Refer to images by location using the 'images-dir' Asciidoc attribute.

spring-geode-docs/src/docs/asciidoc/guides/boot-actuator.adoc

@@ -2,7 +2,7 @@
 = Spring Boot Actuator for Apache Geode & Pivotal GemFire
 :apache-geode-version: {master-apache-geode-version}
 :apache-geode-docs: https://geode.apache.org/docs/guide/{apache-geode-version}
-:images-dir: ../images
+:images-dir: ./images
 :spring-boot-docs: https://docs.spring.io/spring-boot/docs/current/reference/html
 :spring-framework-docs: https://docs.spring.io/spring/docs/current/spring-framework-reference
 :toc: left

spring-geode-docs/src/docs/asciidoc/guides/caching-http-session.adoc

@@ -4,7 +4,7 @@
 :apache-geode-docs: https://geode.apache.org/docs/guide/{apache-geode-version}
 :apache-geode-javadoc: https://geode.apache.org/releases/latest/javadoc
 :apache-geode-website: https://geode.apache.org/
-:images-dir: ../images
+:images-dir: ./images
 :spring-boot-docs: https://docs.spring.io/spring-boot/docs/current/reference/html
 :spring-boot-javadoc: https://docs.spring.io/spring-boot/docs/current/api
 :spring-data-geode-docs: https://docs.spring.io/spring-data/geode/docs/current/reference/html
@@ -74,7 +74,7 @@ experience to which we alluded to above.  These applications instances will need
 
 An application architecture with HTTP Session State Caching appears as follows:
 
-image::../images/HTTP-Session-Caching.png[]
+image::{images-dir}/HTTP-Session-Caching.png[]
 
 Essentially, anytime an HTTP Session is requested by your Spring Boot, Web Application, the Servlet Container
 (e.g. Apache Tomcat) delegates to Spring Session to provide the implementation of `javax.servlet.http.HttpSession`.
@@ -89,7 +89,7 @@ that implement the Spring Session framework's `SessionRepository` interface.
 
 Spring Session's architecture can be depicted as follows:
 
-image::../images/Spring-Session-Framework-Architecture.png[]
+image::{images-dir}/Spring-Session-Framework-Architecture.png[]
 
 Again, the `SessionRepository` interface is the central component of the framework enabling any backend data store
 to be adapted and serve as a provider  for managing the HTTP Sessions.
@@ -198,11 +198,11 @@ Container using a derived `WebApplicationContext`.
 
 Let's run the example:
 
-image::../images/HttpSessionCachingApplication.png[]
+image::{images-dir}/HttpSessionCachingApplication.png[]
 
 When we navigate to the `/session` Web service endpoint:
 
-image::../images/HttpSessionCachingApplication-ServletContainerSession.png[]
+image::{images-dir}/HttpSessionCachingApplication-ServletContainerSession.png[]
 
 We see that the Servlet Container's implementing class for the `javax.servlet.http.HttpSession` interface is
 `org.apache.catalina.session.StandardSession`.
@@ -211,7 +211,7 @@ If we continue to hit refresh in the Web browser, thereby causing additional cli
 the HTTP server, then our HTTP Request count increments.  If we wait for 15 seconds, then the HTTP Session will expire,
 and we will see the HTTP Session count increment along with the HTTP Request count reset to 1:
 
-image::../images/HttpSessionCachingApplication-ServletContainerSessionExpiration.png[]
+image::{images-dir}/HttpSessionCachingApplication-ServletContainerSessionExpiration.png[]
 
 Now, we can repeat this same exercise, but this time, using Spring Session.
 
@@ -242,7 +242,7 @@ robust, highly available, highly resilient, clustered solution provided by Sprin
 
 When we run the example again, and access the `/session` Web service endpoint, we will see:
 
-image::../images/HttpSessionCachingApplication-SpringSession.png[]
+image::{images-dir}/HttpSessionCachingApplication-SpringSession.png[]
 
 Now we see that the implementing class for the `javax.servlet.http.HttpSession` is
 `org.springframework.session.web.http.SessionRepositoryFilter$SessionRepositoryRequestWrapper$HttpSessionWrapper`.

spring-geode-docs/src/docs/asciidoc/guides/caching-inline.adoc

@@ -3,7 +3,7 @@
 :apache-geode-version: {master-apache-geode-version}
 :apache-geode-docs: https://geode.apache.org/docs/guide/{apache-geode-version}
 :apache-geode-javadoc: https://geode.apache.org/releases/latest/javadoc
-:images-dir: ../images
+:images-dir: ./images
 :spring-boot-docs: https://docs.spring.io/spring-boot/docs/current/reference/html
 :spring-boot-javadoc: https://docs.spring.io/spring-boot/docs/current/api
 :spring-data-geode-docs: https://docs.spring.io/spring-data/geode/docs/current/reference/html
@@ -104,7 +104,7 @@ strictly adhere to and be diligent in your use of _Inline Caching_.
 
