Sitecore Session Persistence Notes

I’ve neglected this blog of late, being focused on a number of “not easily blogged about” scenarios across several Sitecore projects.  It’s too bad, because the work is very interesting, but it doesn’t lend itself to a page or two write-up with a digestible take-away for the general Sitecore community out there.

I do want to keep in the habit of blogging, though, so I’m going to mention this ongoing discussion I’ve been a part of about session management with regards to Sitecore.  There are a few options for managing HTTP session state with Sitecore covered in https://doc.sitecore.net/sitecore_experience_platform/setting_up_and_maintaining/xdb/session_state/session_state: SQL Server, MongoDB, and Redis.  Those three technologies are really just the tip of the mountain, as implementation details for each can get quite detailed.  For the discerning Sitecore implementation, it can be useful to understand the nuances of each session state provider.  While not an exhaustive look at any one of these solutions, I wanted to post some notes on each one given the current state of Sitecore architecture (June 2017):

SQL Server

This is often the default session provider we gravitate to.  The SQL Server “Boost” script from Sitecore is something we’ve used on implementations (see “Optimize SQL Server performance” on that link), but it is not without it’s rough edges (see our Rackspace write-up on how to alter permissions so TempDB is reliably available across service restarts).

You’ll notice the approach for improving SQL Server performance with session state is all about getting session state “in-memory” to the furthest extent possible.  Remember this when we examine the other two providers below . . .

I will say that, generally speaking, SQL Server is easy to administer as it’s a well-known technology and updating it, scaling it, managing fail-overs, etc is simple compared with the alternatives.  SQL Server has been part of the Windows dev stack for ages, now, so it’s often the default session provider one gravitates to.

MongoDB

With MongoDB serving as the persistence layer for Sitecore’s xDB, it became a fully supported and viable option for HTTP session state with Sitecore at the same time.  The comparative performance between MongoDB and SQL Server is up for debate (Redis too, for that matter!), and it usually comes down to testing based on how the specific implementation is using session with Sitecore etc; I’m not going to hazard any generalizations on relative perf, as that’s not really the point of this post.

Instead, I’d like to point out how MongoDB does not come in just a single flavor.  The two most common flavors, or “storage engines,” are MMAP and WiredTiger, but there are still others designed to serve specific use cases.  Take, for example, the Percona Server for MongoDB hosted by ObjectRocket that has a posted option for the RocksDB storage engine.  RocksDB with MongoDB may not be a great fit for Sitecore session state (RocksDB is tuned for write-heavy work loads — and, in some cases, if you’re making extensive use of TTL indexes for Sitecore then RocksDB fits those scenarios in certain appealing ways), but it does open the door to MongoDB being more than just a one-size-fits-all data repository (read more about RocksDB and it’s Facebook pedigree here).  One MongoDB storage engine option that is easily overlooked is for WiredTiger “in-memory” that will force data to be stored in RAM . . . and this is perfect for HTTP Session State for most Sitecore builds.

In fact, if you consider the SQL Server “boost” approach that uses TempDB to store session state for Sitecore . . . WiredTiger “in-memory” is attacking the problem from the same direction.  Store everything in RAM!  This is why one must be cautious with general comparisons between SQL Server and MongoDB, the devil is always in the details: a far better comparison would be “boosted” SQL Server for Sitecore using TempDB vs MongoDB WiredTiger “in-memory” storage engine.  And note the network latency . . . and the size of the session objects . . . and you’re getting the point, I trust.  To really answer the SQL Server vs MongoDB question for Sitecore sessions, one has to develop a matrix of performance evaluations and level assumptions across the board.  “It depends” is the only honest answer that doesn’t come with a list of caveats.

If you’re curious on this MongoDB topic for your project, go to http://objectrocket.com/docs/mongodb_plans.html and spin up a WT 3.2 storage engine plan for 5 GB of storage (this allows 1.5 GB for RAM).  1.5 GB for RAM is going to be overkill for most small/medium Sitecore implementations — but again, you’ll want to test with your specific session data set to see!  Furthermore, network latency of 10 ms or less is going to help make the most of an ObjectRocket hosted MongoDB service like this — otherwise, the network latency may not make it worth the money.  Let me know if you pursue this with ObjectRocket, as there are some benchmarking measures we want to do but we haven’t had a real implementation to try it out on.  So if you feel like being a guinea pig, please let me know at grant.killian [at] rackspace.com.  It would be great to have real world metrics to prove this all out.

