Denis Kharlamov from GridGain will be presenting at Kiev JUG at Kiev, Ukraine this Saturday June 28th, 2008. All the details
are here: http://jug.com.ua/
Nikita Ivanov will be presenting at Vancouver Island JUG at beautiful Vancouver Island, BC this Wednesday, May 28th, 2008. All the details
are here: http://www.mosabuam.com/vijug.php
After several weeks of
exhausting testing we've released GridGain 2.0.3. This release is probably one of the most tested
releases to date. The goal of this release was to improve stability under the edge/failure cases in large deployments.
We have worked with several of our customers that have GridGain in large production deployments. That gave us plenty of ammunition for
scalability and performance testing. As always,
this release includes number of documentation improvements, new examples and several new functional areas
such as Java5 executor service integration.
Release notes are available here and
downloads are at the usual location.
This is special type of presentation as this conference is right in the venue of GridGain does - open source
grid computing. I will be doing a short 30 mins "GridGain - Java Grid Computing Made Simple" presentation
in the morning and then participate in a power panel "Trends in Open Source Data Grids" with folks from
Grid Engine, GigaSpaces and Hadoop.
Grid Dynamics and GridGain Systems join forces to simplify high performance grid computing for the enterprises.
Partnership between grid computing pioneers advances high performance grid computing with a
powerful Java-based open source platform and end-to-end professional services, enabling clients
to leverage grid computing quickly, cost-effectively and with less risk...
On May 8th we will be presenting at Orange County JUG. As always - we love to talk and demo our project
as it's never dull. Come see our live demos - coding from "fresh Eclipse" and having grid application in 10-15 minutes from
scratch. And I mean typing every line of code!
On April 21st Nikita Ivanov will be presenting at Cincinnati JUG. Cincinnati is one of those cities we have never been
before so this is going to be interesting. As always - we love to talk and demo our project as it's never dull.
Come see our live demos - coding from "fresh Eclipse" and having grid application in 10-15 minutes from
scratch. And I mean typing every line of code!
Another point release in 2.0 branch with many bug fixes and documentation improvements. One of the notable
improvements is a modification to our P2P class loading to support our integration work with Groovy/Grails.
We've also incorporated a good measure of feedback from our customers. As always, look at the release
notes for more information.
GridGain 2.0.2 is probably last point release before we roll out 2.5 this
summer that will contain number of new SPIs and major new functionality. Stay tuned!
I am speaking at Emerging Technologies for Enterprise 2008 conference this Thursday, March 27th at Philadelphia,
Pennsylvania. If you are attending this conference please come see my presentation - it
will be interesting as always with me doing life coding demonstrations of grid computing. Isn't
it fun to see someone life-coding a grid app just in front of your eyes (and by coding I mean typing it,
testing, debugging and fixing some embarrassing bugs)? That must be :)
I will be speaking at Albuquerque JUG this Wednesday, March 26th. I have never been to New Mexico so
this is going to be interesting. If you are around - come to see the presentation! Here is
more information http://www.abqjug.org
I will be speaking at Seattle JUG today. It is going to be fine trip
and an interesting presentation in the city harboring a lot of .NET folks. I'll be talking about "GridGain -
Grid Computing Made Simple", my favorite presentation. I'll get to talk about what is GridGain and why
it is important but most importantly show some real life coding demos.
If you see my presentations before you know that these demos are always life meaning that I
don't prepare any code and don't know your power-point coding... I just open empty Eclipse, creating
new project, and start coding away right in front of your eyes. You will see all, seriously all,
there is to it to create an interesting grid-enabled example applications.
Thanks a lot guys! As far as source code - we are taking it personally :) Size rarely matters and
we think we have one of the cleanest, readable, consistent and well designed source codes
available out there... Hundreds upon hundreds of code review is the clear reason for that.
Nikita Ivanov will be
presenting at Houston Java User Group (JUG) tomorrow February 27th at 6:30pm. If you are around - stop by and
see why grid computing with GridGain is fun, simple and productive!
It
took us extra couple of weeks to fight last minute issues but... here it
is, GridGain 2.0 with all the new features, integrations,
bug-fixes, core hardening and improved documentation. We'll be updating our wiki-based documentation
for the next week so please be patient if there are any discrepancies.