 _Inline Caching_ can be depicted in the following diagram:
 
-image::../images/Inline-Caching-Pattern.png[]
+image::{images-dir}/Inline-Caching-Pattern.png[]
 
 In the diagram above, there are 2 flows: 1 for _read-through_ (right-side) and another for _write-through_ (left-side).
 Both can occur in a single operation, on a read.
@@ -465,14 +465,14 @@ include::{samples-dir}/caching/inline/src/main/resources/data.sql[]
 
 If you call `http://localhost:8080/caculator/factorial/4`, you will see the following output:
 
-image::../images/factorial-of-four-before.png[]
+image::{images-dir}/factorial-of-four-before.png[]
 
 The output shows the result of `factorial(4)` is *24*, that the calculation took *3096 _milliseconds_* and the operation
 resulted in a *_cache miss_*.  However, now that we computed `factorial(4)`, the result was put into the "cache"
 as well as INSERTED into the backend (embedded, in-memory HSQLDB) database.  So, if we run the operation again,
 the `latency` drops to zero (and *_cacheMiss_* is *_false_*):
 
-image::../images/factorial-of-four-after.png[]
+image::{images-dir}/factorial-of-four-after.png[]
 
 That is because the result (i.e. *24*) of `factorial(4)` is "cached" in Apache Geode (as well as persisted to
 the database; _write-through_) and therefore, the `CaculatorService.factorial(:int)` method is *not* called.
@@ -482,7 +482,7 @@ To see the effects of the `factorial(:int)` method involving the database as par
 call `http://localhost:8080/caculator/factorial/5`.  *5* is stored in the database, but is not currently present
 in the cache:
 
-image::../images/factorial-of-five-before.png[]
+image::{images-dir}/factorial-of-five-before.png[]
 
 While the latency is much better than invoking the _factorial_ function, it is still not as fast as pulling the result
 from the cache.
@@ -492,7 +492,7 @@ the result was loaded from the database and put into the cache (_read-through_)
 we see that the latency drops from *12 ms* to *0 ms*.  However, in both cases, the *_cacheMiss_* was *_false_*
 because the value was found (in the database) without invoking the `CalculatorService.factorial(:int)` method:
 
-image::../images/factorial-of-five-after.png[]
+image::{images-dir}/factorial-of-five-after.png[]
 
 You can play around with the _square root_ operation to see the same effects of _Inline Caching_.
 

spring-geode-docs/src/docs/asciidoc/guides/caching-look-aside.adoc

@@ -3,7 +3,7 @@
 :apache-geode-version: {master-apache-geode-version}
 :apache-geode-docs: https://geode.apache.org/docs/guide/{apache-geode-version}
 :apache-geode-javadoc: https://geode.apache.org/releases/latest/javadoc
-:images-dir: ../images
+:images-dir: ./images
 :spring-boot-docs: https://docs.spring.io/spring-boot/docs/current/reference/html
 :spring-boot-javadoc: https://docs.spring.io/spring-boot/docs/current/api
 :spring-data-geode-docs: https://docs.spring.io/spring-data/geode/docs/current/reference/html
@@ -81,7 +81,7 @@ the `findBy(..)` method is called with the same `AccountNumber` (i.e. "abc123")
 
 The _Look-Aside Caching_ pattern can be depicted in the following diagram:
 
-image::../images/Look-Aside-Caching-Pattern.png[]
+image::{images-dir}/Look-Aside-Caching-Pattern.png[]
 
 In the diagram above, we see that the caching provider (e.g. Apache Geode) is consulted first, #2, after the client
 initiated the request, #1.  If the result of the cacheable operation for the given input has already been computed
@@ -442,7 +442,7 @@ from your IDE, or from the command-line, as is:
 
 Then open your Web browser and navigate to `http://localhost:8080/ping`:
 
-image::../images/LookAsideCachingApplication-Ping.png[]
+image::{images-dir}/LookAsideCachingApplication-Ping.png[]
 
 After that, we can create and increment counters, for example:
 

spring-geode-docs/src/docs/asciidoc/guides/caching-near.adoc

@@ -3,7 +3,7 @@
 :apache-geode-version: {master-apache-geode-version}
 :apache-geode-docs: https://geode.apache.org/docs/guide/{apache-geode-version}
 :apache-geode-javadoc: https://geode.apache.org/releases/latest/javadoc
-:images-dir: ../images
+:images-dir: ./images
 :spring-boot-docs: https://docs.spring.io/spring-boot/docs/current/reference/html
 :spring-boot-javadoc: https://docs.spring.io/spring-boot/docs/current/api
 :spring-data-geode-docs: https://docs.spring.io/spring-data/geode/docs/current/reference/html
@@ -65,7 +65,7 @@ To keep up with demand and not overload backend systems, like a database, you wo
 more CPU, more Disk, more Network bandwidth, basically, more of everything, which can be a very costly endeavor as you
 try to keep up with the every growing demand (which is a good problem to have, but...):
 
