diff --git a/docs/content/Tutorial:-All-About-Queries.md b/docs/content/Tutorial:-All-About-Queries.md
index 2e275bf5131..49f7f413f4c 100644
--- a/docs/content/Tutorial:-All-About-Queries.md
+++ b/docs/content/Tutorial:-All-About-Queries.md
@@ -14,6 +14,8 @@ Before we start digging into how to query Druid, make sure you've gone through t
 
 Let's start up a simple Druid cluster so we can query all the things.
 
+Note: If Zookeeper and MySQL aren't running, you'll have to start them again as described in [The Druid Cluster](Tutorial%3A-The-Druid-Cluster.html).
+
 To start a Coordinator node:
 
 ```bash
diff --git a/docs/content/Tutorial:-Loading-Your-Data-Part-1.md b/docs/content/Tutorial:-Loading-Your-Data-Part-1.md
index 5a9d57b7ecb..122ce70ccc4 100644
--- a/docs/content/Tutorial:-Loading-Your-Data-Part-1.md
+++ b/docs/content/Tutorial:-Loading-Your-Data-Part-1.md
@@ -66,6 +66,8 @@ There are five data points spread across the day of 2013-08-31. Talk about big d
 
 In order to ingest and query this data, we are going to need to run a historical node, a coordinator node, and an indexing service to run the batch ingestion.
 
+Note: If Zookeeper and MySQL aren't running, you'll have to start them again as described in [The Druid Cluster](Tutorial%3A-The-Druid-Cluster.html).
+
 #### Starting a Local Indexing Service
 
 The simplest indexing service we can start up is to run an [overlord](Indexing-Service.html) node in local mode. You can do so by issuing:
diff --git a/docs/content/Tutorial:-Loading-Your-Data-Part-2.md b/docs/content/Tutorial:-Loading-Your-Data-Part-2.md
index 94c3d91970a..4fa9d98dcd2 100644
--- a/docs/content/Tutorial:-Loading-Your-Data-Part-2.md
+++ b/docs/content/Tutorial:-Loading-Your-Data-Part-2.md
@@ -45,9 +45,9 @@ With real-world data, we recommend having a message bus such as [Apache Kafka](h
 <a id="set-up-kafka"></a>
 #### Setting up Kafka
 
-[KafkaFirehoseFactory](https://github.com/metamx/druid/blob/druid-0.6.61/realtime/src/main/java/com/metamx/druid/realtime/firehose/KafkaFirehoseFactory.java) is how druid communicates with Kafka. Using this [Firehose](Firehose.html) with the right configuration, we can import data into Druid in real-time without writing any code. To load data to a real-time node via Kafka, we'll first need to initialize Zookeeper and Kafka, and then configure and initialize a [Realtime](Realtime.html) node.
+[KafkaFirehoseFactory](Firehose.html) is how druid communicates with Kafka. Using this [Firehose](Firehose.html) with the right configuration, we can import data into Druid in real-time without writing any code. To load data to a real-time node via Kafka, we'll first need to initialize Zookeeper and Kafka, and then configure and initialize a [Realtime](Realtime.html) node.
 
-Instructions for booting a Zookeeper and then Kafka cluster are available [here](http://kafka.apache.org/07/quickstart.html).
+The following quick-start instructions for booting a Zookeeper and then Kafka cluster were taken from the [Kafka website](http://kafka.apache.org/07/quickstart.html).
 
 1. Download Apache Kafka 0.7.2 from [http://kafka.apache.org/downloads.html](http://kafka.apache.org/downloads.html)
 
@@ -207,9 +207,9 @@ Batch Ingestion
 ---------------
 Druid is designed for large data volumes, and most real-world data sets require batch indexing be done through a Hadoop job.
 
-The setup for a single node, 'standalone' Hadoop cluster is available [here](http://hadoop.apache.org/docs/stable/single_node_setup.html).
+The setup for a single node, 'standalone' Hadoop cluster is available [here](http://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-common/SingleCluster.html).
 
-For the purposes of this tutorial, we are going to use our very small and simple Wikipedia data set. This data can directly be ingested via other means as shown in the previous [tutorial](Tutorial%3A-Loading-Your-Data-Part-1), but we are going to use Hadoop here for demonstration purposes.
+For the purposes of this tutorial, we are going to use our very small and simple Wikipedia data set. This data can directly be ingested via other means as shown in the previous [tutorial](Tutorial%3A-Loading-Your-Data-Part-1.html), but we are going to use Hadoop here for demonstration purposes.
 
 Our data is located at:
 
@@ -227,10 +227,12 @@ The following events should exist in the file:
 {"timestamp": "2013-08-31T12:41:27Z", "page": "Coyote Tango", "language" : "ja", "user" : "stringer", "unpatrolled" : "true", "newPage" : "false", "robot": "true", "anonymous": "false", "namespace":"wikipedia", "continent":"Asia", "country":"Japan", "region":"Kanto", "city":"Tokyo", "added": 1, "deleted": 10, "delta": -9}
 ```
 
-#### Setup a Druid Cluster
+#### Set Up a Druid Cluster
 
 To index the data, we are going to need an indexing service, a historical node, and a coordinator node.
 
+Note: If Zookeeper and MySQL aren't running, you'll have to start them again as described in [The Druid Cluster](Tutorial%3A-The-Druid-Cluster.html).
+
 To start the Indexing Service:
 
 ```bash