My favorite features: load balancing and data partitioning over any data cache. It is the load
balancing that actually took us for a ride when last minute load tests showed non-optimal load
balancing under the load. It took one of our best brains to actually notice that balanced distribution
was off by ~5-10% and off we went into search for this small problem: is it test,
is it something in OS, VM configurations, in the algorithm's math. In the end of the day it turned
out to be related to a rounding bug in our code and it was quickly fixed. Along the way we actually
made this SPI (adaptive load balancing SPI) more flexible via additional configuration.
I also want to thank all of our customers and users who tried GridGain and gave us
back their feedback. It is absolutely clear to me that
without this feedback GridGain would be a very different product by now.
So, download GridGain 2.0 and see what makes GridGain the fastest growing Java grid computing framework on the planet!
This is really exciting
news for our project. Last week we've got a stripped down version of GridGain to start first time
on the Android. Now, this may sound like a fairly simple undertaking but considering
the limitation and current instability of Android platform - this took us awhile to actually
workaround many current bugs and basic incompatibility of Android's Java 5 implementation. Check
this log snapshot I took from our test setup:
Log snapshot...
We are moving full speed ahead with this development and we'll be publishing more information on upcoming integration of GridGain on Android.
I'm going to be presenting at
JBoss World 2008 in Orlando on February 14th on topic of
integration between GridGain and JBoss. If you are around - come see my presentation!
With upcoming GridGain 2.0 release we are going to round up our integration plans with JBoss by providing
what I consider truly native blend-in integration. In fact, when you use GridGain with JBoss, GridGain
basically becomes a part of JBoss container that looks as if it just acquired new functionality.
Here's the list of integration points that we implement in totality with GridGain 2.0 (most of them has
been available since GridGain 1.6):
Loader for JBoss AS
Support for and integration with JBoss AOP
Integration with JBoss JMX
Integration with JBoss Logging
Integration with JBoss HA
Integration with JBoss Cache (including support for dynamic data partitioning, load balancing and affinity map/reduce)
Integration with JGroups
The reason I'm really excited about this integration is that it provides the first fully open
source full-stack grid computing platform for Java, combining state of the art compute and
data grid functionality.
And that's why I think open source Java grid computing has never been more exciting!
I found this interesting blog
by Jorge Lugo about how GridGain was deployed used in Amazon EC2. Very nice
read with source code and diagrams. Short and to the point. We are actually planning for much deeper
integration with EC2 infrastructure but even at this point EC2 deployment looks pretty cool.
Every four minutes someone around the globe starts the GridGian. In of itself these numbers are not that
impressive and we have plenty of statistics from usage to website hits - but this one remains my favorite. We
have released the first major version of GridGain just four and a half month ago and today GridGain gets
started every four minutes...
Being the young project and a very specialized software - this is certainly great progress in my view. See
for yourself what makes GridGain one of the leading Java grid computing frameworks.
NEW YORK, NY -- October 30, 2007 - GigaSpaces Technologies and GridGain Systems today announced their partnership,
which offers a high performance grid computing platform for Java. The joint offering integrates GigaSpaces'
eXtreme Application Platform (XAP) with GridGain's computation grid framework, enabling businesses to process
high volumes of data -- transactional or analytical -- in extremely short periods of time. In addition, the two
companies will cooperate on joint marketing and sales efforts.
GridGain provides an open source computational grid framework that enables Java developers to improve general
performance of processing intensive applications by splitting and parallelizing the workload. With GridGain,
developers can achieve better overall throughput, better scalability and availability of services.
GigaSpaces XAP provides a single platform for scaling-out the data, messaging and business logic of an
application. By integrating the two products, GridGain customers can enjoy a highly-scalable grid computing
platform for both computational and data-intensive applications. For maximum performance, GigaSpaces allows
GridGain to run computational tasks in the same physical machine in which the relevant data resides in memory.
GridGain team just released GridGain 1.6. This release is about stability, documentation and...
JUnit integration! We are very excited that GridGain 1.6 is the first grid product with natural
and elegant integration for JUnit. Few lines of code to change or simply add annotation - and your JUnits
are running on the grid saving you time on your build - great feature and a great use case supporting our
believe that grid computing can be an everyday tool for every Java developer.
