SaaS Panel Discussion Recap

As mentioned before, last Wednesday I moderated a panel discussion on Software-as-a-Service (SaaS) for IIT-PNW at Google Kirkland campus, an amazing experience. Our panel guests represented broad spectrum of SaaS ecosystem and the audience liberally peppered them with questions on wide variety of topics.

Interestingly, only consensus we had between panelists and audience was that SaaS will grow further and will have significant impact on various business and consumer activities.

• Defining SaaS. Web 2.0 vs. SaaS. Consumer vs. business focus. SaaS meant different things to different panelists and audience members.


• Start small. Target small. Improve quickly and frequently. Generate demand quickly. Scale as you grow. Enable experimentation.


• SaaS strengthens and grows further as web access becomes ubiquitous and available on various devices, specifically growth with internet access through mobile devices.


• Migration from Software-as-a-Product (SaaP) to SaaS. Benefits of frequent feature enhancements and quick customer feedback. Concerns about accessing data and services offline. Migration from pure web complemented by desktop client option.


• Most SaaS growth in application area and little in infrastructure area. But greater and quicker adoption in infrastructure area.


• Main benefit of application SaaS in collaborative namespace. Main benefit of infrastructure SaaS in someone else responsible for muck.


• Tools and platforms for SaaS development. Doubts about reaching a stage where operating system as SaaS in near future. Concerns on how the evolution in API access will impact the existing integrations in place.


• Concerns about Security, scalability and vendor lock-in. High switching cost with infrastructure SaaS.


• Business model - subscription vs. ad supported. Differentiation through service, experience and collaboration.

One of the panelist recounted how he sold his house from retouching images, creating flyer to final selling using only online tools. This reminded me of recent blog post by Phil Wainewright about how Appirio runs its business completely using on-demand integrated application infrastructure.

Panelists believed that SaaS margins will not be as high as SaaP and potentially declining, contrary to McKinsey's expectation of profitability improving as market grows.

Overall a great panel discussion event, thanks to great panelists and engaging audience.

Amazon Simple Storage Service (S3) is being considered a trailblazer and in an enviable position in infrastructure SaaS market. EMC/Unisys initiative shows product vendors caught off-guard with S3 growth.

How will SaaP vendors adopt to SaaS?

Cost vs. Benefit for Caching Appliances

Gary Orenstein at Gear6 sent me preview material with his press release for CACHEfx appliance launch.

I guess writing nice things about vendors once in a while has some benefits. May be, I will be crawling into doghouse, by the time Gary finishes reading this post. :-( But, somebody got to ask the hard questions.

Gear6 Unveils Industry’s First Terabyte-Scale Caching Appliances to Accelerate Data Intensive Applications

CACHEfx appliances support a baseline of 250,000 I/O Operations per Second (IOPS), 16 Gigabits per second of throughput, microsecond response time and scale linearly to handle millions of IOPS. The Reflex OS™ virtualizes appliance memory into a scalable coherent cache pool, optimizes data delivery through parallel I/O channels, and provides robust intelligent cache services.

CACHEfx centralized storage caching solutions are available now starting at $400,000.

My jaw dropped after looking at starting price tag of $400,000. My first reaction was "Damn, this thing is expensive!" The performance stats like 250K IOPS and 16Gbps throughput are impressive but let's be realistic how many customers can afford to pay $1.60 an IOPS to speed up applications, beyond hedge funds and stocks/options traders. I am looking forward to a ROI/TCO justification in near future.

How big is the market for caching appliances anyway? I hazard to guess that $1.6 an IOPS eliminates most web companies with intensive data access performance as well as a large portion of HPC market.

When and where can caching appliance threaten the parallel and clustered storage solutions?

SaaS, Opportunity for Innovation

I will be moderating a panel discussion SaaS, Opportunity for Innovation at Google campus Kirkland, Wednesday, May 16th. The panel discussion is part of May monthly meeting of our alumni organization IIT-PNW. I am looking forward to facilitating a great discussion among our panel guests and audience. Our esteemed panel hails from wide spectrum of SaaS (Software-as-a-Service) ecosystem.

