Delete records like a Ferrari

Delete records like a Ferrari

“Do you really need to delete records like a Ferrari?” – that question was posed to me when I, a few years ago complained about the bad performance of the Bulk Deletion functionality in Power Platform (at that time Dynamics 365 Online) to a friend at Microsoft who I will not name. And my simple answer is yes, we do need to delete records like a Ferrari, for many reasons. I will discuss why in this article and I have for that reason also created an Idea on the Power Apps Community site on this subject and I hope that you agree with me and vote for it! You will find it on the link below.

Click here to go to the idea article and vote for faster bulk deletion

So, why is a fast bulk deletion important. I would say there are several reasons and I will walk through the ones that I have thought of, if you have any other, please drop a comment.

  1. Keep your data in check – remove unnecessary data
  2. GDPR and other compliancy and legal issue
  3. Power Platform growing into Citizen developer platform
  4. Entitlements effectivly blocks using external tools

Keeping data in check

For larger organizations, especially with many integrated modules and systems, many running Flows, workflows, Customer Voice surveys etc. the system will generate a lot of data, especially if it is a B2C scenario. A few of these have built in features that automatically remove old logs etc but most don’t and we as admins and system caretakers (isn’t it a fancy title!) need to tend to this, typically by setting up jobs that clean old data. I would recommend looking at the PPAC statistics of which tables are the largest and having a practice of doing so at regular intervals and downloading it. That way you can see the trends over time. A suggestion for an addon to the CoE Starter kit would be a trend analysis of all tables with growth numbers per week for each tables with warnings for quickly growing tables and prognosis.

However, as instances start growing over 50-100 GB in size (of structured data) it soon becomes too large to handle the data with bulk deletion. Some tables might still be managable this way, but in general the performance is has is, when I have tried to measure it (albeit a few years ago) was around 1-3 records per second. A customer I have, working with B2C for whom I wanted to remove their Voice of the Customer, which had been used a lot, had over 50 Million Survey Invites. It is not possible to remove the solution without first removing the data, and if we were to use Bulk Delete and put it on crack and it got to 10 records per second, it would still take around 2 months. I now did it with SSIS/Kingswaysoft and it took a few days. If Bulk Delete could reach around 200 records/second, it would take a little less than 3 days.

I have also noted that when trying to Bulk Delete very large datasets, Bulk Delete simply fails, as I think the FetchXML query might do a SQL Timeout or something like that. Not exactly sure what happens. As it works with Kingswaysoft I don’t know what might be the difference.

GDPR and other compliancy and legal issues

As GDPR and other similar compliancy regulations have come into play in many countries around the world, it has become ever more important to stricly follow these detailed instructions. These might be simple when you look at them on a Power Point C-level perspective but when you dig down on the detailed level, where they actually need to be implemented, things seldom are as simple as in a Power Point.

Power Platform growing into Citizen developer platform

As the Power Platform grows from being just a platform on which Dynamics 365 is delivered to being a huge platform for digitalization entire organizations with almost 100% user saturation will be coming starting to use Dataverse. The amount of data being stored in dataverse will hence grow to massive amounts and hence an effective tool to manage this data is most important. It is probably even important to such a level that Bulk Delete cannot even scratch the top of the iceberg of what we need to be able to do on a data management perspective as data will be growing and expanding in heaps and bounds and admins will not only need to manage Flows and Apps but also data in size and content.

Entitlements effectivly blocks using external tools

The soon to enacted entitlements, as mentioned in my previous post, Entitlements are not throttling | Powerplatform.se, also effectivly stop the use of external tools like SSIS/Kingswaysoft for deleting unwanted data. One of the customers I am working with generate between 10-20 M API requests PER DAY, and the bulk of these are from deletion jobs or other maintainance jobs trying to keep track of the instances. With the new entitlements charge, there is no way this can be continued, but the customer is cought between a rock and a hard place as either the data grows by leaps and bounds or the API calls becomes a huge cost and there is no easy way to handle it. What advise am I to give the customer? I would think that the most reasonable thing would be if the platform made the tools available to maintain the data to avoid the costs. If this is using bulk delete or some other more elaborate feature, that is up to the product team but I do think they should hold off on activating the entitlements until there is a good alternative for managing an instance data within the platform before this (not generating API requests).

