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On other PS2 EmulatorsDo You Trust Big Data?

by Steve Garrick

In a recent New York Times article, Google Vice-President Eric Schmidt commented, “Nothing will have a greater impact on the quality of our lives and on the very survival of our species than the ability to deal with and manage our information overload.” This is the latest in a string of pronouncements about Big Data.

“Big Data” is the use of large amounts of information to make decisions based upon current trends and accurate data. If you are considering using data analytics for your business, this “Big Data” explanation is not going to be helpful to you.

Unless you have significant data already in place from a variety of sources, you will struggle to find comprehensive data you can base decisions on. Successful “data analytics” requires, not just traditional data, but current and accurate information from current trends.

When we talk about data analytics, we are talking about organizations with a critical mass of data, and the ability to see trends, analyze data and make decisions based upon current trends. The types of organizations using data analytics are numerous and included are industries as diverse as retail, finance, manufacturing, healthcare, or marketing.

The first companies to implement “Big Data” were companies in the financial sector. Financial companies will continue to be leaders in the use of “Big Data” for analytics, and should continue to benefit from the implementation of these new technologies. Using data analytics to determine the future value of a company is important to ensure a robust and competitive organization.

Healthcare will benefit from the use of “Big Data” for analytics. While the explosive growth of healthcare data has created “Big Data,” as described by McKinsey & Company, the need for a common language, standardization, standard tools, and a culture of sharing will be the key success factors. Healthcare organizations today are overwhelmed with data. For the healthcare industry, Big Data is not the easy fix it was assumed to be.

Regardless of the industry or the type of organization, successful data analytics requires organizations to have a clear vision for the future and a long-term focus on what the organization really needs to know. They will also need to acquire the right data, from the right sources, to be able to make the most accurate and timely decisions.

As with all new technologies, organizations need to consider how to work with existing processes and systems to facilitate the new process and result.

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Download a PS2 bios rom1.bin.
PS2 BIOS does not require modification and can be used with existing hardware on your computer.
Sep 12, 2012
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A:

The BIOS for the original PlayStation was public domain, so you should be able to find that on Wikipedia.
The BIOS will work just fine with SCPH10000.BIN and ROM1.BIN, which can be downloaded from Mega.

The Problem

Datadog exposes lots of metrics for us to use on the stack (Kubelet, Kubernetes, Docker, Swarm, Rook, Librato, etc). It’s simple enough to get those metrics working, but what happens when you want metrics from a different application running on the same stack? For instance, let’s say you’re running a service with hundreds of servers and you want to monitor that service through Datadog.

What you really want to do here is check the status of a particular service.

Configure All Metrics

To do this, you configure Datadog with all the metrics, their granularity, and then, when a service is checked, Datadog checks the rest of your stack for other metrics that it collects, and if the metric is present, it joins them together and exposes them as one metric. This means you could have metrics from your stack reporting separately, and when you check the status of the service, you’ll get all of them joined together as one value.

This is fairly common: you want to check the status of a particular service. You can configure this through Datadog.

You could do this by hand on a service-by-service basis, or you could do it through the API, and we’re going to do that in this post.

If you’re familiar with Datadog, you’re already familiar with the API endpoint, which allows you to get all your metrics and send them to a target location in JSON or YAML format. For instance, let’s say you have metrics for how many hosts are running, how many build retries failed, and how many builds were successful. You
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