Redis

If the way to get the best session management perf out of SQL Server and MongoDB is to find in-memory solutions, Redis looks like the slam dunk since it’s just an in-memory storage solution.  We find most clients aren’t interested in managing Redis infrastructure, so again a hosted option such as ObjectRocket has appeal.

Sitecore relies on the StackExchange.Redis assembly, which doesn’t support Redis Sentinel — it’s a bit of a saga at https://github.com/StackExchange/StackExchange.Redis/pull/406;  therefore there’s not a great high availability story with the self-hosted Redis and Sitecore right now.  How concerned one should be with HA of fairly transient HTTP Session State for Sitecore, however, is an open question.  I usually wouldn’t worry about it too much.  Honestly, Redis is a technology that we’re just now starting to get really serious about at Rackspace so our sophistication in this space will improve dramatically in the months to come.  Between Azure Redis and all the Sitecore PaaS movement we’re seeing, it’s become a key player in a lot of Sitecore architectures.

Azure Search compared to Solr for Sitecore PaaS (Chapter 2: Querying)

I carried forward my Azure PaaS benchmarking work from earlier this month (see this post on the indexing side of the equation for the start of the story).

For a quick refresher, I’ve used an ARM template based deployment of Sitecore to get a system resembling the following:

ARM Templates Arch

The element I’m exercising in the benchmarks is how Sitecore’s web servers work with the “Search” icon in the diagram above.  I tackled the document ingestion side (how data gets into the search indexes) in my earlier post.  This post addresses the querying side of things (how data gets out of the search indexes).

By default, Azure PaaS search with Sitecore is configured to use Azure Search.  Solr is another viable option.

Here’s where I’ll interject that Coveo also has an excellent search technology for Sitecore.  There are specific use-cases where Coveo is a strong fit, however, and in my indexing the sitecore_core_index evaluations in the earlier post Coveo would not be considered a good fit.  This changes, however, for the set of benchmarks I’ve run in this post.  I am in the process of testing the Coveo approach in Azure PaaS for Sitecore . . . it’s hot off the presses, so there are still rough edges to work around . . . but Coveo is not part of this write-up for the time being.  I will post an update here once I’ve completed the analysis involving Coveo.

In considering Azure Search vs Solr, I used a methodology with JMeter laid out in a great KB article from Sitecore at https://kb.sitecore.net/articles/398589.  I have a LaunchSitecore site running and I use JMeter to automate visits to the site, simulating simple user behaviour.  I don’t go too crazy with this, because I’m more interested in exercising a basic Sitecore work load than doing a deep-dive in xDB traffic simulation.

My first post showed a clear advantage to Solr for the indexing side of search, but for the querying side I can say there is very little variance between Azure Search and Solr.  Sitecore does a good job of protecting data repositories with layers of data and html caches, but even with those those features disabled (we’re talking cacheHtml=”false”on the site definition, <cacheSizes> configuration all set to a heretical zero (“0”), etc) there isn’t a significant difference between the two technologies.

I’m not going to put up a graph of it, because the throughput as measured by JMeter for tests of 20, 50, 100, 200, or  more visitors performed almost the same.

I could develop a more search heavy set of benchmarks, performing a random dictionary of searches against a large custom index that Sitecore responds to but must bypass all caches etc, but that feels like overkill for what I’m looking to achieve.  Maybe that’s appropriate once I bring Coveo into the benchmarking fun.

For this, I wanted to get a sense for the relative performance between Azure Search and Solr as it relates to Sitecore PaaS and I think I’ve done that.  Succinctly:

  1. Solr is considerably faster at search indexing (courtesy of the search provider implementation in Sitecore)
  2. both Azure Search and Solr perform about the same when it comes to querying a basic Sitecore site like LaunchSitecore (again, courtesy of the search provider implementation in Sitecore)

This isn’t the definitive take on the topic.  It’s more like the beginning.  Azure Search is native to Azure, so there are significant advantages there.  There is a lot of momentum around Azure and Sitecore in general, so that story will continue to evolve.

