There is a nice discussion happening on James Fee’s Blog about Web Mapping Systems and Services and the future of hosted mapping services. I was reading it and thought back to an interesting Wall Street Journal article on Monday about Circuit City that said same store sales in December fell by 12% in the US. While this news was depressing for the stock market, the silver lining for the geo-community was that navigational products were the only product line with increasing sales over the period.

Geo-devices are becoming more ubiquitous. The shear number of curious and talented people moving into our industry combined with these devices will drive product and service innovation in directions that may not be completely clear at the moment.

Converging with the mass market penetration of geo-devices and geo-content (geoware?) is the cloud computing efforts by AWS (and soon to be others). While the production of quality mapping today may require high end desktop workstations and servers, I think that Moore’s Law is eventually going to allow our field to produce geo-content and services far more easily, leading to a feedback into future product innovation. How we in the professional community create products and services today may be radically different in the future.

I offer this anecdote - today, after 10 years of running a Microsoft Exchange Server for our email requirements, we switched to Google Mail Premium. Over the 10 year period, we incurred costs of $10,000s, possibly greater than $100,000. These costs included licensing, hardware, server room, service personnel, etc. Our spam filter alone on the MSFT Exchange Server costs us $35 per year per mailbox. Our costs for Google Mail Premium service is $50 a mailbox per year. It is an easier to use, cheaper to implement, and offers more robust service than the Exchange product.

I think there might be parallels for our industry in this anecdote. It is probably a good exercise to be thinking about what products might be replacing the ones we are using today.

The future of GIS, geo-content, geo-entertainment, etc. will belong to those who can think outside of the traditional methods of production and product delivery. For historical evidence of the difference between companies that focus on the future and those that focus on their current narrow niche, look at the change in market capitalization of Trimble (TRMB) and Garmin (GRMN) over the last decade.

Above Chart taken from Google Finance

I am writing this in Seattle as we prepare for the finals of the Amazon Start-Up Challenge. We are truly excited to be a part of this Challenge. It is an amazing opportunity to be recognized for our technology and business model.

I am in love with our technology and how easy it makes it for all players, large and small, to participate in a global mapping market based on the quality of their skills and geo-content. WeoGeo will make it easy for all of us in the geospatial field to do our jobs, while at the same time increase our operating margins and productivity.

A really exciting part of this Challenge is that our business model is also being recognized by an internet service company with a $39 billion market capitalization. Everyone in our field has seen the explosion of interest in geospatial over the last few years. One only has to look at the >200 million downloads of Google Earth, as well as the consolidation by Tele Atlas and NavTeq to know that our industry is moving mainstream. This is excellent new for all of us, for it will provide more resources and revenues for our field, which translates into better opportunities for us all.

Come see the videos of the finalists in this Challenge and vote for your favorite (preferably WeoGeo!). But make sure you see our video. I hope the passion for what we are trying to accomplish is evident. I also hope that you will find what we are attempting to accomplish as exciting as we do.

Big thanks to Adena Schutzberg at All Points Blog and James Fee at Spatially Adjusted for helping us rock the vote!

The only thing I can say is, “Wow!” Followed by the biggest grin you have ever seen on my face. As one of 7 finalists, Amazon expresses their confidence in our technology and business strategy. In all honesty, I am humbled and honored by the selection, and truly thank them for their selection of us as one of the 7 finalists.

I believe (passionately) in what we are trying to create. I believe that WeoGeo will change the paradigm in how we discover and access geo-content. I believe that we (the geospatial industry) as a community will more easily synthesize new mapping products that will help us create a better world. But these are my beliefs, and I tend to view everything we do through these rose colored glasses.

The selection as a finalist by Amazon Web Services (AWS) means that someone else out there sees the same potential for the mapping and geo-content industry as we do. It provides validation for the people who have worked so hard on this project beyond anything that I could offer, and for this I am eternally grateful.

In addition, Amazon will offer the winner of this contest a venture investment. I believe this says a lot about the geospatial industry, as well as WeoGeo. For WeoGeo to be among those considered a suitable investment opportunity by a $32 billion dollar company, we must have (1) a great business plan, (2) a great set of technology, and (3) be in an industry with high growth potential. Our industry, the geospatial industry, is now recognized by a leader in internet services industry as having high growth potential.