• Russ Arun, General Manager, Windows Live Communications, Microsoft. His current role includes Mail, Messenger, Manageability, Storage and back-end services for Windows Live.
  
• Charlie Bell, Vice President, Utility Computing, Amazon. His current role includes the Elastic Compute Cloud (EC2) and the Simple Storage Service (S3).
  
• Kevin Marcus, Chief Technology Officer, Intelius. His current role includes technology ecosystem of a SaaS offering.
  
• Peeyush Ranjan, Engineering Manager, Google. His current role includes web search related projects with prime area of interest in building large scalable systems.

Would you like to attend the event? Please send an RSVP to IIT-PNW President, Mohan Venkataramana at mohan_13 [at] msvi [dot] org. Please mention this blog post in your message. The admission to this event may be limited due to the capacity restrictions of facility and IIT-PNW's primary responsibility to IIT graduates.

Would you like to be the "mystery" panelist? If you are opinionated, hail from SaaS ecosystem, don't belong to organizations already represented on the panel, send me an email with your contact info, interest, background and introduction.

It is going to be a very interactive event, slide-free, prop-free, whiteboard may be. All panel guests will have 5 minutes to introduce SaaS (What, Why, Where, Who, How) from their viewpoints followed by 40 - 60 minutes of audience Q&A.

Do you have a question on SaaS topic for our panel guests? Send me an email. Please indicate if you like your name and affiliation to be withheld. All responses will be posted on this blog.

Our last panel discussion Mobile Advertising - Technical Challenges and Business Opportunities moderated and blogged by Chetan Sharma had overwhelming response and very engaging audience. Unfortunately, being at Storage Networking World (SNW) in San Diego, I missed this great evening.

Look for a recap of the event sometime later in the week.

SVW: Storewiz. What do I like? Compression.

There are three key factors (compression process, unpredictability of data reduction techniques, and allaying buying fear from startup) that are attractive for Storewiz. It doesn't appear that Storewiz is highlighting these factors publicly. I don't know, why? My cynical side cautions you to take these virtues with grain of salt. Of course, there is no doubt about the ultimate benefit with Storewiz appliance, the data footprint reduction on a storage device.

As you may realize (See previous posts, Storage Vendors to Watch: Storewiz. I and SVW: Storewiz. Q&A. and resulting comments), compression doesn't seem to get much love in storage industry with primary concerns being CPU utilization and performance impacts. How does Storewiz implement compression?

There is not enough information available from Storewiz on compression methodology and implementation. Most of the information below comes from Storewiz patent applications, specifically Method and System for Compression of Files for Storage and Operation on Compressed Files [US 2006/0184505 A1].

ABSTRACT. A method and system for creating, reading and writing compressed files for use with a file access storage. The compressed data of a raw file are packed into a plurality of compressed units and stored as compressed files. One or more corresponding compressed units may be read and/or updated with no need for restoring the entire file whilst maintaining de-fragmented structure of the compressed file.

The segments of an original file are sequentially compressed, by segment, into series of compression logical units (CLUs). The metadata for compressed section and corresponding CLUs are stored in a separate table.

Reading data stored in a compressed file requires identifying relevant compressed segment then CLUs belonging to that segment. Then, applicable CLUs are restored until all data that need to be read is restored.

Updating data stored in a compressed file follows the similar process as read. But, it involves a little more complexity as number of CLUs that need to be written after update can change from original number of CLUs restored.

Based on the patent document, the uniqueness in Storewiz compression implementation probably comes from:

• Random access to data in compressed stored files
  
• Operations on the compressed data without decompressing entire file
  
• Compression/decompression operations transparent to users
  
• User unawareness of the storage location of the compressed data

The compression in an appliance approach is the easiest, quickest and very flexible one to follow from initial product development and adoption perspective. Once, this method for block devices and communication matures, I don't see anything preventing from merging the functionality into storage and networking hardware as SBCs.