Download GridGian 1.6 today and enjoy better core product stability, GlassFish integration,
Apache 2.0 dual-licensing for binary linkage with our APIs, much improved performance for AOP grid
enabling, better documentation and examples - and don't forget to try our new JUnit integration!
"Java Grid Computing with AOP" vendor presentation will be shown this Friday at 8th IEEE/ACM International
Conference on Grid Computing (Grid 2007). We are really excited about this conference as this is focused
exclusive on grid computing. There will be plenty of fine folks from academia and business and talks are
looking very interesting. This year this conference is hosted in Austin, Texas which should be fun place
to visit.
We will be presenting at Colorado Software Summit 2007 (CSS2007) in October 21-25. CSS07 is a unique developer's
conference in many ways... It is about the only conference that is build around the attendees: each presenter
runs his presentation every day for a week so that everybody who wants could attend each and every talk
removing usual conflicts when you have to pick one talk out of 2 or 3 going on concurrently.
It is a simple fact but hugely important for attendees: during 6 days you get to see practically all talks.
Your days away from work are very productive. CSS reminds more of a training camp on new and upcoming
technologies rather than a traditional conference. And it doesn't hurt that it is situated in a
beautiful rocky mountain resort and you can always drive to Boulder to unwind after the long conference day...
I will be presenting at JavaZone 2007 in Oslo, Norway September 13-14. JavaZone is one the largest European
Java conferences and this is a great opportunity for us to talk about GridGain project and most importantly
about the technology and ideas behind it and our view on grid computing in general.
I will be presenting
on "Java Grid Computing with AOP - Fun, Simple and Productive". In this presentation I will show a live
coding example where I will create a simple grid application in just 10-15 minutes. Should be fun!
JavaZone is a must go if you can travel (and if you are in Europe - you are just couple of hours flying
away at the most).
We have been picking up steam with support questions and we decided to put up an online forum
for GridGain project. Huge kudos to Jive Software that provided open source free license to us
which doesn't get any better - Jive Forum is a golden standard in online forum software.
This is a beta release as we going to be studying what works better and what structure and
configuration suits project's needs the best. Give it a shot. It can be found on any page on
our website on the right navigation bar in "Developers" section.
GridGain team just released GridGain 1.5.1. This point release is about documentation and better examples.
We also fixes several bugs that made their way into 1.5.0 GA. No new features have been added and
it's fully backward compatible. Enjoy better documentation and more examples. Check out also
updated screencast!
This is an important release for our project. This release was about hardening core functionality
and APIs as well as providing new integrations. GridGain now supports Jboss, Spring, AspectJ,
Weblogic, Websphere, Coherence, GigaSpaces, JXInsight, and Mule with native integrations either
as loaders, AOP frameworks or SPI implementations.
We also significantly improved our core functionality and simplified the APIs in many ways.
Among new features we've added ability for jobs in split to communicate with each other via
common task session (for common connected task problem-space).
We've also added new tracing SPI and exciting implementation for JXInsight that provides
great tracing and monitoring capabilities for GridGain.
Oh, yeah, and we switched ascii-logo back to INFO log level. So, what are you waiting for :-)
As member of IBM PartnerWorld program GridGain complete validation for "Ready for IBM Grid Computing"
seal. We were surprised by the level of attention we were given and breadth of the partner programs
that IBM provides for its partners, even to small startups like us.
IBM offers plenty of specially designed solutions for partners to run and validate their software
on practically any IBM hardware or with almost any IBM software, setup demo configuration, etc. Level
of assistance was really great too, offering to "hold the hand" on each step. Overall, unexpectedly
great job from such a behemoth like IBM...
GridGain project is moving ahead. GridGain 1.0.1 is released and available for immediate download. 5 weeks after initial release of 1.0,
almost 200 bug fixes and improvements, over 400 downloads and non-stop testing brought about 1.0.1 release.
Although 1.0.1 release is mostly about stability and bug fixes we added support for Mac OS X with specific
testing and dedicated installer. We also improved support for Windows Vista (that still has numerous general
Java issues comparing to XP). We improved logging and substantially improved stability under the load. We
retested with latest Linux kernals and distros (including Ubuntu 7.04).