I’ve been grinning so much, my face hurts…

WeoGeo has created a scalable, fault-tolerant infrastructure to manage its use of Amazon Web Services Elastic Compute Cloud (EC2) operations. I’ve written about it a couple of times (see this link for a listing of the Amazon tagged blogs). The latest version of WeoCEO (Version 0.1.0) is ready for release and with it we are moving from private to public Beta.

This version includes the Assistant to back up WeoCEO (see this feature described in this Amazon Web Services StartUp Event Slide Show). WeoCEO Version 0.1.0 also provides enhancements to the stable IP addressing, failure detection, and automatic scaling and load balancing. These enhancements include automatic emailing to your site administrator during trouble events and detailed logging capabilities.

WeoCEO Version 0.1.0 (including the load-balancing and auto-scaling capabilities) will be free of charge at least until December 1, 2007. It will continue to be free if you only use the stable IP addressing and auto-recovery features for a single client instance.

There will be a charge for the load-balancing and auto-scaling features of WeoCEO, which support running multiple EC2 instances and optimizing your network. The charge for these features will be $0.05 per managed client instance per hour. The charge will be on the average usage over an hour, calculated at <15 minute intervals.

You can obtain a WeoCEO ISO with the setup and installation instructions, by visiting http://www.WeoCEO.com and clicking the “Signup” button, or by clicking the Signup button below. We are still in beta, so constructive comments on any of the components that make up this service will be met with exuberance and free goodies.

This weekend was a bit crazy for some of the AWS EC2 users. EC2’s “management software erroneously terminate[d] a small number of user’s instances” (from the AWS forum post). Some of our instances were among them providing an opportunity to test the fail-safe mechanisms in WeoCEO. We received the following email:

From: Amazon Web Services
Sent: Saturday, September 29, 2007 5:46 PM
To: David Kohler
Subject: Amazon EC2 Notification of Terminated Instances

Hello,

This is just a quick note to let you know that some of your instances were erroneously terminated today. We have resolved the underlying issue, and the service is fully available.

You can find a summary of the issue here:
http://developer.amazonwebservices.com/connect/thread.jspa?messageID=68169𐩉

These are your affected instances:
i-8004e0e9
i-681ef101

We apologize for this inconvenience.

Sincerely,

The Amazon EC2 Team

If we had not prepared for this by building WeoCEO, this could have been a real issue for us. We would have needed to scramble staff at 6 AM on a Saturday morning. Fortunately, WeoCEO recovered from the failure and it was not until Monday afternoon that we notice that it happened to a lot of other people.

From WeoCEO’s architect, Bob Banfield’s, forum post:

Here is a quick shot from our WeoCEO logs. We told WeoCEO that regardless of usage we want a minimum of two instances running, so that is the initial number of instances at 6am in the morning, even though we are receiving next to no traffic. At 6:09, i-681ef101 stops responding (the first of five allowed consecutive failures). At 6:10 it still hasn’t responded, and at 6:11 both it and instance i-52907e3b have now stopped responding. Instance i-52907e3b comes back up in another 2 minutes, but instance i-681ef101 is ruled dead after 5 failures. It is automatically terminated and a new one is brought up in its place.