What else is missing?

Bulk deletion is not only not being performant enough, it also lacks the effective filtering logic that is required for more complex queries. For some customers a I have had to construct rather elaborate SSIS scripts which start with a complex FetchXML and the filter the data through several Cache Transforms, for instance with GDPR consents and similar to be able to get the final list. I must admit that I havn’t tried using the new T-SQL connector for this, that it could handle the full T-SQL complexity and that it is implemented in Buld Delete or Kingswaysoft as a means to make querying more powerful.

Entitlements are not throttling

Entitlements are not throttling

Should a five user organization be entitled to the same amount of compute as a 5 000 user organization?

Entitlements are the limitations that Microsoft have set on the platform that are based on which type of license each user has. This is not the same as the API Service limits which are much more liberal. The entitlements have not yet been fully enforced as the reporting capabilities of the platform have not been rolled out fully yet. But they will. With this blog post I attempt to give my perspective on entitlements on the Power Platform and Dynamics 365 (CRM part).

My previous post was about API Service limits which are commonly referred to as the throttling limits of the platform. The entitlements limits (and here) have another part in the Microsoft docs that go into these a bit deeper. I’d first like to go into why there are two different “protections” or limitations.

The API Service limits are there to protect the platform from noisy neighbours. Some of us, that have been around since the earlier days of Dynamics 365/CRM online remember that the performance used to be rather shaky. This could often be due to the fact that some other instance on the same hardware your instance was hosted on, was being slammed with massive amounts of requests, like during a migration. To make sure that this “noisy neighbour” problem doesn’t occur, the API-limits have been put in place and since they have, things have been a lot better so they do seem to work.

The Entitlements are there for another reason. Let’s say you buy two (2) Dynamics 365 Sales users and then use integrations with a custom built front end for B2C purposes with one of those users (or an app user), and, still within the limits of the API Service limits, hammer the API:s from day to night with an amazing amount of requests. The B2C aspect would be covered from a licensing perspective in what was previously called “external connector” license and is nowdays included in the normal license. However, the amount of compute that the instance is utilizing is way above what you are paying for. This is the reason why Microsoft have created the entitlements, as far as I know anyway. And I think it only makes sense that there is some kind of reasonable proportionality to that.

To quote the Microsoft docs page: “These limits represent the number of requests users are entitled to make each day. The allocated limit depends on the type of license assigned to each user.

What is a request?
The first question is then, what is a request? Previously we were told, that a batch request (ExecuteMultiple) was one (1) request but that has since changed and is now considered to all the subparts. I would even think that a batch request has the extra overhead of the batch itself. Hence, a batch request with 10 creates, will actually be counted as 11 requests; 1 for the batch, and 10 for the creates. The exact definitions are not disclosed but we get a rather good description from the docs with this paragraph, where I have highlighted some interesting parts:

“For Dataverse, API requests include all data operations that interact with table rows where rows are created, retrieved, updated, or deleted (CRUD). Special operations such as share and assign are included because they are considered updates. These requests can be from any client or application and using any endpoint. These include, but are not limited to, operations performed by plug-ins, async workflows, custom controls, and $batch (ExecuteMultiple) operations. There are a small set of system internal operations that are excluded, like login, sign out, and system metadata operations.”

The important takeaway here is hence that you cannot create a workaround by using a plugin and using the internal context pseudo-api to do the calls, as these are counted as well. Difference might be that they are done in the context of a specific user and that user has a rather large entitlement, which might hence “flatten the curve” so to speak. An interesting aspect, though is the exception to this rule:

“Power Platform API request allocations include use of Power Automate, AI Builder, and Connector APIs. All requests through a connector that result in a Dataverse request will represent 1 Power Platform request.”

This strongly indicates that Microsoft wants us to use the Power Platform tools and that these should not at least have additional costs. There are, however, still some inconsistencies in this area that I really hope that they fix, such as:

  • Microsoft supplied integrations in ADF
  • Integrations to Dynamics 365 Finance & Operations
  • Dynamics 365 Business Central
  • Exports to ADLS
  • Data Export Service

The latter two can be really heavy on the API:s if you have an enterprise system or a B2C system. I work with a customer which currently have a database of >400 GB which uses Data Export service and the amount of notifications on the Data Export Service just for Contacts for a year often exceed the hundreds of millions.