There are Solr as a service options out there that make Solr for Sitecore much easier (such as www.measuredsearch.com which I’ll blog about in the next few days), but Solr can be a lot for corporate IT departments to take on, so it isn’t a simple choice for everyone.

 

 

Auto-suggest with Solr Facets in Sitecore

Sitecore’s auto-suggest feature for search in the Content Authoring environment is pretty slick, but there is some confusing documentation from Sitecore about how to set it up properly with Solr.  As of today, Sitecore’s documentation on integrating with Solr indicates…

“When you implement Solr with Sitecore you need to enable term support in the Solr search handler.  The term functionality is built into Solr but is disabled by default. To power the dropdowns in the UI you must enable the terms component.

That above documentation will be updated at some point by Sitecore, since it’s no longer the case for the latest version of Sitecore — 8.2 rev. 161221 (Update-2).

In earlier versions of Sitecore, search in the Sitecore Content Editor could make use of the Solr “terms” component to populate suggestions.  This is why this guidance has previously been part of the Solr integration documentation from Sitecore.  Read more about Solr’s use of this auto-suggest through terms at https://cwiki.apache.org/confluence/display/solr/The+Terms+Component.

Sitecore’s strategy of making use of the “terms” component has changed with recently, however.  Sitecore now uses faceting with Solr instead of terms.

To prove this out, I’m going to turn to the Solr logs after I try some queries for content in the Sitecore client.  Refer to this documentation from Sitecore if you’re looking for more context on how to use the search facility — there are a lot of features that are very under-utilized, in my experience.  I’ll specify a clause by typing Updatedby: and then “siteco” to engage the auto-suggest feature:searbhby

Very nice, right?

Under the covers, the Solr logs will reveal something like this . . .

2017-02-17 19:33:07.546 INFO  (qtp33171127-11) [   x:trial_core] o.a.s.c.S.Request [trial_core]  webapp=/solr path=/select params={q=*:*&facet.field=parsedupdatedby_s&facet.prefix=siteco&rows=0&facet=true&version=2.2&facet.sort=true} hits=24626 status=0 QTime=2

. .  . and that can be further debugged by turning it into the URL request powering that auto-suggest response . . .

http://server:port/solr/sitecore_master_index/select?q=*:*&facet.field=parsedupdatedby_s&facet.prefix=siteco&rows=0&facet=true&version=2.2&facet.sort=true

. . . and that would return results like the following:

solrresponse

If instead we tried an author: search in Sitecore, for example, the facet.field would be parsedcreatedby_s instead of parsedupdatedby_s.

I don’t want to go too far down this rabbit hole.  I really just wanted to share that despite what the documentation shows, it’s not necessary to enable the Solr term component on the /select requestHandler in Solr if you’re using the most recent version of Sitecore.  I’ve confirmed with official Sitecore support that this change was tagged as change #444661 and that’s it was incorporated into the product since Sitecore 8.1 update-1 (rev. 151207); the release notes for 8.1 update-1 are vague, but here it is:

Autocomplete for known fields such as language did not work in the Content Editor Search tab using the SOLR provider. The problem was related to the SOLR server configuration. This has been fixed so that Sitecore no longer depends on this configuration. (444661)

Happy faceting to all!

 

High Availability of Azure Search with Sitecore

I’ve been investigating Azure Search with Sitecore’s new Azure App Service offering.  I’ve got a giant Excel file of benchmarks and charts based on several permutations and configurations, and several other interesting tidbits that I need to organize into posts to this blog . . . so look for much more about this general topic in the future.

For now, I thought I’d share a point I’ve confirmed with Sitecore support regarding a limitation of Azure Search with Sitecore’s CloudSearchProviderIndex.  The CloudSearchProviderIndex is what the standard Platform-As-A-Service product from Sitecore will use in place of Lucene or Solr or Coveo to power content search for Sitecore.  This is the key building block for working with Azure Search through Sitecore.  While I was performing performance benchmarks for search re-indexing with Sitecore, I noticed the Azure Search document count would drop to 0 and I’d see odd results from Sitecore requests that depended on the search index.  This was classic “search index is being worked on, don’t rely on querying it until the work is done” behaviour.  This was corrected several years ago through Sitecore’s addition of a SwitchOnRebuildLuceneIndex and equivalent for Solr . . . but there is no such equivalent for the CloudSearchProviderIndex used by Azure PaaS solutions.  Essentially: Sitecore is using a single copy of search indexes for query and re-indexing operations, limiting the availability of search during maintenance work.