SVW: Storewiz. Q&A.

Continuing from Storage Vendors to Watch: Storewiz. I

First the disclaimer for those with fertile imagination, I don't speak for Storewiz. Most information was obtained through public sources along with discussions at SNW with executives and others.

Let's address questions from Storagezilla, before I continue with my thoughts on Storewiz. He objected to the phrase "with better predictability than data de-duplication product."

What struck me about that is just like de-dup the data you're working with will dictate what savings you'll get. Image files or movies? Damn all or close to damn all. 1:1. … Databases or text files? Hell, you could get 5:1 compression, perhaps even more.

The data type is only one factor that impacts savings from data de-duplication. The others being "duplicity" of data in the dataset targeted for data de-duplication, "duplicity" of the dataset in stored data, targeted saving type, internal dedupe design and the implementation of data de-duplication solution in end-user environment.

Real life data de-duplication ratios vary a lot from 2:1 to 100:1. Data type on its own is not enough to be able to predict with certainty the achievable data reduction with data de-duplication. Beyond data type, data duplicity and the variations in duplicity over time is the main reason for a wide range in data reduction.

Why, when and where, "predictability" of data footprint reduction target matters more than the "highest achievable" data footprint reduction? Let's hear your thoughts first!

I've known about StoreWiz for a while now but I've always wondered where the FC/iSCSI compression boxes were?

Based on what I was told by Storewiz executives at SNW, the expected release is Q3/Q4, 2007. I am as usual skeptical of "Q3/Q4" claims like most people who have some experience dealing with any storage vendor. Most vendors say Q3/Q4 when asked in Q1/Q2 for time frame of next or new release. So, I wait too!

The sheer computational grunt required for such compression is an issue, …

I wrote in the last post, The strategy is similar to hardware compression in storage devices but with a twist that makes Storewiz implementation very resource efficient. Further explanation when I discuss three things that make Storewiz stand out in the data reduction market. As usual my opinion only.

All opinions expressed on this blog are my own, whether sink or swim. Your dissents, corrections and attempts to influence my opinions are always welcome.

Storage Vendors to Watch: Storewiz. I

At SNW, I enjoyed briefings from two vendors the most. The enthusiasm of IBRIX executives for their product was contagious. And, simplicity of Storewiz product had me jump at the first opportunity to meet with company executives, JF Van Kerckhove and Jon Ash.

Storewiz product fits into two of the three themes, I observed at SNW, Global data reduction and Special-purpose appliances. It is a single-purpose appliance that helps you reduce the data footprint on storage devices with better predictability than what you get from data de-duplication products. Storewiz product provides real time on the fly compression, transparent to end user, easily added in front of the existing storage devices, and in some cases may improve performance.

What! that was my reaction when I first heard the performance improvement claims. Over the years, we all have been programmed to believe that compression slows things down and takes too many CPU cycles. My first reaction to performance improvement claims was no way! compression is an overhead, most probably slowing everything down. What is the first question that pops in to your mind when you hear compression?

The compression/decompression activity is performed by CPUs in Storewiz appliance eliminating the need to run compression process on storage devices or hosts. The strategy is similar to hardware compression in storage devices but with a twist (explained later in another post) that makes Storewiz implementation very resource efficient.

Storewiz execs also claimed that their appliance doesn't increase latency by more than 50 - 100 microseconds. I believe as long as the latency caused by compression process doesn't exceed the net decrease in time to write "compressed" data to the disks, you could potentially see the performance improvements during write operations. Same is true for reading the data from disk and decompression process which is also enhanced by read cache. Storewiz patented resource efficient compression implementation also reduces the need to compress/decompress too much data.

Checkout the image below showing NetApp read/write performance and CPU utilization with and without Storewiz appliance listed in one of their case study.

To be continued …