resource contention. T-SQL Snapshot Backup, a new feature in SQL Server 2022, addresses these challenges by allowing storage-based snapshots to be coordinated through T-SQL. This feature delivers faster, more efficient backups, especially for large-scale environments with the most aggressive of recovery objectives.
Anatomy of a Full Backup Before we start learning about T-SQL Snapshot backup, let’s establish what a backup in SQL Server is.
Welcome back to the fifth installment of our blog series on using the Pure Storage PowerShell SDK2. In this post, we’re diving into a hands-on demonstration of using the Pure Storage FlashArray API to track replication performance between two arrays. This is especially useful for DBAs and storage admins, who must ensure their data replication processes run smoothly and efficiently. A typical scenario here is ensuring a snapshot is entirely replicated between sites before kicking off some other process.
Welcome back to the fourth installment of our blog series on using the Pure Storage PowerShell SDK2. In this post, you’ll learn how to use Purity Tags to classify workloads, giving you the ability to search and manage resources in FlashArray and Cloud Block Store based on the types of workloads you’re running. Using the techniques in this post, combined with those learned in our last post, Using the Pure Storage PowerShellSDK2 - Part 3 - Getting Performance Data from FlashArray you can retrieve information about subsets of objects in your FlashArray or Cloud Block Store across several performance dimensions.
