Index: 08/ops.html
===================================================================
--- 08/ops.html	(revision 1695175)
+++ 08/ops.html	(working copy)
@@ -326,7 +326,7 @@
 Application segregation: Unless you really understand the application patterns of other apps that you want to install on the same box, it can be a good idea to run Zookeeper in isolation (though this can be a balancing act with the capabilities of the hardware).
 Use care with virtualization: It can work, depending on your cluster layout and read/write patterns and SLAs, but the tiny overheads introduced by the virtualization layer can add up and throw off Zookeeper, as it can be very time sensitive
 <p>
-Zookeeper configuration and monitoring: It's java, make sure you give it 'enough' heap space (We usually run them with 3-5G, but that's mostly due to the data set size we have here). Unfortunately we don't have a good formula for it. As far as monitoring, both JMZ and the 4 letter commands are very useful, they do overlap in some cases (and in those cases we prefer the 4 letter commands, they seem more predictable, or at the very least, they work better with the LI monitoring infrastructure)
+Zookeeper configuration and monitoring: It's java, make sure you give it 'enough' heap space (We usually run them with 3-5G, but that's mostly due to the data set size we have here). Unfortunately we don't have a good formula for it. As far as monitoring, both JMX and the 4 letter words (4lw) commands are very useful, they do overlap in some cases (and in those cases we prefer the 4 letter commands, they seem more predictable, or at the very least, they work better with the LI monitoring infrastructure)
 Don't overbuild the cluster: large clusters, especially in a write heavy usage pattern, means a lot of intracluster communication (quorums on the writes and subsequent cluster member updates), but don't underbuild it (and risk swamping the cluster).
 <p>
 Try to run on a 3-5 node cluster: Zookeeper writes use quorums and inherently that means having an odd number of machines in a cluster. Remember that a 5 node cluster will cause writes to slow down compared to a 3 node cluster, but will allow more fault tolerance.
Index: 081/ops.html
===================================================================
--- 081/ops.html	(revision 1695175)
+++ 081/ops.html	(working copy)
@@ -595,7 +595,7 @@
   <li>I/O segregation: if you do a lot of write type traffic you'll almost definitely want the transaction logs on a different disk group than application logs and snapshots (the write to the ZooKeeper service has a synchronous write to disk, which can be slow).</li>
   <li>Application segregation: Unless you really understand the application patterns of other apps that you want to install on the same box, it can be a good idea to run ZooKeeper in isolation (though this can be a balancing act with the capabilities of the hardware).</li>
   <li>Use care with virtualization: It can work, depending on your cluster layout and read/write patterns and SLAs, but the tiny overheads introduced by the virtualization layer can add up and throw off ZooKeeper, as it can be very time sensitive</li>
-  <li>ZooKeeper configuration and monitoring: It's java, make sure you give it 'enough' heap space (We usually run them with 3-5G, but that's mostly due to the data set size we have here). Unfortunately we don't have a good formula for it. As far as monitoring, both JMZ and the 4 letter commands are very useful, they do overlap in some cases (and in those cases we prefer the 4 letter commands, they seem more predictable, or at the very least, they work better with the LI monitoring infrastructure)</li>
+  <li>ZooKeeper configuration and monitoring: It's java, make sure you give it 'enough' heap space (We usually run them with 3-5G, but that's mostly due to the data set size we have here). Unfortunately we don't have a good formula for it. As far as monitoring, both JMX and the 4 letter words (4lw) are very useful, they do overlap in some cases (and in those cases we prefer the 4 letter commands, they seem more predictable, or at the very least, they work better with the LI monitoring infrastructure)</li>
   <li>Don't overbuild the cluster: large clusters, especially in a write heavy usage pattern, means a lot of intracluster communication (quorums on the writes and subsequent cluster member updates), but don't underbuild it (and risk swamping the cluster).</li>
   <li>Try to run on a 3-5 node cluster: ZooKeeper writes use quorums and inherently that means having an odd number of machines in a cluster. Remember that a 5 node cluster will cause writes to slow down compared to a 3 node cluster, but will allow more fault tolerance.</li>
 </ul>
Index: 082/ops.html
===================================================================
--- 082/ops.html	(revision 1695175)
+++ 082/ops.html	(working copy)
@@ -853,7 +853,7 @@