One could argue this may not be such a big deal because one may not rebuild Azure Search indexes with any frequency.  I’m not sold on this argument, however, since the Sitecore projects I know will frequently perform re-indexing due to development changes to the schema, content synchronization demands, or just routine deployment standard practices.

Further complicating this issue is that my benchmarking for Azure Search re-indexing through Sitecore leaves a lot to be desired.  It can be slow.  This could make for an extended period of search index unavailability due to the CloudSearchProviderIndex‘s limitations.  I’ll share the full battery of testing I’ve done in a future post, but for now let me share the timings I’m observing regardless of the number of Azure Search partitions or replicas I’m working through (partitions should generally improve indexing performance; replicas should generally improve querying performance):

App Service Configuration Time for 20,000 Sitecore Items to Re-Index with Azure Search
Azure PaaS Standard (S1) CM IIS (OOTB from the Marketplace) 66 minutes
Azure S2 CM IIS 35 minutes
Azure S3 CM IIS 25 minutes
Azure P2 CM IIS 35 minutes
Azure P3 CM IIS 24 minutes

For reference, with Lucene indexes this operation would take 5 minutes or less.  The scaling options for Azure Search, Partition count and Replica count, have a minimal impact to the re-indexing operation.

I’ll go into details of this later, but it could be that . . .

  • 20,000 Sitecore items is too small a figure to benefit from scaling with Azure Search?  Many customers have 100,000 or more items, so perhaps I should evaluate a larger data set.
  • there are bottlenecks at the SQL tier?  App Insights here I come…
  • the fact Sitecore isn’t using Azure Search Indexers to ingest data and relies on the Sitecore crawling logic to handle data indexing is artificially slowing this process down

For the time being, Sitecore has responded that improving the availability of Azure Search indexes during rebuilds is an official “feature request” and assigned reference number 146822 

In the meantime, if a project needs high availability for Azure Search indexes one may need to roll up their sleeves and craft their own SwitchOnCloudSearchProviderIndex.  It appears fairly straight-forward based on reviewing how this is solved for Solr, just as one example.  A key caveat is in the Azure Search capacity planning documentation:

High availability for Azure Search pertains to queries and index updates that don’t involve rebuilding an index. If you add or delete a field, change a data type, or rename a field, you will need to rebuild the index. To rebuild the index, you must delete the index, re-create the index, and reload the data.

To maintain index availability during a rebuild, you must have a copy of the index with a different name on the same service, or a copy of the index with the same name on a different service, and then provide redirection or failover logic in your code.

It looks like providing for high availability would double the price of Azure Search indexes, so there are a cascade of complications related to this.

My investigations into Sitecore and Azure Search yielded this complication — it’s not insurmountable, and I actually find it fascinating how an on-premises product (classic Sitecore) will evolve into a cloud-first product.  This is just one piece of the evolutionary story.  I expect this will be addressed sooner rather than later in an official upgrade or patch from Sitecore, and until then it’s important to understand this nuance to the Sitecore PaaS landscape.

Digesting Sitecore Commerce 8.2.1

A whole new take on Sitecore Commerce is hot off the presses and I had an opportunity to dig into it briefly this week.  Taking from the release notes and the documentation, which is actually fairly extensive:

This is Sitecore’s new re-envisioned Commerce product.

“Release number 8.2.1 has been assigned to reflect the compatibility with release 8.2 of the Sitecore Experience Platform (Sitecore XP). However, Sitecore Commerce 8.2.1 is not an update to previous Commerce 8.2 releases, but is an entirely new Commerce product and release.”

I worked on a few Sitecore Commerce implementations a while back, but it had been over a year since I ran a proof-of-concept or even completed the installation.  My background with the permutations of “Commerce” on Windows goes back over 15 years, starting with the Microsoft Site Server product and the initial craze around XSLT rendering HTML output from content engines . . . I remember a horrendous e-commerce project designed with a Commerce Server beta and the “elegance” of XML was a complete productivity killer.  It’s a poor worker who blames their tools, right? 🙂   I digress…

Anyway, the last real work I did with Sitecore Commerce was in 2015 and I recall the installation/configuration process being arduous, with both Web and Desktop elements, lots of security hoops to jump through, COM everywhere, and even registry edits for good measure.