Other areas which are not mentioned but which I think are included are addon first-party apps like Customer Insight (Sales Insights) which actually uses a ADLS in the background (not that you can actually access it). I have heard stories of support tickets where Microsoft support have blamed the API Service protection for hitting the ceiling when it was Sales Insight that caused it, which would indicate that these are actually counted. I think the intention is to include all of these so that the license for these cover the API entitlements. I just wish they would fix the gaps as customers are being affected.

Entitlement telemetry might not be the same as API Service protection telemetry
That actually brings up another interesting aspect. The measurements that are used for the API Service protections are probably NOT the same as the measurements that are used for entitlements, but this is based on my personal hunch, and not any kind of facts. Mainly based on the assumption that I think that the areas that are excluded from entitlement measures above, probably are not excluded from the API Service protection.

Another definition of request!?
On this page there is another definition of what a request is that is different from the one above. I believe this is older than the one mentioned above, as it uses the term “CDS” which has been replaced by dataverse now. I am not sure though as this page last change is dated on the second of feb 2021 while the other the 5:th of March 2020. The main difference is that this does not make the exception mentioned in the article above, hence every call through a connector, every successful or failed call in Power Automate will be counted as one request. Hopefully Microsoft will clear this up soon.

Entitlements per user
At this link you can find the specific entitlements per license. They are all measured on a 24 h period and range from 20 000 for the full enterprise versions of Dynamics 365 to Power Apps per app plan which get 1000 requests.

Entitlements for non-licensed users, which mainly will be application registrations/application users are fixed per tennant based on the highest licensed purchased on the tennant. This means the following pooled included non-licensed entitlements.

  • 1 Sales Enterprise -> 100 000
  • 1 Sales Professional -> 50 000
  • 1 Power Apps license -> 25 000
  • 1 Sales Enterprise, 1000 Power Apps -> 100 000
  • 10 000 Sales Enterprise, 10 000 Power Apps -> 100 000

The important note here is that this does not scale at all, but is fixed. And if you plan to do some integrations with a Power Apps only tennant, you’d be wise to buy at least one Dynamics 365 Enterprise, just to get the non-licensed user entitlements, as the Sales Enterprise is around $95 and each additional 10 000 is $50, which means that the saving to get to a 100 000 calls / 24h is:

50*(100 000 – 20 000)/10 000-95= 400 – 95 = $305/month

Buying extra capacity
It is also possible to buy extra API capacity. You can read more about this in the Licensing Guide for the Power Platform. I am not able to find a current price for this at this time, but the list price was previously set at $50 (per 10 000 for 24h). These are then to be allocated to the users as you wish.

Overshooting
Users will not be blocked from using apps for occasional and reasonable overages at this point of time.
What will happen when or if you overshoot? A very important question. Most organizations will at some time do this, most probably during migration of data from the old systems. The statement from Microsoft above, especially the highlighted “at this point of time.” is rather omnious. It does indicate that at some time the hammer will come down. But at this time it won’t, admins will be harassed with emails about overshooting and just as with overshooting data capacity, they might start with blocking some features when you are overshooting. It is mentioned in one of the articles in the FAQ that after the transition period they will start blocking. So that will be a real fact unless they change their mind on that.

My very strong advice, is hence that all organizations that are not compliant need to start looking at this as soon as possible. I have some tips on what you can do further down in this article. Please refer to these and feel free to leave a comment if you have questions on the subject not answered here.

ISV Bundling
There are many ISV:s which export rather large amounts of data. The first ones that come to mind are the Marketing Automation products like Adobe Marketing, Click Dimensions, Dot Digital and more. These all synchronize contacts, marketinglists and marketinglistmembers, at least, which for larger installations can be quite large datasets. I do think it would be advantageous if these ISV:s could include the API Entitlements that are required, or if they are billed by Microsoft to the ISV which in turn bills the customer with a surcharge. At the very least Microsoft have to take ISV:s into the equation here as they are an essential part of the ecosystem, especially from the customer perspective.

