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How To Successfully Implement a Big Data Project in 8 Steps

Monday, October 28th, 2013 by

There are countless ways to incorporate Big Data to improve your company’s operations. But the hard truth is that there’s no one-size-fits-all approach when it comes to Big Data. Beyond understanding your infrastructure requirements, you still need to create an implementation plan to understand what each Big Data project will mean to your organization. At a minimum, that plan should include the following 8 steps.

Big-Data-Cloud

Step 1: Gain executive-level sponsorship

Big Data projects need to be proposed and fleshed out. They take time to scope, and without executive sponsorship and a dedicated project team, there’s a good chance they’ll fail.

Step 2: Augment rather than re-build

Start with your existing data warehouse. Your challenge is to identify and prioritize additional data sources and then determine the right hub-and-spoke technology. At this stage, you’ll want to get approval to evaluate a few options until you settle on the appropriate technology for your needs. (more…) «How To Successfully Implement a Big Data Project in 8 Steps»

How to Build Highly Available Applications with Cloud Infrastructure

Tuesday, July 30th, 2013 by

Every technology company starts with a great idea. And in the early stages of application design, the decisions you make can have a long-term impact. These design decisions are critical and can make or break both the product and the company. At GoGrid, we’ve helped a lot of customers architect applications for the cloud and along the way we’ve learned a thing or two about the decisions you need to make. Here are 3 key questions to help you get started.

Uptime

1. Traditional data center or cloud infrastructure (IaaS)?

One of the first and most important decisions is whether to go with a traditional data center or architect in the cloud by leveraging an infrastructure-as-a-service (IaaS) provider. Although a traditional data center provides absolute control over hardware and the software, there’s a significant downside to maintaining the hardware. These costs can be significant, but if you move to the cloud, you can avoid them completely. The GoGrid, Amazon Web Services, and Microsoft clouds are all maintained by professionals, allowing you to focus on your application rather than the hardware. By going with an IaaS provider, you also gain application flexibility that lets you scale resources up and down as needed. And we can all agree that in most cases, scaling an application horizontally is preferable to scaling vertically. This option is especially important when your application reaches global proportions and you require specialized features like global load balancing to ensure minimal application latency or even support for regional application variations (think multiple languages for global applications).

2. Where does multi-tenancy reside?

In most cases, you’ll also need to make a decision about where multi-tenancy resides. If you were to architect in a traditional data center, you might take a shortcut and decide to put each customer on a separate machine. However, doing so would be a mistake for a few reasons. First, applications no longer run on a single box that’s scaled up, which means isolating users to individual machines no longer makes much sense. What’s worse, that approach would create a management nightmare by requiring you to monitor thousands of machines as your application scales users. Plus, this type of architecture locks you into a particular vendor or service provider, and you probably don’t want that. So where should multi-tenancy reside? The answer is easy: It should reside in the application layer above the virtual machine or server layer. By architecting multi-tenancy into the application layer, you’re free from lock-in and able to scale resources as needed, avoiding costly over-provisioning. You’ve also allowed customers to scale beyond the resource constraints of a single server. Equally important, this approach lets you architect failover scenarios that ensure high availability and consistency even if the underlying platform has an issue.

(more…) «How to Build Highly Available Applications with Cloud Infrastructure»

How To Optimize Cloud Server Workloads to Maximize Efficiency

Monday, September 24th, 2012 by

If you’re familiar with cloud infrastructure and infrastructure-as-a-service (IaaS), you probably understand the substantial benefits that come along with deploying infrastructure in the public cloud: things like “utility billing and on-demand availability,” “elastic benefits that let you scale resources up and down based on demand,” and “the ability to rapidly move and redeploy workloads as needed.” This flexibility is why we originally brought GoGrid’s hourly pay-as-you-go Cloud Servers to market. They’re perfect for specific cases like these:

  • Periodic workloads that only run for a few hours, days, or weeks during a given billing cycle
  • Short-term, project-based workloads where term commitments aren’t desirable
  • Short-term spikes in workload where demand is erratic and being able to scale resources up and down quickly are desirable
  • Development and test workloads that require rapid iteration and redeployment of resources
  • Proof of concept workloads where instant access to resources and the ability to quickly change technology are key

Customers with steady-state and long-term workloads don’t always need this hourly flexibility, however. And that’s why GoGrid has developed prepaid monthly, semiannual, and annual Cloud Server products. Prepaid Cloud Servers are less flexible, but they do offer significant cost savings in exchange for the term commitment. The shortest prepaid term GoGrid offers is a monthly prepaid Cloud Server and the longest term is an annual prepaid Cloud Server.

If you run a constant workload during a given month, a prepaid term server is probably a better solution than an hourly server. Again, the tradeoff here is flexibility. Prepaid servers are ideal for:

  • Steady-state workloads where demand is constant
  • Workloads that tend to grow rather than contract
  • Production applications where you can plan for demand in advance

For example, imagine you run an eCommerce website. You know you always need three servers to run your operations throughout the year. During the holiday season, however, you know demand is likely to spike. Your deployment of annual servers going into the holiday would look something like this:

(more…) «How To Optimize Cloud Server Workloads to Maximize Efficiency»

How to Predict Elastic Cloud Computing Costs for Your Organization

Tuesday, March 6th, 2012 by

Every day I talk with customers about the benefits of cloud computing—everything from faster provisioning of resources, to reduced management overhead, to flexible workload management. The benefits are becoming well-known; however, when it comes to managing an IT budget, these benefits can also present a challenge. Unlike virtual compute, network, and storage resources, budgets aren’t elastic. Your company’s CFO doesn’t want to see that your nimble IT organization is spending $100 today and $1,000 tomorrow. He doesn’t care that you’ve matched IT resources to your customer’s demand curve. No my friend, what your CFO wants is predictability. Fortunately for you, that’s a challenge we’ve solved with our improved plan pricing for cloud servers.

To demonstrate how this new plan works, let’s build a simple model where your usage changes from one month to the next. In month 1, you need three servers for 400 hours, one server for 80 hours, and two servers for the entire month. For simplicity’s sake, we’ll assume all servers are 1 GB and 1 core. Using Pay-As-You-Go pricing, this configuration of servers on GoGrid would cost you $0.12 for each hour an individual server is running. The math for the first month’s configuration looks like this:

3 X 1 GB server x 400 hours = 1,200 hours used
1 x 1 GB server x 80 hours = 80 hours used
2 x 1 GB server x 730 hours = 1,460 hours used

The total hours used for all servers = 2,740 hours at a rate of $.12 per hour.

Total Pay-As-You-Go cost for month 1 = $328.80.

PayAsYouGo-Cloud

(more…) «How to Predict Elastic Cloud Computing Costs for Your Organization»