This new 8.2.1 Release installation process is certainly an improvement over what is now considered “Legacy” Sitecore Commerce . . . but standing up a baseline installation to kick the tires will still likely occupy a solid day of your time.  The documentation is good, but not 100% bulletproof because there are so many moving parts.  I know I ended up needing to install some new .Net elements for ASP.NET Core . . . and I needed to install an old .Net framework SDK to get another piece of the puzzle to run on the IIS server. I took notes on what extra steps I needed to perform, but I was using a fairly old Rackspace server image so not particularly applicable to everyone.  A few examples from my notes, however:

  1. Re-install the Default Web Site to IIS (our scripted Sitecore installation cleans out the Default Web Site in IIS, so I needed to add it back in to satisfy an assumption one of the various installers made)
  2. Configure IIS 6 Metabase Compatibility to satisfy a requirement for the Commerce Server installation

It’s these sorts of nuances that I recall from previous run-ins with the Commerce platform Sitecore inherited and now fully owns.  In some respects, not all that much has changed.

On the bright side, however, there are clean new SPEAK applications for working with Commerce data:

threecommerce

To get this far, however, you really have to earn it.  There are eight Sitecore “packages” that must be installed, for example, once you get the base Commerce Server + Sitecore + Commerce Core running . . . oh, and they need to be installed in a specific order that is NOT alphabetical, either:

packages

On the bright side, there is a lot more documentation than I’ve seen before on this set of products.  I worked with Sitecore Commerce at a time when there was essentially no real current information about the product, so maybe I’m satisfied too easily with what is now available . . . but I really found this an area Sitecore has improved upon.

Based on this documentation, I was able to pull out some of Sitecore’s diagrams of the product and compile this single visual of the Sitecore Commerce platform as I understand it for version 8.2.1:

8-2-1-annotation

The above is just consolidated from a variety of pictures and notes contained throughout the official documentation from Sitecore on the subject, but one of the ways I digest a system is by diagramming and scribbling notes as I go through a project.  Maybe others will find it useful, too.

Strategies for Sitecore Index Organization into Solr Cores

A few days ago, I shared a graphic I put together to illustrate how Solr can be used to organize Sitecore “indexes” into Solr “cores” — this post has the complete graphic.  I want to elaborate on how one sets Sitecore up to use these two approaches, and dig further into the details.

1:1 Sitecore Index to Solr Core Strategy

To start, here’s a visual showing the typical way Sitecore “indexes” are structured in Solr using a one-to-one (1:1) mapping:

solrseparate

This shows each of the default search indexes defined by Sitecore organized into their own cores defined in Solr.  It’s a 1:1 mapping.  This 1:1 strategy means each index has their own configuration (“conf”) directory in Solr, so seperate stopwords.txt, solrconfig.xml, schema.xml, and so on; it also means each index has their own (“data”) directory in Solr, so separate tlog folders, separate Segment files, etc.

This is the setup one achieves by following the community documentation on setting up Sitecore with Solr; specifically, this quote from that write-up is where you’re doing a lot of the grunt work around setting up distinct Solr cores for each Sitecore index:

“Use the process detailed in Steps 4-7 to create new cores for all the remaining indexes you would like to move to SOLR.”

Since this is the common strategy, I’m not going to go into more details as it’s straight-forward to Sitecore teams.

Kitchen Sink (∞:1 Sitecore Index to Solr Core) Strategy

Here is the comparable graphic showing the ∞:1 strategy of structuring Sitecore indexes in Solr; I like to think of this as the Kitchen Sink container for all Sitecore indexes, since everything goes into that single core just like the kitchen sink:

solrsame

With this approach, a single data and configuration definition is shared by all the Sitecore indexes that reside in Solr.  The advantages are reduced management (setting up the Solr replicationHandler, for example, requires updating 15 solrconfig.xml files in the 1:1 approach, but the Kitchen Sink would require only one solrconfig.xml file to update).  There are significant drawbacks to consider with the Kitchen Sink, however, as you’re sacrificing scaling options specific to each Sitecore index and enforcing a common schema.xml for every index stored in this single core.  There are plenty of reasons not to do this for a production installation of Sitecore, but for a crowded Sitecore environment used for acceptance testing or other use-cases where bullet-proof stability and lots of flexibility when it comes to performance tuning, sharding, etc is not necessary, you could make a good case for the Kitchen Sink strategy.