Tips on how to handle future entitlement enforcement

  1. Start by using the PPAC to get an overview of how your situation looks even though you might not get an exact picture.
  2. Consider the overhead of batching. There can be performance advantages to batching as mentioned in my previous article. But there needs to be
  3. Consider “outsourcing large datasets” to ADLS – although the ADLS export also uses API-calls.
  4. Maybe not a problem if short term – for now
  5. Consider using official connectors or Power Automate instead (although that might cause costs in itself)
  6. If building Power App licens based solutions and you have heavy integrations, buy one Dynamics 365 Enterprise license.
  7. If possible impersonate the data load over all the users. This can be done with plugins and synchronous workflows for instance. Patterns that can be used in this case can be staging tables in dataverse where the owner is set and then a plugin is triggered that slices the row into many pieces as the owner of the import record. I am not sure if impersonation using the API will have any effect on this. That needs to be investigated. If it can be used to spread the load, that would be a good pattern to use.
  8. Refactor inefficient code. Depending on implementation maybe increase use of caching or other techniques to reduce the amount of requests. Make sure you have skilled Power Platform/Dynamics 365 developers working with development as knowing how to do this very particular to this platform.

Microsoft representatives, locally in Sweden anyway, are saying to our customers and potential customers that they need not worry about this. I find that message a bit mixed with what I read here. On the other hand I think this will be a very rough change for many organizations. If your organization will be very negativly affected by this and you feel that you are still paying “fairly” for your part, then I suggest you contact Microsoft and describe your business scenario in detail. If you need help with who to contact you can always start with the people who have written the articles who you can ask to forward the articles to the right people, use your local user group or ask some local MVP for help as they often have contacts directly with the product group (and many other experts do too).

Good luck and do leave a comment or share this if you like it!

Thoughts on throttling updates

Thoughts on throttling updates

Microsoft recently (in February) published some updates to their documentation regarding Service protection API limits or as they are sometimes referred to, throttling. Some of these, like the new recommendations on how to handle batching are rather interesting and I thought I’d give my 2 cents about this. They are also eluding a bit regarding how the network infrastructure is set up for the deployment and how to optimize when handling larger workloads using the affinity cookie setting. I did find this rather interesting too.

So, first of all, a quick recap for those who arn’t into the throttling and API service limits. There are three different limits set up for Power Platform. You can read the details here: https://docs.microsoft.com/en-us/powerapps/developer/data-platform/api-limits#how-service-protection-api-limits-are-enforced

In short, within a 5 minute sliding window, you cannot exceed the following for one specific user.

  1. Not more than 6 000 requests.
  2. Not more than 1 200 (20 minutes) execution time – equal to 4 parallell processes if running at full capacity
  3. Not more than 52 request at the same time (concurrently).

Generally, if you do not use batching, you would typically run into the first (1) or the third if running unlimited threading. If using a connection pooling with 52 connections, then you probably run into the 1:st, and if you use complex request that cause cascading behaviours or batching, then you typically run into the second (2). There are exceptions that match these. Do refer to the official docs above for details about that.

Now to the interesting part.
There is a new section that is attempting to tells us how to maximize throughput. First of all, I think this is great. We really need this and we need Microsoft to tell us how to not only use the platform, but how to efficiently use their platform.

“Let the server tell you how much it can handle”
This section is interesting as it recommends a rather complex approach to how to work with performance. As they further down recommend using threading, they essentially recommend building logic that dynamically increases and decreases the number of threads as the platform informs you that it has capacity. This brings me back to university math, and trying to figure out the derivative of an unknown function by sampling and finding the local max. I do however, think this is a rather tall order to recommend to your average developer. But it would be a great community tool, so feel free to build it. Consider the challenge set. Best would be if Microsoft included this in the SDK of course.

Use multiple threads
In this part they recommend using multiple threads. This is also my experience that this is a good idea as the processing time and latency per package causes certain delay on a per-message basis. By utilizing multi-threading with multiple connections, this overhead can be reduced. As there is a limit of 52 concurrent connections, I would recommend using a maximum of that amount of connections/threads per user.

Avoid batching
Now this is really interesting. The previous recommendation was to use batching to be “nicer” to the API and get increased performance. The recommendation now is the direct opposite. This is based on the fact that the overhead in a WebAPI JSON-message is significantly smaller than that in a SOAP message and that this will reduce the difference between using batching and non-batching. They do, however, recommend using smaller batch sizes still. This is also my experience when working with Kingswaysoft. I typically (it depends on the instance and which table I am using) start with 16 threads with batches of 10 or 20. This has typically given me the best performance, with performance of +300 records/s.