18 months of work is completed. Input from the more than a dozen people. 2 months of testing. 1 month of
documentation writing. More than 20 years of combined experience in grid computing. It is open source and
it is free. Take one today.
Last couple of months has been very hectic here at GridGain. We've had number of
client engagements, frenzy on testing as well as number of last minute features
that pushed the release date but we felt they were essential to put in.
In retrospect... we still think they were and couple of months of delay was worth it.
Beta release is a beta release and we are expecting number of bugs to be fixed before
go final 1.0. We are also going to be finished Wiki documentation and Javadoc
along with more examples. Stay tuned and give the beta release a try.
Social networks have been lately in a spotlight. The concept is clear and it works: provide
web-tools for ad-hoc networking between individuals or group of individuals.
Some time ago I noticed that there is some similarity between the basic concept of social networks
and the grid computing product we are currently pushing to release. In fact, social networks are
based on capability of ad-hoc networking between previously unknown to each other entities. In our
product, grid tasks are autonomous and practically self-managed and ad-hoc decisions (ones that are
based on immediate and current context) are at the core of our design.
Stretching it a bit further one can say that our grid tasks form social networks when they get
executed... which I think is an interesting way to look at it.
The overriding theme of these three articles (and they are based off the same IT research in UK) is that Grid Computing is:
too expensive
too complex
too ambiguous in its value
Not surprising these are the same pain factors we attempts to address in our upcoming product:
it will be licensed under LGPL and its runtime will be available free of charge
it will provide revolutionary simplicity in usage
it is developed with small to mid-size business in mind that don't have months and months or even years to realize full ROI
The same research claims that only 8% of participating IT organizations has Grid Computing in their production operations - and
so Grid Computing is "not catching on".
To me this number is rather startling, indeed - almost one in 10 companies in UK with any substantial IT already has Grid
Computing in their operations. Given the nature of the Grid Computing application and shortcomings of the current offerings - I
find this number encouraging and pointing to built-up demand that is unmet by the current products.
One of the unique features of our upcoming GridGain 1.0 product is AOP-based integration.
Since the beginning, the integration part of Grid Computing products was a sore point. APIs are complex,
non-intuitive and vendor generally assumed that people writing grid-enabled software would be willing to
spend a significant time on grid-enabling process (changing their applications, learning complex grid APIs, etc.).
When we set to tackle this problem in GridGain we quickly realized that AOP can be a ticket here. Now, I've had
experience with AOP a number of years ago (when AspectJ just came out) and having studied and used it back then quite
intensively I came away rather disappointment by how little applicability it brings. I still believe that AOP is a
niche technique but when you find such niche it usually fits like a glove.
I think AOP makes an almost perfect fit in our product and that's why:
Grid-enabling (at least in Java) most often comes down to grid-enabling a method call. No matter whether you
are grid-enabling an existing code or developing a new - you will most likely deal with one method. Java5 annotations
and AOP pointcut model provide perfect tooling for defining all necessary information to grid enable a specific method.
AOP allows us to grid-enable not only the application for which you have source code, but also for applications for
which you don't have a source code (or even documentation). For non-splitting scenarios (like in on-demand computing)
you don't even have to know anything about the method - even a signature.
Think about it: using GridGain with AOP integration you can grid-enable your current application, someone else's framework,
your favorite app server or even a standard JDK. In simple cases you don't even have to write a single line of code as you
can apply aspects via external XML definition - and in the same time you have full power of AOP's pointcut model at your disposal.
When thinking about how Grid Computing software can be architected there are many angles one can look from. One such
angle that is rarely seen is whether to consider the software architecture from the "Resource" point of view, or from
the "Task" point of view.
As much as abstract it sounds this question is rather very fundamental to how your Grid Computing software will be used.
Let me explain by starting with some loose definition of these two different views.
When taking a "Resource" point of view you are basically implying that the task that is executing on the grid is "dumb".
Such task knows how to execute itself and usually that is about it as far as any interesting behavior. In this scenario
the "Resource" (i.e. software that manages the task execution such as resource manager, task scheduler, failover manager,
task loader, etc.) is a king as it decides where, how and when task gets executed. Most of the current Grid Computing software
falls into this category.