   <li>I/O segregation: if you do a lot of write type traffic you'll almost definitely want the transaction logs on a different disk group than application logs and snapshots (the write to the ZooKeeper service has a synchronous write to disk, which can be slow).</li>
   <li>Application segregation: Unless you really understand the application patterns of other apps that you want to install on the same box, it can be a good idea to run ZooKeeper in isolation (though this can be a balancing act with the capabilities of the hardware).</li>
   <li>Use care with virtualization: It can work, depending on your cluster layout and read/write patterns and SLAs, but the tiny overheads introduced by the virtualization layer can add up and throw off ZooKeeper, as it can be very time sensitive</li>
-  <li>ZooKeeper configuration and monitoring: It's java, make sure you give it 'enough' heap space (We usually run them with 3-5G, but that's mostly due to the data set size we have here). Unfortunately we don't have a good formula for it. As far as monitoring, both JMZ and the 4 letter commands are very useful, they do overlap in some cases (and in those cases we prefer the 4 letter commands, they seem more predictable, or at the very least, they work better with the LI monitoring infrastructure)</li>
+  <li>ZooKeeper configuration and monitoring: It's java, make sure you give it 'enough' heap space (We usually run them with 3-5G, but that's mostly due to the data set size we have here). Unfortunately we don't have a good formula for it. As far as monitoring, both JMX and the 4 letter words (4lw) commands are very useful, they do overlap in some cases (and in those cases we prefer the 4 letter commands, they seem more predictable, or at the very least, they work better with the LI monitoring infrastructure)</li>
   <li>Don't overbuild the cluster: large clusters, especially in a write heavy usage pattern, means a lot of intracluster communication (quorums on the writes and subsequent cluster member updates), but don't underbuild it (and risk swamping the cluster).</li>
   <li>Try to run on a 3-5 node cluster: ZooKeeper writes use quorums and inherently that means having an odd number of machines in a cluster. Remember that a 5 node cluster will cause writes to slow down compared to a 3 node cluster, but will allow more fault tolerance.</li>
 </ul>
Index: 083/ops.html
===================================================================
--- 083/ops.html	(revision 1695175)
+++ 083/ops.html	(working copy)
@@ -852,7 +852,7 @@
   <li>I/O segregation: if you do a lot of write type traffic you'll almost definitely want the transaction logs on a different disk group than application logs and snapshots (the write to the ZooKeeper service has a synchronous write to disk, which can be slow).</li>
   <li>Application segregation: Unless you really understand the application patterns of other apps that you want to install on the same box, it can be a good idea to run ZooKeeper in isolation (though this can be a balancing act with the capabilities of the hardware).</li>
   <li>Use care with virtualization: It can work, depending on your cluster layout and read/write patterns and SLAs, but the tiny overheads introduced by the virtualization layer can add up and throw off ZooKeeper, as it can be very time sensitive</li>
-  <li>ZooKeeper configuration and monitoring: It's java, make sure you give it 'enough' heap space (We usually run them with 3-5G, but that's mostly due to the data set size we have here). Unfortunately we don't have a good formula for it. As far as monitoring, both JMZ and the 4 letter commands are very useful, they do overlap in some cases (and in those cases we prefer the 4 letter commands, they seem more predictable, or at the very least, they work better with the LI monitoring infrastructure)</li>
+  <li>ZooKeeper configuration and monitoring: It's java, make sure you give it 'enough' heap space (We usually run them with 3-5G, but that's mostly due to the data set size we have here). Unfortunately we don't have a good formula for it. As far as monitoring, both JMX and the 4 letter words (4lw) commands are very useful, they do overlap in some cases (and in those cases we prefer the 4 letter commands, they seem more predictable, or at the very least, they work better with the LI monitoring infrastructure)</li>
   <li>Don't overbuild the cluster: large clusters, especially in a write heavy usage pattern, means a lot of intracluster communication (quorums on the writes and subsequent cluster member updates), but don't underbuild it (and risk swamping the cluster).</li>
   <li>Try to run on a 3-5 node cluster: ZooKeeper writes use quorums and inherently that means having an odd number of machines in a cluster. Remember that a 5 node cluster will cause writes to slow down compared to a 3 node cluster, but will allow more fault tolerance.</li>
 </ul>