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  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 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.



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.

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:


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:


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="">
          <index id="sitecore_master_index" type="Sitecore.ContentSearch.SolrProvider.SolrSearchIndex, Sitecore.ContentSearch.SolrProvider">
            <param desc="core">kitchen_sink</param>
          <index id="sitecore_web_index" type="Sitecore.ContentSearch.SolrProvider.SolrSearchIndex, Sitecore.ContentSearch.SolrProvider">
            <param desc="core">kitchen_sink</param>

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:


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 = 
    using (Sitecore.ContentSearch.IProviderSearchContext ctx = 

. . . 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:



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:


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!

Sitecore Gets Serious About Search, by Leaving the Game

Sitecore is steadily reducing the use-cases for using Lucene as the search provider for the Sitecore product.  Sitecore published this document on “Solr or Lucene” a few days ago, going so far as to state this one criteria where you must use Solr:

  • You have two or more content delivery servers

Read that bullet point again.  If you’ve worked with Sitecore for a while, this should trigger an alarm.

Sound the alarm: most implementations have 2 or more CD servers!  I’d say 80% or more of Sitecore implementations are using more than a single CD server, in fact.  Carrying this logic forward, 80% of Sitecore implementations should not be running on Lucene!  This is a big departure for Sitecore as a company, who would historically dodge conversations about what is the right technology for a given situation.  I think the Sitecore philosophy was that advocating for one technical approach over another is risky and means a Sitecore endorsement could make them accountable if a technology approach fails for one reason or another.  For as long as I’ve known Sitecore, it’s a software company intent on selling licenses, not dictating how to use the product.  Risk aversion has kept them from getting really down in the weeds with customers.  This tide has been turning, however, with things like Helix and now this more aggressive messaging about the limitations of Lucene.  I think it’s great for Sitecore to be more vocal about best practices, it’s just taken years for them to come around to the idea.

As a bit of a search geek, I want to state for the record that this new Solr over Lucene guidance from Sitecore is not really an indictment of Lucene.  The Apache Lucene project, and it’s cousin the .Net port that Sitecore makes use of out-of-the-box, was ground breaking in many ways.  As a technology, Lucene can handle enormous volumes of documents and performs really well.  Solr is making use of Lucene underneath it all, anyway!  This recent announcement from Sitecore is more acknowledgement that Sitecore’s event plumbing is no substitute for Solr’s CAP-theorem straddling acrobatics.  Sitecore is done trying to roll their own distributed search system.  I think this is Sitecore announcing that they’re tired of patching the EventQueue, troubleshooting search index update strategies for enterprise installations, and giving up on ensuring clients don’t hijack the Sitecore heartbeat thread and block search indexing with some custom boondoggle in the publishing pipeline.  They’re saying: we give up — just use Solr.

Amen.  I’m fine with that.

To be honest, I think this change of heart can also be explained by the predominant role Azure Search plays in the newest Sitecore PaaS offering.  Having an IP address for all the “search stuff” is awful nice whether you’re running in Azure or anywhere else.  It’s clear Sitecore decided they weren’t keen to recreate the search wheel a few years ago, and are steadily converging around these technologies with either huge corporate backing (Azure Search) or a vibrant open source community (Solr).

I should also note, here, that Coveo for Sitecore probably welcomes this opportunity for Sitecore teams to break away from the shackles of the local Lucene index.  I’m not convinced that long-term Coveo can out-run the likes of Azure Search or Solr, but I know today if your focus is quickly ramping up a search heavy site on Sitecore you should certainly weight the pros/cons of Coveo.

With all this said, I want to take my next few posts and dig really deep into Solr for Sitecore and talk about performance monitoring, tuning, and lots of areas that get overlooked when it comes to search with Sitecore and Solr.   So I’ll have more to say on this topic in the next few days!


How to use Redis in place of Sitecore in-memory caches

In this previous post I discussed the case for separating functions typically combined into a single out-of-the-box Sitecore instance into distinct parts, supporting better scalability, performance, availability, etc.  I concluded that piece with a reference to using Redis cache for Sitecore caches, instead of the default IIS in-memory cache.  Prior to Sitecore 8.2, this wasn’t entirely possible (although one could alter some Sitecore caching aspects through extensive customization of certain Sitecore assemblies).  Implementations looking to free up IIS resources, to get more out of their limited Sitecore IIS licenses, might consider swapping the in-memory caches for Redis.

Major caveat: This specific blog post doesn’t analyze the performance implications of doing this; my focus here is to cover how to accomplish the swap of the in-memory cache instead of examining all the nuances of why or why not to do it.  That being said, I do expect the use of Redis for Sitecore caches to be a surgical decision made based on the particulars of each project.  It’s not a one-size-fits-all solution.  There are also questions of which caches to put into Redis, and where Redis should be running (considerations of connectivity, Redis perf, and the whole landscape of Redis can also be brought into this conversation).  This will make for future material I cover, probably in conjunction with the big time Redis pros at ObjectRocket (who, conveniently, are part of my family at Rackspace).  I hope and expect others in the greater Sitecore community will expand on this topic, too!

Customizing Cache Configuration with Sitecore 8.2 +

Sitecore 8.2 includes a new .config file at App_Config\Include\CacheContainers.config — as the name suggests, this is where one can identify cache containers that will replace the default ones Sitecore uses.  For my example, I’m going to specify a custom container for the website[html] cache; any cache can be included here (I refer you to the old reliable /sitecore/admin/cache.aspx page — the name column enumerates all the Sitecore caches):


With my customization, my CacheContainers.config file looks like this:

<configuration xmlns:patch="">
   <cacheContainer name="website[html]" type="Rackspace.Sc.Caching.ReferenceRedisCache, Rackspace.Sc.Caching">
    <param desc="name">$(0)</param>
    <param desc="maxSize">$(1)</param>
    <cacheSizeCalculationStrategy type="Sitecore.Caching.DefaultCacheSizeCalculationStrategy, Sitecore.Kernel" />

I’m not going to regurgitate the comments from the default CacheContainers.config file, but it’s certainly worth reviewing.