Alternatively, if one takes "Task" point of view, the task itself becomes much more intelligent as it now "knows" where,
how and when it gets executed. Symmetrically, the role of "Resource" becomes much simpler.
We at GridGain Systems have chosen "Task" point of view from the beginning for a number of reasons. In retrospect, I view
this decision as one of the two most important ones (another one being AOP-integration). Let me list these reasons as they
are interesting on their own:
Primary user of the Grid Computing software is the developer who writes code (task) that will be executed on the grid.
As simple as it sounds - it is often overlooked as many current (if not all) Grid Computing products tend to view the
developer of grid enabled business applications as a "necessary evil" for an elegantly manageable infrastructure of
the grid itself...
Having the "Task"-based orientation enabled us to give the right tools to the right user via simple APIs with unmatched
feature set.
"Task" orientation enabled us to simplify the user-facing APIs. Indeed the whole user API for GridGain consists of
less than a couple of dozens of interfaces, and simple AOP-based usage scenario requires just a handful of interfaces
to learn.
"Task" orientation allowed us to concentrate the behavioral logic in one place - in the task itself, making the task
extremely intelligent and autonomous (and, yes, IBM's notion of self-healing software is fully implemented in our design).
Task itself makes the decision on execution topology, failover strategy, resource collision resolution, splitting/aggregating,
etc.
Now, one can ask a legitimate question: why not separate the concerns of executing the task (the task body) and managing its
execution in the grid environment (scheduling, failover, collision resolution, etc.)?
The fallacy of this question (and this argument) is the same as in roles separation in EJB 2: the real world just does not
work this way. You will be hard pressed to find an organization that would have a dedicated EJB developer, EJB assembler,
and EJB administrator. Likewise, in Grid Computing world the developer that writes the executable body of the task is usually
responsible for the logic that defines where, when and how this task will be executed.
"Task" orientation is not a new concept. University of Wisconsin-Madison's work on Condor project
(http://www.cs.wisc.edu/condor), for a example, provides a fine example of resource
request/provider matching. While not purely "Task" oriented it provided important milestone in encapsulating task's behavior
into a separate concern closely related to the "Task" itself.
The usual answer is - Google it... Oh, you did? Well, the odds are that you are not any closer to the answer - and you are not alone.
Working on Grid Computing for the last 5 years I've accumulated my own share of strange looks on people faces when trying
to describe to them the grid computing idea. What is fascinating is that the actual concepts behind Grid Computing are very
familiar, simple and logical to anyone with basic understanding of how computers work.
Grid computing is not a technical term - it is a marketing term. There is no technology called "Grid Computing", there are no
products that implement "Grid Computing". The term "Grid Computing" collectively defines a set of distributed computing use cases
that have certain technical aspects in common.
There are four main use cases in distributed computing that are most often referred to as Grid Computing. Not all of them are
equal in their usage or usefulness for everyday business. Yet they probably represent more than 95% of "Grid Computing" today:
1. Computational Grids
Computational Grids account for a lion share of Grid Computing usage now and will certainly retain this lead in the near
future to the least.
In a nutshell, the idea behind it is very simple: if you have a task that is executing unacceptably long time, you can split
this task into multiple sub-tasks, execute each sub-task in parallel on a separate computer, combine results from the sub-tasks
and get the original task's result O(N)-times faster, where N is a number of sub-tasks in the split.
Computational Grids amount for almost all real-life applications of Grid Computing. The reason for this is quite obvious: unlike
other use cases it provides clear and unumbigious value and is applicable to a wide verity of business tasks. When properly
explained, it is easy to understand and easy to see how it can solve the real-life problems.
Despite ill-fated comparison to academia HPC, Computational Grids can be applicable to businesses of any size - from small
size companies to Google and Yahoo of this world. For example, even a relatively small company may have a need to speed up a
business report generation from 1 minute to 5 seconds to make it suitable for online access on their website - and in most
cases Computational Grids is the only practical approach to achieve 10 times performance improvement.
2. Utility or On-Demand Grids
This scenario is probably most over-generalized among all by the technology "visionaries" (you've surely read by now about
comparing computing resources to utility aspects of electricity or water services and how you will be able to tap into this
new type of utility by simply plugging in your computer into imaginary "computing" socket on the wall).