There is also a comment about the fact that the using batching does not bypass the entitlement limits, ie. 20 000 API calls/24 hours for an enterprise user/100 000 API calls for all non-licensed users and so on. See more on the Entitlement limits based on which license you have here. Hence this calculation is done by after exploding the batch on the servers. This is also news to me as I previously was told that batching was exactly the way to go to limit the amount of calls.

Removing the affinity cookie – server multiplexing
The details being eluded to in this section are very interesting. If I understand it correctly, the logic is as follows:

The point being that, shutting off the affinity cookie int the HttpClient will allow for more wider use of all the servers in the node (the entire setup of all the Frontends, backends, NLB etc.)

What I do wonder, is if it would be possible to store the Affinity Cookie, and hence pool it on the client side. As each time you need to hit a new front end you will loose some time while it warms up your instance, and it would hence be advantageous to be able to more tightly control this. Maybe even this could be another community tool for someone interested?
I also think, I havn’t tested this, that you will get better results when working with removed affinity cookie if you do use batching, at least until all the frontends have been warmed up to your instance.

Do also note a very important sentence; “This increases throughput because limits are applied per server“. We do not know how many servers are used in a node frontend, but probably more than 10. Removing the affinity cookie could hence increase performance by at least one order of magnitute.

User multiplexing
As all API limits are calculated on a per-user basis, another way to increase performance is to use what I like to call user multiplexing. This means that operations are done using several different application users at the same time. There is of course some admin work that needs to be done to set these up, and there is no OOB way of doing this but with SSIS and Kingswaysoft it is rather straight forward; just create several connections, one per user, configure them per user and then use the “Balanced Data Distributor” which can be found in the productivity pack to spread the data to different destinations that are using the different connections.

My tips
My tips for getting good performance, for large scale datasets, are hence the following based on these new facts:

  1. Continue to use batching, but don’t use huge batches. Probably around 5-20 will be ok.
  2. Use multithreading. I typically use around 16, but that was before I knew about the removal of the affinity cookie. Hence I would recommend 16 per server. But I cannot tell you how many servers there are.
  3. Use the remove affinity cookie setting, and if possible, figure out some way of pooling the affinity cookies instead.
  4. Make sure your application can handle the exceptions regarding the API-limit and have some reasonable strategy for working with them. I have found that blasting the API for 5 minutes at max speed, then backing off for 5 minutes, then going full throttle again for 5 minutes, has given me better throughput overall than “being nice” and just finding the “right” speed to use to not be throttled. Not sure this strategy will work in the long run though.
  5. Use application user multiplexing.

Suggestions to ETL vendors and others
My suggestions to ETL vendors and others who build connections to Dataverse that require high performance are:

  1. Start by visualizing the affinity cookie setting so that it is possible to set this as wanted.
  2. Include multithreading, batching and application user multiplexing into the standard dataverse connections.
  3. Figure out if there are an points to pooling the affinity cookies, and if so, include this into the connection.
  4. Make the connection auto-optimize with the data it is currently sending. Ie. how many threads, size of batches, size of affinity cookie pool and number of application users to utilize.
  5. Have different strategies for utilizing application users instead of just spreading the data evenly, it could be that one is used until it receives an exception an then it is put on hold for 5 minutes and then another is being used. Or a combination of these two if there are five application users, 3 might be used for data transfer, and two on hold in case one gets an exception and needs to be put on hold.

I hope this has given you some insights and that my 2 cents got you this far. Feel free to leave a comment if you have an questions!

Custom columns on systemuser  – good or bad?

Custom columns on systemuser – good or bad?

Some people might have heard about an industry best practice that you should never have custom columns (fields) on the systemuser table (entity) in dataverse. Is this true and why so? This article is based on my understanding of how the inner workings of dataverse works and hence what you need to think about when designing your application to not unintentionally create an application that destroys your environments performance. In short, be careful about adding custom columns to the systemuser and if you do, only add fields that have static data, ie data that doesn’t often change. Let me describe this in more detail.