(SSS) Sat Sep 29 06:07:24 2007 Weoceo[6562]: Overall usage = 0% NumInstances = 2
(SSS) Sat Sep 29 06:08:25 2007 Weoceo[6562]: Overall usage = 0% NumInstances = 2
(EEE) Sat Sep 29 06:09:25 2007 Weoceo[6562]: Instance i-681ef101 has not reported statistics (1/5)
(SSS) Sat Sep 29 06:09:25 2007 Weoceo[6562]: Overall usage = 0% NumInstances = 2
(EEE) Sat Sep 29 06:10:25 2007 Weoceo[6562]: Instance i-681ef101 has not reported statistics (2/5)
(SSS) Sat Sep 29 06:10:25 2007 Weoceo[6562]: Overall usage = 0% NumInstances = 2
(EEE) Sat Sep 29 06:11:26 2007 Weoceo[6562]: Instance i-681ef101 has not reported statistics (3/5)
(EEE) Sat Sep 29 06:11:26 2007 Weoceo[6562]: Instance i-52907e3b has not reported statistics (1/5)
(EEE) Sat Sep 29 06:11:26 2007 Weoceo[6562]: No instances have reported statistics.
(EEE) Sat Sep 29 06:12:26 2007 Weoceo[6562]: Instance i-681ef101 has not reported statistics (4/5)
(EEE) Sat Sep 29 06:12:26 2007 Weoceo[6562]: Instance i-52907e3b has not reported statistics (2/5)
(EEE) Sat Sep 29 06:12:26 2007 Weoceo[6562]: No instances have reported statistics.
(EEE) Sat Sep 29 06:13:26 2007 Weoceo[6562]: Instance i-681ef101 has not reported statistics (5/5)
(EEE) Sat Sep 29 06:13:26 2007 Weoceo[11310]: Terminating i-681ef101 due to lack of statistics
(SSS) Sat Sep 29 06:13:26 2007 Weoceo[6562]: Overall usage = 0% NumInstances = 1
(III) Sat Sep 29 06:13:26 2007 Weoceo[6562]: Launching 1 instance(s)
(III) Sat Sep 29 06:13:26 2007 Weoceo[11310]: Terminating 1 instance
(SSS) Sat Sep 29 06:14:28 2007 Weoceo[6562]: Overall usage = 0% NumInstances = 1
(SSS) Sat Sep 29 06:15:28 2007 Weoceo[6562]: Overall usage = 0% NumInstances = 1
(SSS) Sat Sep 29 06:16:29 2007 Weoceo[6562]: Overall usage = 0% NumInstances = 1
(SSS) Sat Sep 29 06:17:29 2007 Weoceo[6562]: Overall usage = 0% NumInstances = 1
(SSS) Sat Sep 29 06:18:29 2007 Weoceo[6562]: Overall usage = 0% NumInstances = 1
(III) Sat Sep 29 06:19:05 2007 Weoceo[11351]: Added ID=i-94ce20fd, PublicHost=ec2-67-202-13-222.z-1.compute-1.amazonaws.com, Host=domU-12-31-36-00-1D-B4.z-1.compute-1.internal, PublicIP=67.202.13.222, IP=10.253.34.66
(SSS) Sat Sep 29 06:19:32 2007 Weoceo[6562]: Overall usage = 0% NumInstances = 2
(SSS) Sat Sep 29 06:20:32 2007 Weoceo[6562]: Overall usage = 0% NumInstances = 2

Email warnings were delivered to me 6am on Saturday alerting me to the problem, however I was fast asleep and WeoCEO corrected identified and corrected the problem.

We believe in the future of scalable utility computing. Dealing with events such as these is just a part of the issues with these types of systems that we’ll all have to overcome to make this future work. Our goal is that we can share what we are creating for WeoGeo in a way that helps other overcome such problems.

I do not wish to minimize the impact of this API outage, but it would be unrealistic to assume that this type of event will not happen in the future. We should all consider this in building our virtual computing architectures. The use of AWS means that you are outsourcing your metal infrastructure. This means that your system design must be organic and self-healing (see also slideshare link).

WeoCEO was built to help us at WeoGeo survive these types of outages. We are completing our private beta shortly, and are releasing the latest version of WeoCEO that we will be bringing into open beta. Contact us at WeoCEO [at] WeoGeo [dot] com if you would like to participate. Open beta will provide the stable IP addressing and recovery options for one instance for free.

Our solution is simple to use and operate, but does expect that you have some working knowledge of EC2. There are others who can help in building these types of architectures on AWS from the ground up (some of those contributed to the above AWS Forum thread including Thorsten at RightScale and Reuven at Enomaly).

Please be aware of the limitation of utility computing, as well as the promise. Planning for these outages will be a requirement for safely outsourcing your metal resources.

I was out of town last week. I’ll try and catch up on a number of subjects this week.

