Thanks for adding your experience. Yes, your method for sizing per user process makes perfect sense, and that is how I did it when using client/server applications. I spend a lot of time now with a CSP (web) application which has less server processes per user so the calculations are different per user.

The same with memory so plentiful now 1023 MB is often the default for routine buffer. But smaller sites or small VMs may be adjusted down.

The 60/40 came about because of a need for sizing a new site, but I also like the idea of using a % for expected active data. In the end the best path is try and start in the ballpark with the rules we have... over time with constant monitoring adjust if/when needed.

Thanks again. MO

Hi Michael, Its possible to update configuration files, run scripts etc that could be used to configure a system. So the short answer is yes. At the Ensemble level investigate what you can do with Caché[/Ensemble/HealthShare] %installer as well. For example I choose to do Caché config with %installer, rather than edit the cpf file. I use both tools when configuring benchmark servers... I install web servers, Caché and configure the OS etc with Ansible then use %installer to do the final Caché and application level work such as creating databases, namespaces, global mappings, configuring global buffers etc. You can call Caché routines from the command line so once Caché is installed you can run any routine. I'll create a post about this.

I suggest you map out the steps you need to do then get familiar with the Ansible and Caché %installer actions in the respective docs. There is a post on the Community already about %installer. 

Regards, MO

Thanks for the comments Francis, I think Mark sums up what I was aiming for. The first round of posts is to introduce the major system components that affect performance, and you are right memory has a big role to play along with CPU and IO. There has to be a balance - to keep stretching the analogy  good nutrition and peak performance is the result of a balanced diet. Certainly badly sized or configured memory will cause performance  problems for any application, and with Java applications this is obviously a big concern.  My next post is about capacity planning memory, so hopefully this will be useful - although I will be focusing more on the intersection with Caché. As Mark pointed out NUMA can also have influence performance, but there are strategies to plan for and mitigate the impact of NUMA which I will talk about in my Global Summit presentations, and which I will also cover in this series of posts.

Another aim in this series is to help customers who are monitoring their systems to understand what metrics are important and from that use the pointers in these posts to start to unpack whats going on with their application and why - and whether action needs to be taken. The best benchmark is monitoring and analysing your own live systems.

There are several more aticles to come before we are done with storage IO 

I will focus more on IOPS and writes in comming weeks. And will show some examples and solutions to the type of problem you mentioned.

Thanks, for the comment. I have quite a few more articles (in my head) for this series, I will be using the comments to help me decide which topics you all are interested in.

The latest Caché documentation has details and examples for setting up read only or read/write asynchronous report mirror. The asynch reporting mirror is special because it is not used for high availability. For example it is not a DR server.

At the highest level running reports or extracts on a shadow is possible simply because the data exists on the other server in near real time. Operational or time-critcal reports should be run on the primary servers. The suggestion is that resource heavy reports or extracts can use the shadow or reporting server. 

While setting up a shadow or reporting asynch mirror is part of Caché, how a report or extract is scheduled or run is an application design question, and not something I can answer - hopefully someone else can jump in here with some advice or experience.

Posibilities may include web services or if you use ODBC your application could direct queries to the shadow or a reporting asynch mirror. For batch reports or extracts routines could be scheduled on the shadow/reporting asynch mirror via task manager. Or you may have a sepearte application module for this type of reporting. 

If you need to have results returned to the application on the primary production that is also application dependant.

You should also consider how to handle (e.g. via global mapping) any read/write application databases such as audit or logs which may be overwritten by the primary server. 

If you are going to do reporting on a shadow server search the online documentation for special considerations for "Purging Cached Queries".

Thanks! Yes I wrote the wrong way around in the post. I have fixed this now.