Like any new technology, though, it does have its pitfalls. What is Hadoop and how can you avoid the three primary pitfalls of its implementation?

What Is Hadoop?

Hadoop is the name given to a new software framework designed to use basic hardware to manage big data. It is open sourced, meaning users can change, tweak or improve the software as needed. Basically, it provides the software to turn large pieces of relatively simplistic hardware into a big data network.

You don’t have to spend thousands of dollars on servers or server hardware with Hadoop. Instead, you can link basic computer hard drives to run in parallel. It’s the same concept that allows researchers to turn a group of linked gaming consoles into a supercomputer, only now it’s being applied to big data.

A well designed, fully functional Hadoop can be a game changer for anyone who utilizes big data. It’s scalable, making it easy to upgrade or downgrade depending on the amount of data being analyzed, and is eminently flexible as well. If properly set up, Hadoop can also be much more cost-effective than traditional big data hardware or software.

Those are just a few benefits of a well-run Hadoop system. It can, if used properly, totally change the game. Because it’s open-sourced software, companies are often tempted to set up their own do-it-yourself Hadoop, which can lead to tons of problems if not done correctly. The three most common pitfalls DIY Hadoops face are cost, underestimated complexity and security challenges.

Pitfall 1: Cost

With an easy-to-use, open-sourced piece of software like Hadoop, it’s easy to assume you can pick up the cheapest hardware to go with it. After all, the software itself is nearly failure proof. If a node goes down, you’re not going to lose any information because it’s available in multiple nodes.

Unfortunately, if you choose the cheapest hardware to go with your new software, you will inevitably have nodes failing all the time. Failing nodes means downtime, which potentially means monetary losses as well as additional costs to repair them.

Good server hardware might seem like quite an investment, but when paired with Hadoop, it could easily pay for itself. As with any technology, you get what you pay for. Don’t sacrifice productivity in favor of cheap hardware.

Pitfall 2: Underestimated Complexity

While we did just call Hadoop easy to use, it isn’t as easy as plugging in a new hard drive – there is definitely a learning curve when it comes to this software. Because its open sourced, new updates and upgrades are being pushed through constantly as developers from around the world find new and more efficient ways to process data.

A new update could turn your entire operation on its head, so you need to be prepared for the ways in which the program could change in the future. That learning curve we mentioned for discovering how to use Hadoop resets itself every three months, and it gets even more complex with each new subproject that merges with Hadoop.

Pitfall 3: Security Challenges

Anytime you set up a networked system, there are always going to be security challenges. Initially, big data and programs like Hadoop were used primarily in closed internal networks. This allowed the data to be processed in-house while still providing an extra layer of security against breaches. Newer applications of the software, however, have moved to the cloud and to external networks, creating many new security concerns.

These challenges can be handled without too much trouble, but it does require your Hadoop team to remain vigilant and to have a plan in place for each new software upgrade. Tools like proper user authentication, limits on the data that can be accessed and histories for each user who accesses the data are good ways to prevent data breaches and keep security challenges to a minimum.

Overall, Hadoop is a great tool that can change the way your business uses big data, but it is definitely not something you want to jump into unprepared. Proper preparation prevents poor performance, as the old saying goes, and preparing your business to adapt a program like Hadoop should be your first priority before you start installing software or plugging in servers.

The post 3 Reasons to Avoid These DIY Hadoop Pitfalls appeared first on Colocation America.

Agility, efficiency, and stability reign supreme. If you cannot deliver these elements, your platform will suffer.

Naturally, there’s a rate of failure to contend with because data centers rely on hardware, and hardware can fail at any time.

So, you end up with experience “putting out fires” and bringing your data center back online. But the key to running a good platform is making sure downtime is not a regular thing.

With a stable data center, IT teams waste less time on fixing issues and spend more time rolling out new technologies and optimizations. This leads to a better experience for customers.

You should strive for that by implementing a solid data management plan.

Sometimes you have no control over what’s happening, like when there are major hardware failures. Servers fail, software malfunctions, and stuff just happens.

That’s why you need a data management plan.

A data management plan is a pre-determined outline that details how you will run, manage, and maintain your data center.

