Monitoring In a previous Monitoring Performance on MongoDB – Mongo Basics article we went over some basics about Mongo and monitoring Mongo performance.  In this article we are going to examine some interesting services, that can help with our Mongo monitoring.

Basically, we have two sets of statistics we would like to collect from our Mongo instances.  First, the basic computer stats that you need to collect for any machine in your fleet, and second we want to collect all these great DB stats from the Mongo HTTP Console.

We want to collect all these statistics, but we also need somewhere to store and view them.  That’s where Monitis comes into play!

Cassandra is a robust and highly scalable NoSQL datastore that usually consists of multiple nodes spread out across multiple datacenters.  If you are the system administrator for a large Cassandra deployment then you might be curious as to how your cluster is doing.  In fact your job probably depends on it!  So how can you combine a great service like Monitis with Cassandra to make sure you cluster is buzzing along smoothly?

Hadoop, which was named after a toy elephant, is a serious framework for doing distributed data processing across thousands of nodes and petabytes of data.  It’s loosely based on some big time Google projects, MapReduce, Big Table, and Google File System.  A key thing to understand about Hadoop is that it’s not just one monolithic project. Hadoop has a number of different pieces that all work together to help you crunch some very big data.

Hadoop is all about processing data, and Hadoop’s MapReduce engine is what makes all this processing possible. MapReduce is a process that Google came up with for churning through petabytes of data on commodity hardware. Here’s how it works.

Cassandra is a complex, highly scalable NoSQL database system that was initially developed by Facebook and is now under the purview of the Apache Foundation.  Apache Casandra has risen as a welcome alternative to HBase, another highly scalable, and available key value store.

Cassandra is different from most Relational Databases in that it stores data by column instead of by row.  This makes aggregating column values super fast.  It also makes dealing with the database somewhat different as well.  Instead of creating tables, you create column families.  And I shouldn’t have to mention this, but Cassandra is a NoSql solution, so don’t expect any “joins”!

Monitoring MongoDB is very similar to monitoring a normal relational database.  If it’s on its own machine then you need to care about things like how much CPU it’s taking up, how much RAM, how fast are the disks etc.   If Mongo starts grinding on any of your core compute resources then guess what, you’ve got a problem!

A good Database Administrator, which hopefully we all aspire to be, needs to monitor more then just the basics.  A good Database Administrator needs to monitor the actual database.  Not to mention in many cases especially with Mongo you will need to monitor a cluster of databases, not just one instance.  You’re in luck with Mongo, because fortunately the folks at 10gen, the makers of MongoDB, have written some excellent documentation for how to properly administer and performance tune MongoDB.

Perhaps you’ve caught our series of blogs about NoSQL database storage tools?! Monitis has begun providing guidance on picking the right tool to match your company’s IT computing needs. In our previous blog post on NoSQL, we offered a comprehensive overview of Apache Cassandra – one of the many (currently there’s more than 100 popular solutions out there) NoSQL tools available.

Today, we’ll take a look at Apache HBase – originally created for use with Apache’s Hadoop, a software framework that supports data-intensive distributed applications under a free license.

Our mission in these posts is simply to help you choose the best NoSQL DBSs – most of which are open-source and cost-free. After all, you want to make sure that your data is being stored safely. Aren’t there enough worries out there about data security – whether the data is being stored on the cloud or behind your internal, private firewall?

Gosh; there are so many NoSQL database storage tools out there. It’s almost as bad as brands of sport drinks or water. Have you noticed that some mega-supermarkets have whole aisles dedicated to what we drink!

As an IT system administrator or manager, it’s sometimes very hard to compare various NoSQL tools. It involves considering your special computing needs, matching them to what is out there, aligning what’s right for your organization and then make the right decision!

That’s why Monitis, the first hosted all-in-one network and systems performance monitoring service for sysadmins, is publishing a series of blogs that are meant to offer a comprehensive guide to NoSQL technology and brands. We want to help you make the right choice that fits the particular needs of your company.

Why should we care, you may ask yourself? Increasingly, our clients, who depend on our ability to monitor servers and networks and a host of other key metrics 24/7 from the cloud, want our advice, too, on what kind of scalable and robust database technology to use. So, we’re obliging!

Here, in a series of blogs, we’ll present research on existing popular NoSQL data storage tools that are generally intended to store unprecedented large amounts of data, offer flexible and horizontal scalability and provide blazing-fast processing queries. We’ll also get down to the nitty-gritty and compare several well-known NoSQL DBs…such as Cassandra, MongoDB, CouchDB, Redis, Riak, HBase and others.

In this first post, let’s discuss the reason why NoSQL technology is important.