First of all, I would like to give credit to a lot of this to my friend and former Business Application MVP Adam Vero, who described this in detail for me, I have also discussed this with other people and since had it confirmed but not actually seen it documented as such, why it might not be fully official. I do, however, not see any problems with people understanding this, rather the opposite.

Dataverse is an application platform that has security built into it as an integral part, there are security roles, system users, teams and business units that form the core pieces of the security in the system. As the system will often need to query data from these four tables, it has a built in “caching” functionality that per-environment loads these four tables and precalculates them into an in-memory table for easy and fast access. This is then then stored in-memory for as long as the data in these four tables is kept static, in other words, nothing is changed, no updates, no creates, no deletes.

What could then happen if you add a column to the systemuser table? Well, that depends. If this column is a column that you set when the user is created and then never change that, that isn’t a problem, as this wouldn’t affect the precalculated in-memory table. However, if the data of these columns are constantly being changed, like for instance, if you add a column called “activities last 24h” and then create a Flow which every time an email, appointment etc. is created it will increment this by one per day and reset it every night for every user. Then every time, this writes to any user, the precalculated in-memory table will be flushed and recalculated before it can be used again causing a severe performance hit that can be very hard to troubleshoot.

How would you create a solution for a the “activities last 24h”, as described above then? Well, I would probably create a related entity called userstatistics with a relationship to systemuser. In this case it could even be smarter to have a 1:N relationship to this other entity as you could then have many userstatistics per user and measure differences in activities day by day.

But wouldn’t the NLB:s (Network Load Balancer) make this irrelevant as each environment is hosted together with many others? Well, I cannot, due to NDA talk about the details of how the NLBs actually work for the online environements, but I can say this, no, it is still relevant. The NLB will make it so for performance reasons.

As for teams, it is only the owner teams that count in this equation, the access teams are only being used for sharing or other types of grouping and hence never part of this pre-calculation.

And the savvy person would then of course realize that the multiplied size of:

systemusers x owner teams x business units x security roles

Does make up the size of this pre calculated table and for large implemenations, this can give indications of where performance can start to make a difference as every time a user does not have organizational level privilige, the system has to go through the entire table to check what is right. And then of course the POA. But that table is story for another day and another article.

Just final word. The platform is constantly shifting and even though this was true and probably still is true, there might be changes going on or that have happened that I am unaware of, that have changed how this works. If I hear of this, I will let you know.

Jonas, FetchXml Builder and Kingswaysoft

Jonas, FetchXml Builder and Kingswaysoft

As you probably will have heard by now, my colleague and friend, Jonas Rapp suffered a stroke about two weeks ago. Daryl LaBar, Carina Claesson, Benedikt Bergmann and I talked about this on the XrmToolCast which you can listen to here: https://xrmtoolcast.libsyn.com/coming-together-to-support-jonas

I would, with this post, like to give my personal perspective on how I use FetchXml Builder as an integral part of making scripts with SSIS and Kingswaysoft.

And before I begin, I would just like to urge everyone to donate a dollar or two to Jonas as he is having tough time. Or just share your story of why you love to use his tools. Everything matters. And if you want to donate, just use this address: https://fetchxmlbuilder.com/donate. If he has helped you, as he has helped me, why not help him back. Why not leave a comment with how much you donated, and when we have 10 comments, I will share how much I have donated.

With one of my customers, I work a lot with trying to manage their rather larger database, around 500 GB, and doing what I can to make sure that it doesn’t grow out of proportion. This also entails looking into GDPR rules and making sure that personal information is removed, and kept according to specific rulesets that become rather complex. So complex that one advanced find query isn’t enough to define them. And the removal of data is not seldom in the millions of records, why I need a tool that can do deletes quickly. Hence, I have found that SSIS and Kingswaysoft with Azure Data Factory for deploying these packages to be run continously, is a good method.

However, there is a very important piece of the puzzle that is missing when you want to do this, and that is being able to assemble the FetchXmls to the nitty gritty level that they are as efficient as possible and for that job, there really is only one tool, FetchXml Builder. Hence I often set up my general idea of how I would like the rules to be executed and then start assembling the data often into different Cache transforms, and then filter the dataflows using lookups based on this.

So, for me, FetchXml Builder is essential when working with this and this is my story of how critical it is for me.