Iris Slevin’s Post

Our Foglight Series will be live tomorrow. We invite you to join us for this free session on the Query Insights features of the latest release of Foglight for Databases. Bring your questions and join us at 10 AM CST Featuring our very own Alain Abdulsater Get your calendar invite by registering here: https://lnkd.in/giqCbdzs #performancemonitoring #crossplatformdatabases #foglightfordatabases #questsoftware

I've had a lot of conversations with customers and partners about what subnetworks are in the utility network, and why/how to best use them. In response to this, we developed a whole learning series that demonstrates how and why to use the subnetworks in the utility network (https://lnkd.in/gWAFM_C5). The only problem with this content is that while it's a good starting point, it's started a lot of deeper, more technical conversations with customers and partners about how things actually work. In response to this, I've started writing several articles that provide a deep dive into how and why subnetworks behave the way that they do. Is this something you'd be interested in reading? Are there specific things you want to know more about? Let me know below!

One of the things I struggled with when I was Designing, Deploying, and Testing the World's First Multi-Home 10Gig FTTH network at Nerdalize (now owned by leafcloud), was the quality and readability of OTDR reports and aligning those with our GIS data. Especially when the reports from 3rd-party contractors arrived as printed documents (or PDFs) straight out of the OTDR itself - I constantly had to ask for the raw SOR files as I could do a better job in Python and I did with OpenODTR (https://lnkd.in/ehGbTTbK), along with a number of internal closed-source projects that integrated this with our GIS data. - It's one of the reasons I completed my Actieve Operator verbindingen in FttH PoP's certificate (amongst others). Looking at the industry today, frankly, it doesn't look like the industry has changed, ODTR reporting & trace viewing software still sucks (if it even runs), none of it seems to integrate with GIS data, and only a handful of people have ever tried OpenOTDR. Surely, I can't be the only one annoyed by this? Can the industry change? Does it need to? Can MTTR be reduced through better integration between OTDR and GIS data? Should Plaintextnerds Ltd resume the development of OpenOTDR and other tools? Share your thoughts in the comments! #networkoperations #otdr #gismapping #fibreoptic #fiberoptics #fibreopticengineer #fibreoptique #fibreopticnetwork #fiberopticnetwork #glasvezel #glasvezelnetwerk

💎 Nuggets Unearthed 🏅 From 🚨PowerPlatformTip 24🚨Merge arrays or tables. #PowerPlatform #Datamanipulation #PowerAddicts #PowerPlatform #SharingIsCaring #CommunityRocks

🤯💡 Ever wanted to merge arrays in Power Automate but keep those pesky duplicates? Check this out! 🔗 🎩🪄 This tip is like magic! Combine arrays using concat and split, and keep all your precious duplicates. No more unique-only merges with union! 💥 🎓📚 Here's what you'll learn: - How to conjure arrays together with concat - The secret sauce: using a unique delimiter like '||' - Splitting the merged string back into an array with split 💻💼 Benefits? Inclusivity, flexibility, and power! Keep every element, customize to your needs, and manipulate data like a pro. 🤔💬 So, how do YOU merge arrays in Power Platform? Share your tips and tricks below! 👇 #PowerPlatformTip #PowerPlatform #AppPerformance #DataOptimization #PowerAppsDevelopment

🚀New #WindowsServer #InsiderPreview reveals new #ActiveDirectory Forest and Domain functional Levels. Sadly it's unknown what stands behind it. Read my Blog Article 📣 #WindowsServer2025 https://bit.ly/3R45quX

In our latest blog (part 2 of our Ruddr series), we show you a clever way to fetch all your Ruddr data using Power Query – no more hassling with data chunks! In this blog, you'll learn: 📁 How to build custom functions that simplify API calls to Ruddr. 🧙♂️ The magic of List.Generate for efficient data collection in one go. 🚑 Troubleshooting tips to help you along the way. It's a step-by-step guide that we ourselves have used to unlock the full potential of using Ruddr with Power Platform. Check it out: https://buff.ly/4e7uev5 #PowerPlatform #Ruddr #DataIntegration #ProductivityHacks

Join us TOMORROW, April 11, for a new Office Hours session hosted by Andre Newman and Dan Muret! 🚀 They'll be covering: • What is Fault Injection? Learn how simulating incidents is the first step towards resolving them. • How to run blackhole and shutdown experiments using Gremlin. • How to use observability to monitor your system's response, then use these insights to make reliability improvements. Register here to grab your spot: https://lnkd.in/gjFXHfyW #Webinar #SRE #ChaosEngineering

lets continue from the last post, ..vacuum in postgressql.. now as we know vacuum is an utility to reclaim unused space from dead rows . now let's discuss more. vacuum types. 1. vacuum broadly can be done either plain vacuum operation or full vacuum operation. each operation having its pros and cons. we will discuss more on those . plain vacuum only mark the dead rows, free for further use, so in case of future insert or update , postgressql can use the space, instead on consuming new space Full vacuum - it releases the dead row occupied space from the tulle and added the space to os. but the issue with full vacuum is it creates a new tuple only with the required rows (removing the dead rows) and then postgres renames the new tuple to older one(having dead rows) and after rename completed, it drops the old table, and reclaims the space to os. but we have certain limitations with full vacuum operation. like, 1. as it creates a temporary table to move data, so for the operation to complete we need almost double size (of the candidate tuple for which we are expecting vacuum operation) , so we should have sufficient space in is for the operation. 2. it needs an exclusive lock on table till the full vacuum operation complete, so that lead to application unavailability and downtime. and it's also a slower operation as compared to plain vacuum, . now I know ur mind is crazy to learn, when and how frequently I will do the vacuum, and what I need to check after my vacuum operation, ok, so we will discuss those too.. Till the time as you go through this post you can share me your experience with vacuum operation in your environment, any issues, any amazing achievement by doing vacuum on your db. ( I know how satisfying it is to see db running faster and getting appreciation from client/ application team for the same..😁) stay tuned, ..😊#vacuum #postgresql

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