One of the reasons I was out of town was that I was invited by AWS to present at their StartUp event in Boston.

A copy of the presentation may be seen on Slideshare.net (or just click on the image). It was a great event, and I enjoyed sharing the stage with the talented people from AideRSS, Praxeon, and Geezeo. It was good to interact with others who are building (and bootstrapping) new web services using AWS.

I truly believe that utility computing is going to change the way businesses get started and (eventually) operate. However, we are going to have to build systems that are organic in how they handle resources, i.e. scale up and down as a function of load. In addition, these systems need to be self-healing by automatically addressing processor and storage outages.

The importance of self-healing will be evident in the next post.

I posted last week about bandwidth issues associated with geospatial data and our AWS S3 solution. The deciding factor for us to use Amazon’s offerings was not necessarily the edge distribution capabilities of S3, but the synergy from combining S3 data storage and distribution with virtual computing capabilities of EC2. There are multiple issues in image processing that require a ton of memory space and CPU horsepower. In both Market and Server, we offer the following basic map distribution options to our map providers -

Geo Clipping (6 zoom levels, allowing for ~125 million possible selections per data set)
Spatial Resampling (4 levels)
Layer Resampling (depends on data)
Output File types (5 - JPEG, GeoTIFF, ENVI, ESRI BIL, ERDAS IMG)
Projections (5 - UTM, Transverse Mercator, Lambert Conic, Albers Equal, Geographic)
Datums (3 - WGS84, NAD 83, NAD 27)

These options result in millions of possible map variants, which preclude the storage of each variant for distribution. So processing power for conversion is critical; and this processing power needs to be connected to a large, web-addressable, temporary data storage array to house the unique variant that a map user has selected. Now for a true mapping marketplace, this infrastructure needs to support 100s to possibly 1000s of simultaneous map requests from the same base map like the 40 GB image in Figure 1. Doing our NeoMapping Market correctly requires the creation of enormous processing, storage, and bandwidth infrastructure.

Figure 1. 40 GB, 156 layer HyperSpectral Imagery (HSI) map listed on WeoGeo Market. (Click on image to go to the listing in the Market).

However, who could afford that infrastructure upfront? Our original estimates for acquiring base computation needs and placing them into a co-location facility were around $500K. While not a lot of money in the scale of today’s internet operations, it was big for us. In addition, we were trying to develop the software architecture to support the Market and Server, and these expenses were large in it of themselves. AWS provided a unique and simultaneous answer to many of our immediate storage, processing, and distribution needs.

Developing our infrastructure on the scalable AWS solution allows us to say we can support the 1000s of map requests required for a functioning digital marketplace. The user experience is vital to the service’s credibility and therefore our success. However, there is a true (and in a number of cases unexpectedly high) cost in this decision. We traded high capital expenditures for high operating expenditures. In an upcoming post, I’ll talk about the Total Cost of Operations (TCO) on AWS, and some of the ways we are moving to reduce these high operating expenses through stability and scaling solutions. Some of these solutions we have turned into products that we provide to others (e.g WeoCEO)..

I would be interested in hearing about the actual experience of others on AWS and whether S3 and EC2 could or could not meet their needs.

This is a bit tougher than the solution discussed in this earlier post. When we (FERI) first started developing HSI sensors and flying them for others, the distribution of imagery data was mainly through DVDs. As the research groups got larger, we started getting more and more requests for data. This eventually led to the WeoGeo Server solution, which allows for customization and asynchronous delivery.

However, 100 40GB files that look like Figure 2 in my HSI post means 4TB of data through our lab’s pipe in a relatively short period of time. Our bandwidth at the time we were trying to develop these solutions was a dedicated T1, or 1.5 mbits per second. To transfer 4 TBs of imagery files with full access of our pipe would require 259 days.

Clearly there are some solutions these days that would have helped this type of large file distribution effort. Akamai, Limelight Networks, or some bittorrent solution would provide capabilities to deliver large files over distributed networks. However, we were also providing search and customization solutions, which required modification of the data before delivery. This meant that we had a scalability problem in processing as well as delivery. Edge distribution solutions would solve one part of our problem, but not necessarily the processing part.