-image::../images/Small-Database-To-Big-Database.png[]
+image::{images-dir}/Small-Database-To-Big-Database.png[]
 
 Rather than scale-up, you could scale-out by using a sophisticated caching technology that uniformly partitions data
 across a cluster of data nodes thereby enabling data access operations to be intelligently routed and evenly distributed
@@ -74,7 +74,7 @@ cluster more resilient to failure.  Such a data management technology is ideal i
 as a single, logical unit of pooled resources (Memory, CPU, Disk, and Network) but uses a shared-nothing architecture.
 That is, no node in the cluster can be a single point of failure.
 
-image::../images/Cluster.png[]
+image::{images-dir}/Cluster.png[]
 
 From a Spring Boot application's point-of-view, it is the client in this application architecture, and multiple
 application instances can access and share the same data.  Indeed, in a Microservices architecture, another application
@@ -107,7 +107,7 @@ These 3 things in conjunction with each other should have a net effect of reduci
 Effectively, an applied "_Near Caching_" software design pattern looks like the following in our application/system
 architecture:
 
-image::../images/Near-Caching-Pattern.png[]
+image::{images-dir}/Near-Caching-Pattern.png[]
 
 It is now time to see the _Near Caching_ pattern in action.
 
@@ -470,14 +470,14 @@ from your Web browser.  Look for a line containing: `[info 2019/08/12 13:14:19.7
 Once both application instances are running, you can access the Webapp from your Web browser at the following URL:
 `http::/localhost:8181/`.
 
-image::../images/Near-Caching-Example-Webapp.png[]
+image::{images-dir}/Near-Caching-Example-Webapp.png[]
 
 TIP: To switch between the 2 client app instances, it is useful to have 2 Web browser tabs or windows open
 accessing each Web Server port (e.g. `8181` and `8282`).
 
 Next, let's create some data using client app instance one.
 
-image::../images/Near-Caching-Example-Webapp-Create-JonDoe.png[]
+image::{images-dir}/Near-Caching-Example-Webapp-Create-JonDoe.png[]
 
 This operation takes a bit of (simulated) time (`2167 milliseconds (ms)`, or `~2 seconds (s)`) since "_Jon Doe_"
 did not previously exist in the cache, which can be noted by the `cacheMiss` value of *true*.  "_JonDoe's_"
@@ -488,7 +488,7 @@ is being pulled from the "_local_" cache (i.e. "_Near Cache_) on the client.
 
 Now, in our second client app instance, if we access the same person, "_JonDoe_", then we see the following:
 
-image::../images/Near-Caching-Example-Webapp-Read-JonDoe.png[]
+image::{images-dir}/Near-Caching-Example-Webapp-Read-JonDoe.png[]
 
 Notice that `cacheMiss` is *false* and the `latency` is only `1 ms`.  That is because the 2nd client app instance
 was already pushed the data from the server based on the client's interest registration.  This is also apparent
@@ -503,7 +503,7 @@ in the log output for the client application instances:
 To see the effects of updating a cache entry from a client app instance, let's update "_JonDoe_" from the 2nd client app
 instance by changing his email address and phone number:
 
-image::../images/Near-Caching-Example-Webapp-Update-JonDoe.png[]
+image::{images-dir}/Near-Caching-Example-Webapp-Update-JonDoe.png[]
 
 Before we refresh the Web browser tab or window pointing to our 1st client app instance, if you look at the log output
 for the 1st client app instance, you will see:
@@ -517,7 +517,7 @@ for the 1st client app instance, you will see:
 Then, switch back to the 1st client app instance Web browser tab or window and hit the refresh button, or navigate
 to the URL, `http://localhost:8181/yellow-pages/JonDoe`, and you should see the updated contact information:
 
-image::../images/Near-Caching-Example-Webapp-Reload-JonDoe.png[]
+image::{images-dir}/Near-Caching-Example-Webapp-Reload-JonDoe.png[]
 
 You can repeat this exercise as often as you like.
 

spring-geode-docs/src/docs/asciidoc/guides/getting-started.adoc

@@ -5,6 +5,7 @@ John Blum
 :apache-geode-docs: https://geode.apache.org/docs/guide/{apache-geode-version}
 :apache-geode-javadoc: https://geode.apache.org/releases/latest/javadoc
 :apache-geode-website: https://geode.apache.org/
+:images-dir: ./images
 :pivotal-cloudcache-version: {master-pivotal-cloudcache-version}
 :pivotal-cloudcache-docs: https://docs.pivotal.io/p-cloud-cache/{pivotal-cloudcache-version}
 :pivotal-cloudcache-website: https://pivotal.io/pivotal-cloud-cache
@@ -92,14 +93,14 @@ see that `2.2.0.RC1` was selected when the project was generated.  For more on v
 
 Your selections should look similar to:
 
-image::../images/spring-initializer-screenshot.png[]
+image::{images-dir}/spring-initializer-screenshot.png[]
 
 Be sure to click the "*+*" button next to the "_Spring for Apache Geode_" dependency to select and add it to
 the generated project Maven POM file.
 