In a nutshell though it has surprisingly simple idea: if you have a number of tasks that from time to time spike in execution
and overload your computer(s), you can offload execution of some of these tasks during the peak time to other computers, often
located remotely. This has the following interesting characteristics:
In most cases you only pay for the actual usage time of remote computers vs. buying your own computers that will idle for
the most of the time (off peak). As an example, SUN is offering $1/CPU/hour server farms which you can rent in hour increments.
You solve the scalability but not performance, i.e. you can execute more tasks without slowing down, but you won't be executing
each task faster (in many cases you will be executing each task actually slower due to extra work for off-loading task to a remote
computer, remote computer being less powerful, etc.).
The main point of Utility or On-Demand Grids is on-demand computing availability which for certain types of businesses makes it an
attractive economic choice. For example, all online retailers experience repetitive cycles of increased customers' activity: major
holidays, back-to-school season, etc. During these cycles the activity spikes (sometimes in order of magnitude) and on-demand
computing can provide economically sound solution of handling increased load.
You may ask why not split the tasks as we do in Computation Grids and achieve the performance increase as well? The answers lies
in the fact that in majority cases the usage pattern of Computational Grids requires the constant availability of all computing
resources making on-demand point irrelevant - there is a constant demand in Computational Grids.
3. Data Grids
Date Grids allows for splitting data onto multiple computers. Much like Computational Grids splitting computations, Data Grids
allow placing data onto multiple computers or storage resources and treat them virtually like one.
However, the show here has been "stolen" by replicable distributed caching which accomplish almost the same and is readily
available today from number of vendors. More over, unlike illusive Data Grids caching technology is highly integrated with
server-side Java development. For the best example of distributed replicable caching look no further than Coherence
from Tangosol.
Another caveat of Data Grids is that their value is often unclear comparing to NAS or similar technologies.
4. Management Grids
Management Grids are only mentioned here because of Oracle. Oracle was the first company that put up a TV advertising
campaign promoting what their call "Oracle Grid". In an essence, it is a specific fault-tolerant database implementation
plus some administrative tools that allow Oracle database operate in a distributed environment in a managed fault-tolerant mode.
Oracle's grid is probably the best example of technology that has almost nothing to do with what most of us think about
the Grid Computing - yet it is routinely referred to as such.
As you can see in most cases the term Grid Computing means Computational Grid. It represents majority of uses cases and
provides clear and ready value to the user. But wait, there is more to it...
What about SOA?
There is a lot of talk going on about synergy between Grid Computing and SOA. It is however driven primarily by
implementation concerns at this point rather than by any deeper considerations. Clearly, Grid Computing can deliver
unchanged value without SOA, yet WS-* based implementation (such as Globus) can be beneficial in some cases (highly
distributed heterogeneous environments that should only exist in unfortunate legacy-support situations).
Any other prognosis (like OGSA) is nothing more than a fiction at this time.
What about cluster computing and traditional HPC?
Pundits from academia would like you to believe that there is irreconcilable difference between "primitive" cluster
computing and "sophisticated" Grid Computing. The truth is that in most cases you won't really recognize one from the
other and differences exist primarily in theory.
As far as Computational Grids are concerned the difference is minimal, if any.
Global Grids vs. Enterprise Grids?
Another categorization you can find in the media is Global Grids vs. Enterprise (non-global) Grids. In all cases you can
safely rename this discussion as Non-commercial Grids vs. Commercial Grids as Global Grids (in their pure notion) have
almost no applicability to commercial application.
In the same time, Universities find Global Grid much to their advantage as they usually don't concern themselves with
security, complex resource allocation or any other concerns that are daily dealt with in the business world.
What about OGSA/OGSI proposed by GGF and WSRF from OASIS?
Grid Computing is plagued by over-generalization, science fiction "specifications" produced by various consortiums
(whose primary reason is to collect the membership fees from the companies that want to get marketing value off a
joining such consortium or organization). As harsh as it may sound these efforts are primarily responsible for
PRODUCT
NEWS
After several weeks of
exhausting testing we've released 
I'm going
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See full press release at 
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