We began to explore co-location solutions, but these seemed to require a lot of upfront costs, as well as travel and maintenance expenses. As a small business, those capital expenditures were more than we could absorb. It was at this point that we were introduced to Amazon Web Services by a former co-worker who had been recruited by Amazon. AWS allowed us to build a distribution of large data files on top of a very large pipe via S3. (I’ll discuss the processing using EC2 later). It provided us scalable distribution at reasonable cost for those 100 40GB files.

To be honest, there are some devils in the details in using S3 for our operations. But (to date), the service has been more valuable than costly. The rapid ingestion of large files into S3 is a current problem that we are trying to solve. Moving forward we hope to build on the expansion of S3 as Amazon develops more physical data storage locations. This will provide us with some of the edge distribution advantages of the above solutions, while keeping us connected with our virtual computing solutions on EC2.

I’m also curious to see how others are using S3 in geospatial solutions; if you have a unique one, please let me know.

An obvious question that drops out of yesterday’s post on the right file format to use to distribute large raster files is, “How do you distribute a 40 GB file?” The distribution of a single 40 GB file would overwhelm the bandwidth of many small businesses. That was one of the reasons we originally developed the WeoGeo Server.

Figure 1. WeoGeo Server (click on the image to see more information)

The Server allows the mapping organization to distribute customer-defined customized products that would reduce the required file size, and thus bandwidth, to satisfy their customers’ demand. However, there is still the use case where the customer wants the whole file.

Since FERI is a small business, we couldn’t have our daily research activities impacted by an imagery request. So the first (obvious) step was to develop a customization and distribution system that processes a data request in an asynchronous manner, i.e. the order is taken during business hours, but it is processed and delivered after business hours. This allowed us to optimize our bandwidth in our labs and still reasonably satisfy customer demands (assuming they did not need instantaneous data delivery). We also tweaked the system to allow some small files and all of our own requests to be processed immediately, while larger ones for external users were processed in the evenings.

The asynchronous data delivery is also a fundamental difference between our technology and online GIS servers. We optimized for discovery, customization, and ordering in a way that allows the customer to receive near-instant gratification on the discovery and ordering, while (possibly) delaying gratification on the delivery.

While the customization of product selection and the asynchronous processing and delivery bought us some additional help in terms of distributing large geospatial content files, it still did not help us with the problem of what to do with multiple requests for 40 GB image files. This is where some of my earlier posts, where I described our use of Amazon Web Services, begin to make some sense (and maybe why Jinesh digs what we are doing).

However, I am late for dinner, so I’ll pick up this theme on a later post…

I ran into an interesting article on the Amazon Web Services Blog on Metropix. The company appears to be trying to help real estate agents market properties with the creation of 2 and 3-D floor plans available properties. (They are using S3 to host their data files).

What struck me was a comment at the end of the blog, which stated “that content is still king on the Net.” In this case, the content is a form of geospatial content, just not a form that we in the professional services industry might think of as geospatial content. The GIS or survey community might overlook this content as being advertising or marketing driven, not the quantitative content that you could determine water flows through a flood plain or predict this season’s forest fire.

However, Metropix’s content is a shining example of what I believe will be an explosion of “geospatial” content. Any digital content that can be tied to a point of the ground that has value to another should be considered geospatial. This wider view dramatically expands our “traditional” concept of geospatial content, and points the way to a larger future for our field.

The question will be how to monetize this digital information. The most frequently used revenue stream in the professional services field is direct consulting services sales (e.g CH2M Hill), but there are many individual companies that are also providing direct internet sales of data to their customers (e.g Digital Globe). I would put Metropix in this category of revenue. There is of course the advertising-based model that would appear to be Google Earth’s focus (in spite of the sales of Pro and Enterprise editions).

We believe that the WeoGeo model, which combines the marketing of digital data with the services of discovery, customization, hosting, and delivery, as well as the content and derivative license management will help facilitate the expansion of the geospatial content market. A bigger geomarket helps us all generate more revenues, drawing more people and better content to the field.

I’ll match the “content is king” quote with this one, “A rising tide raises all boats.”