Once the CacheContainers.config is pointing to the custom class and assembly (in my case type=”Rackspace.Sc.Caching.ReferenceRedisCache, Rackspace.Sc.Caching”) it’s necessary to create the custom assembly to provide the Redis cache behaviour.  The foundation for this is to implement the new Sitecore.Caching.ICache interface (which requires Sitecore.Caching.ICacheInfo and Sitecore.Caching.Generics.ICache<string> interfaces. It can look like a lot of work, but it actually isn’t so bad.

One way I found to make it easier was to reference the out-of-the-box Sitecore Sitecore.Caching.MemoryCacheAdapter in the Sitecore.Kernel assembly.  One can consider the MemoryCacheAdapter for an example of the implementation of these interfaces:


Reflector, or whatever your preferred decompilation tool of choice, for the win!

In my case, I create a ReferenceRedisCache for this. . .

public class ReferenceRedisCache : Sitecore.Caching.ICache

. . . and the nuts and bolts come down to swapping Redis in place of the System.Runtime.Caching.MemoryCache object from the MemoryCacheAdapter implementation.  There are other considerations, of course, but this is the big picture.

I’m not going to post all the code here as mine is still a bit of a work in progress, and I need to evaluate it in terms of performance etc.  You’re much safer using the decompiled Sitecore source as a guide, at this point.  With this post, I did want to share how one can approach this powerful Sitecore customization; you can selectively change from Sitecore’s in-memory caching to just about any option you’d like this way.

There is another avenue that I’ve not explored with this.  Sitecore provides a Sitecore.Caching.BaseCacheConfiguration class that can be overridden to introduce customizations.  Sitecore.Caching.DefaultCacheConfiguration is the standard approach you could use as an example; this is an alternative way of substituting your own caching logic, but I haven’t dug into it yet.

I’ll clean up my code, do some profiling and evaluations, and come back with the full details of my custom Rackspace.Sc.Caching.ReferenceRedisCache implementation soon.

The Sitecore Pie: strategic slicing for better implementations

The Sitecore Pie

At some point I want to catalog the full set of features a Sitecore Content Delivery and Content Management server can manage in a project.  My goal would be to identify all the elements that can be split apart into independent services.  This post is not a comprehensive list of those features, but serves to introduce the concept.

Think of Sitecore as a big blueberry pie that can be sliced into constituent parts.  Some Sitecore sites can really benefit from slicing the pie into small pieces and letting dedicated servers or services manage that specific aspect of the pie.  Too often, companies don’t strategize around how much different work their Sitecore solution is doing.

An example will help communicate my point: consider IIS and how it serves as the execution context for Sitecore.   Many implementations will run logic for the following through the same IIS server that is handling the Sitecore request for rendering a web page.  These are all slices of the Sitecore pie for a Sitecore Content Delivery server:

  1. URL redirection through Sitecore
  2. Securing HTTP traffic with SSL
  3. Image resizing for requests using low-bandwidth or alternative devices
  4. Serving static assets like CSS, JS, graphics, etc
  5. Search indexing and query processing (if one is using Lucene)

If you wanted to cast a broader net, you could include HTTP Session state for when InProc mode is chosen, Geo-IP look-ups for certain CD servers, and others to this list of pie slices.  Remember, I didn’t claim this was an exhaustive list.  The point is: IIS is enlisted in all this other work besides processing content into HTML output for Sitecore website visitors.

Given our specific pie slices above, one could employ the following alternatives to relieve IIS of the processing:

  1. URL Redirection at the load balancer level can be more performant than having Sitecore process redirects
  2. Apply SSL between the load balancer and the public internet, but not between the IIS nodes behind your load balancer — caled “SSL Offloading” or “SSL Termination”
  3. There are services like Akamai that fold in dynamic image processing as part of their suite of products
  4. Serving static assets from a CDN is common practice for Sitecore
  5. Coveo for Sitecore is an alternative search provider that can take a lot of customer-facing search aspects and shift it to dedicated search servers or even Coveo’s Cloud.  One can go even further with Solr for Sitecore or still other search tiers if you’re really adventurous

My point is, just like how we hear a lot this election season about “let Candidate X be Candidate X” — we can let Sitecore be Sitecore and allow it to focus on rendering content created and edited by content authors and presenting it as HTML responses.  That’s what Sitecore is extremely valuable for.

Enter the Cache

I’ve engaged with a lot of Sitecore implementations who were examining their Sitecore pie and determining what slices belong where . . . and frequently we’d make the observation that the caching layer of Sitecore was tightly coupled with the rest of the Sitecore system and caching wasn’t a good candidate for slicing off.  There wasn’t a slick provider model for Sitecore caches, and while certain caches could be partially moved to other servers, it wasn’t clean, complete, or convenient.

That all changed officially with the initial release of Sitecore 8.2 last month.  Now there is a Sitecore.Caching.DefaultCacheManager class, a Sitecore.Caching.ICache interface, and other key extension points as part of the standard Sitecore API.  One can genuinely add the Sitecore cache to the list of pie slices one can consider for off-loading.

In my next post, I will explore using this new API to use Redis as the cache provider for Sitecore instead of the standard in-memory IIS cache.