The only change necessary to a standard Sitecore configuration to support this Kitchen Sink approach is to patch the contentSearch definitions for the Sitecore indexes where the name of the Solr “core” is specified (stored by default in config files like Sitecore.ContentSearch.Solr.Index.Master.config,  Sitecore.ContentSearch.Solr.Index.Web.config, etc).   This is telling Sitecore which Solr core contains the index, but the actual name of the core doesn’t factor into the ContentSearch API code one uses with Sitecore.   A patch such as the following would handle both the sitecore_master_index and the sitecore_web_index to organize into a Solr Core named “kitchen_sink:”

<configuration xmlns:patch="http://www.sitecore.net/xmlconfig/">
  <sitecore>
    <contentSearch>
      <configuration>
        <indexes>
          <index id="sitecore_master_index" type="Sitecore.ContentSearch.SolrProvider.SolrSearchIndex, Sitecore.ContentSearch.SolrProvider">
            <param desc="core">kitchen_sink</param>
          </index>
          <index id="sitecore_web_index" type="Sitecore.ContentSearch.SolrProvider.SolrSearchIndex, Sitecore.ContentSearch.SolrProvider">
            <param desc="core">kitchen_sink</param>
          </index>
        </indexes>
        </configuration>
    </contentSearch>
  </sitecore>
</configuration>

If you peek into the Solr Admin for the kitchen_sink core that I’m using, specifically the Schema Browser in the Solr Admin UI, it becomes clear how Sitecore uses a field named “_indexname” to represent the Sitecore index value.  For this screenshot below, I’ve set the kitchen_sink core to contain two Sitecore indexes: sitecore_master_index and sitecore_web index:

solrterms

This shows us the two terms stored in that _indexname field, and that there are 18,774 for sitecore_master_index and 5,851 for sitecore_web_index.  Even though the indexes are contained in the same Solr Core, Sitecore ContentSearch API code like this . . .

Sitecore.ContentSearch.ISearchIndex index = 
  ContentSearchManager.GetIndex(indexName);
    using (Sitecore.ContentSearch.IProviderSearchContext ctx = 
      index.CreateSearchContext())

. . . doesn’t care whether all the Sitecore indexes reside in a single Solr “Core” or if they’re in their own following a 1:1 mapping strategy.

Caveats and Going In A Different Direction

There was a bug or two in earlier versions of Sitecore related to this, so be careful with early Sitecore 7.2 or Sitecore 8 implementations (and if you’re using Sitecore 7.5, you’ve got plenty of other things to worry about so don’t sweat a Solr Core organization strategy!).

I should also note that while this post is looking at combining Sitecore indexes into a single Solr Core for convenience and to reduce the management headaches of having 15 sets of Solr Cores to update etc, there are some implementations that go in the opposite direction.  Consider a strategy like the following:

solrmindblown

 

There may be circumstances where keeping Sitecore indexes in their own Solr Core — and even isolating them further into their own Solr implementation — could be in order.  Solr runs in a JVM and this could certainly factor in, but there are other shared run-time resources that Solr sets aside for the whole Solr application.

I’m not familiar enough with these sorts of implementations that I want to comment further or recommend any course of action related to this right now, but it’s good to think about and consider with Solr tuning scenarios.  I just wanted to share it, as it’s a logical dimension to consider given the two previous strategies in this post.

 

Solr Configuration for Integration with Sitecore

I’ve got a few good Solr and Sitecore blogs around 75% finished, but I’ve been too busy lately to focus on finishing them.  In the meantime, I figure a picture can be worth 1,000 words sometimes so let me post this visual representation of Solr strategies for Sitecore integrations.  One Solr core per index is certainly the best practice for production Sitecore implementations, but now that Solr support has significantly matured at Sitecore a one Solr core for all the Sitecore indexes is a viable, if limited, option:

draft

There used to be a bug (or two?) that made this single Solr core for every Sitecore index unstable, but that’s been corrected for some time now.

More to follow!