 You can explore the contents of the generated project by pressing the `CTRL+SPACE` keys:
 
-image::../images/spring-initializer-explore-project-screenshot.png[]
+image::{images-dir}/spring-initializer-explore-project-screenshot.png[]
 
 Click the "_Generate the project_" button.  This generates a *Java 8* project with *JAR* packaging.
 
@@ -977,7 +978,7 @@ Caused by: o.a.g.cache.client.NoAvailableServersException: null
 The application will continue to run if you included the Spring Web dependencies in your application classpath,
 in which case, you can then inspect the application using a Web client (e.g. Web browser):
 
-image::../images/customer-service-application-jondoe.png[]
+image::{images-dir}/customer-service-application-jondoe.png[]
 
 [[spring-geode-samples-getting-started-run-app-clientserver]]
 == Run the Application in a Client/Server Topology
@@ -1797,21 +1798,21 @@ We see the "_crm-app_" in the table of apps, which is currently stopped.
 We can either start and stop the app, restage the app, bind services, and so on, all from the command-line using `cf`,
 or we can perform these actions from within _Pivotal AppsManager_, which is what we will do:
 
-image::../images/pvtl-appsmanager-org-space-apps.png[]
+image::{images-dir}/pvtl-appsmanager-org-space-apps.png[]
 
 Again, we see the "_crm-app_".  You can click on the app name and drill in to get more details:
 
-image::../images/pvtl-appsmanager-org-space-apps-crm-app-overview.png[]
+image::{images-dir}/pvtl-appsmanager-org-space-apps-crm-app-overview.png[]
 
 If you click on "_Service (1)_" in the left navigation bar, you will see that the "_crm-app_" is bound to
 the "_pccServiceOne_" Pivotal Cloud Cache service instance:
 
-image::../images/pvtl-appsmanager-org-space-apps-crm-app-service.png[]
+image::{images-dir}/pvtl-appsmanager-org-space-apps-crm-app-service.png[]
 
 If you click on "_Settings_" in the left navigation bar and "REVEAL ENV VARS" you will find the "_Gfsh login string_"
 that you can use to connect to the Pivotal Cloud Cache cluster using _Gfsh_ from your local development environment:
 
-image::../images/pvtl-appsmanager-org-space-apps-crm-app-settings.png[]
+image::{images-dir}/pvtl-appsmanager-org-space-apps-crm-app-settings.png[]
 
 Let's do that now.  Copy the "_Gfsh login string_" and enter it in _Gfsh_:
 
@@ -1863,12 +1864,12 @@ Now, we can start the CRM, Spring Boot application using _Pivotal AppsManager_ f
 
 The "_crm-app_" will be staged and then started:
 
-image::../images/pvtl-appsmanager-org-space-apps-crm-app-start.png[]
+image::{images-dir}/pvtl-appsmanager-org-space-apps-crm-app-start.png[]
 
 Click the "_play_" button in the upper right corner above the log output frame to tail the log file of the CRM,
 Spring Boot application.  Eventually, you should see the application log the interaction with "_JonDoe_".
 
-image::../images/pvtl-appsmanager-org-space-apps-crm-app-logs-output.png[]
+image::{images-dir}/pvtl-appsmanager-org-space-apps-crm-app-logs-output.png[]
 
 As you can see in the image above, the application successfully logged the interactions with "_JonDoe_".  This only
 appears in red "[ERR]" since the interactions with logged with `System.err.printf` statements.
@@ -1876,11 +1877,11 @@ appears in red "[ERR]" since the interactions with logged with `System.err.print
 If you now click on "VIEW APP" link in the upper right-hand corner, it will open a new tab to the CRM Web app's
 home page:
 
-image::../images/getting-started-crm-app-homepage.png[]
+image::{images-dir}/getting-started-crm-app-homepage.png[]
 
 Then, you get all customers in JSON by using HTTP `GET http://host:port/customers` REST API Web service endpoint:
 
-image::../images/getting-started-crm-app-getallcustomers.png[]
+image::{images-dir}/getting-started-crm-app-getallcustomers.png[]
 
 Now, back in _Gfsh_, you can see that the 1) "_/Customers_" Region was added to the cluster of PCC servers
 and that 2) "_JonDoe_" was persisted to the cluster and you are able to query for "_JonDoe_".