Data center problems can be managed two ways, preventatively and correctively.

Obviously, preventative maintenance is better, because you’re fixing potential problems before they happen. But during an emergency, corrective maintenance is necessary. In your data management plan, you must address both of these methods.

1) Maintain Proper Rack-Level Capacity

In a data center, there are a ton of servers, and they vary in utilization, power draw, and performance. These factors all correlate with one another. For instance, if you have a server that is being utilized heavily the power consumption ratings are going to increase.

This can lead to you putting too much stress on certain servers or hardware.

It’s best to figure out the power draw for a rack before you get things running, that way you can choose the proper equipment. It also allows you to plan space for upgrades of servers or arrays.

Deploying your servers in an efficient configuration will mean less stress, and better reliability.

2) Observe Server Racking Best Practices

Because you are packing servers, racks, cables, and equipment into a confined space, you want to make sure you are doing it efficiently.

Unorganized dense configurations will lead to extreme temperatures and frequent hardware failures.

Poor cable management will raise temperatures, especially if they block cooling vents or airflow. A messy space will mean more time cleaning when you need to fix a problem or perform maintenance. Your engineers will have to fight through all the cables to get to the racks.

3) Benchmark Your Servers

You can hire vendors and maintenance teams to track core counts, workloads, and performance. But what you need is a way to benchmark server performance along with a system to keep track of this data.

This info will help you with preventative maintenance, allowing you to take action before a major problem or failure. For instance, if a server is having unexpected issues then you can replace the hardware before it fails completely.

4) Always Observe Security Best Practices

Security is important. Customers want to know you can protect their data and keep it secure.

Never allow unauthorized personnel to handle equipment, and don’t give them access to your network either. Always observe basic data center security protocols.

5) Use IT Infrastructure Tools to Your Advantage

As a data center manager, no tool is more crucial than your IT infrastructure data monitoring system. Why? They monitor stats like bottlenecks, server capacity, total usage, external access attempts, and more.

When used properly, monitoring tools can tell you just about everything you need to know about the regular operation of your servers.

Implementing the tools can be a real pain, but it’s worth the hassle.

6) Configuration Management Tools Can Help

Facebook completed a migration to a Chef configuration management system, which took three years. That may seem like a long time, and it is. Hopefully, with their advice—including details about mistakes and best practices – you will be able to deploy sooner.

But don’t let that scare you. You should be following Facebook’s lead.

Configuration management tools allow for better stability and faster updates. These two things are sorely needed in the world of data centers.

7) Standardize and Optimize Change

As technologies continue to grow, change is just something you’ll need to accept. All data centers must be able to scale, which means being able to change at a moment’s notice.

Establish a change management process so that you can quickly roll out changes without running into serious problems. This will translate to a better experience for your customers, better agility, and much more flexibility. Having a good change management plan also means you can modify your platform without affecting online servers.

8) Plan for Contingencies

Imagine it’s summer and your Air conditioning units fail. You’re going to have severe heat problems inside your server room. What if there is a power surge or outage due to a storm? Do you have proper circuit boards in place to manage the power supply?

These are just two possible scenarios! You need to plan for these contingencies before they happen. Install an environmental monitoring system to monitor temperatures. Have backup AC units in the event of a serious emergency. Backup data regularly and keep replacement hardware too.

9) Get a Handle on Your IT Assets

Do you know how many users and devices are accessing your network? Do you know what OS and application licenses are going to expire soon? Do you know the age of your hardware? Do you know how many backup assets you have at your disposal?

You cannot do your job as a manager without first knowing the where, what, and why of all your IT assets. This means managing them properly. It’s not out of the question to enlist help for this. But get a system in place—digital or not—and stick to it.

10) Don’t Be Afraid to Ask for Help

If you run into a situation such as a bug, hardware failure, software issue, or general problem that you and your team cannot solve, then ask for help!

It’s okay to enlist help from a third party or vendor if you are having trouble.

Your primary goal should be to keep the data center operational, and if it’s down, get it up and running as soon as possible. That means doing what it takes, including seeking outside assistance.

The post 10 Rules to Follow While Creating the Best Data Management Plan appeared first on Colocation America.