A Fine Slice Of SQL Server
Ajay Dwivedi has an update to SQLMonitor:
I have been using SQLMonitor extensively for monitoring & performance tuning of my SQLServers. To make it more and more useful, I have added more functionalities to the tool in version v1.6.0.
Click through for a list of enhancements and links where you can learn more about SQLMonitor.
Comments closedKiana Harris lays out some challenges:
As organizations embrace containerization and Kubernetes for their applications, the need for seamless portability across the Kubernetes ecosystem coupled with cloud object storage and local persistence has become a pressing concern. In this blog post, we will dive into the core problem and dissect the complex challenges that customers face in achieving containerized app portability.
Read on for the list of challenges, followed by what you can do to address them. This is at a really high level but can provide food for thought.
Comments closedBang Nguyen wants to see what’s going on:
Observability of a system includes Logging, Tracing and Metric. Today, we will go to detail how to implement observability’s elements on a K8S environment use Promtail, Open Telemetry Collector, Loki, Tempo and Grafana bellow is the demonstration of system we will implement
Click through for a detailed guide showing how to do this.
Comments closedMuhammad Ali explains what information you can find regarding tables in Postgres:
Database monitoring, performance tuning and query optimization are critical operations for maintaining an efficient database system. A key component in PostgreSQL for this purpose is the pg_stat_all_tables view.
pg_stat_all_tables offers real time statistics on table activities such as number of sequential and index scans performed on a table, updates, deletes, inserts, and more. It also offers information on dead tuples along with vacuum and analyze stats which enables DB admins to make data-driven decisions. Here’s a table detailing the columns in the pg_stat_all_tables:
Click through for that table about tables.
Comments closedLance Wright shows off a dashboard:
At Ignite 2023, we announced the public preview of performance dashboards for SQL Server enabled by Azure Arc. With these performance dashbaord, DBAs and IT Admins now get performance monitoring right from within Azure. No need to setup and login to another tool or remotely connect to the SQL Server to run performance queries. Let Azure Arc do the heavy lifting so you can get to your performance metrics faster.
This is another tool in the toolbox of DBAs, IT admins, and cloud specialists looking to gain better visibility into their hybrid and multi-cloud workloads. If a SQL Server enabled by Azure Arc meets the requirements for data collection (see “How to enable performance dashboards”), Azure Arc will automatically collect the following types of data from the Dynamic Management Views (DMV) datasets oof the SQL Server:
Click through to see what it includes and how to enable it.
Comments closedTomaz Kastrun continues a series on Microsoft Fabric:
If you have used Power BI services in the past, you will be on board immediately. The outlook is the as it is with the Power BI. You will only need additional credentials to access the services. In general, you will need Azure subscription, Power BI service already enabled, and the ability for your organization to enable Fabric with Admin roles
Click through to see how to enable Microsoft Fabric in your environment.
Comments closedRyszard Szymanski tracks memory utilization:
R/Shiny allows you to prototype a working web application quickly and easily. However, with increasing amounts of data, your app may become slow and, in extreme cases, crash due to insufficient memory.
When the worst-case scenario happens, we need to figure out a way to lower the memory usage of our app to avoid those crashes.
A crucial part of optimization efforts is benchmarking how much memory our app is consuming. This allows us to check if the changes we made to the app are indeed moving us in the right direction.
In this step-by-step guide, we will describe how to do that based on an example application.
Read on for the process and how you can diagnose memory problems. H/T R-Bloggers.
Comments closedJosephine Bush works around a deprecation notice:
I’m saddened that the Workspace Summary is being deprecated in Log Analytics Workspace. I am trying to reproduce it in workbooks. While it isn’t an exact match, workbooks provide me with enough information to use and share with others.
Click through to see what you could get from the Workspace Summary and how to re-implement a fair amount of that in Azure Workbooks.
Comments closedAs part of my PASS Summit 2023 community session, I created a hybrid of two of my favorite sys.dm_io_virtual_file_stats scripts. It captures data from the DMV at two different intervals, to help you diagnose SQL Server I/O related performance data.
Click through for more details and to get a copy of the script.
Comments closedSandeep Pawar talks about fallback options:
When you create a Direct Lake semantic model, by default it is in Direct Lake mode, i.e. you will directly query the delta table from the lakehouse/warehouse. This is what we want because the query performance will be very much comparable to the import mode. However, under certain circumstances, the DAX query can fallback to DirectQuery if Direct Lake limitations are hit.
Read on to learn more about circumstances in which this could happen and ways to change the default behavior.
Comments closed