Category Archives: Book Reviews

Specifically book reviews

Learning Ansible Review Part 2

18 Wednesday Feb 2015

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Example Ansible playbook

So having had a significant introduction to Ansible and its capabilities, chapter 2 gets into developing Ansible Playbooks. To do this the book confronts development practises of environment creation and management scripts, or the tendency for ops teams not to apply development like rigour. It is refreshing to read things like ….

… seen these practices at close quarters, we firmly believe that these are more or less similar to voodoo practices that need to be done away with.

Excerpt From: “Learning Ansible.” Packt Publishing.

 

The book does there for dig into the basics of using Git, and illustrating it using the configuration files from an earlier example. The next step would be if you follow development practises to use a Continuous Integration (CI). The book is surprisingly brief on this subject, compared to say Git.

In a development lifecycle the next step is to test, which elegantly introduces Ansible and Vagrant for instantiating virtual machines that the Ansible playbook can be tested against.

This creates the environment by which several additional capabilities provided by Ansible can aide testing activities particularly the ability to tag activities and then run the Ansible script targeting the specifically tagged activities. The additional ability that allows Ansible Playbooks to be executed in a way that allows it only tell what would be changed, rather than perform the change.

The book takes you on from there to introducing how Serverspec could be used. Things for me gain a little too much velocity, perhaps it doesn’t help that I am not familiar with Ruby.

The final part of the chapter and we’re back on solid ground with options on configuring SCM solutions such as Git to support deployment and how Ansible can support the same playbook in different environments such production, preproduction where the playbook is the same but you will be working with different server ids and credentials.

Even if you weren’t to use Ansible there are some thought provoking and good principles for config management and system scripting here.

So by having completed the first two chapters all the principle of Ansible are covered along a range of guiding practises that reflect good development practises in the context of producing environment management. There are limits and the next chapters then go into how to build upon the basics for so it is easy to create  more advanced Playbooks for real world environments with capabilities like playbook iteration, including Playbooks within Playbooks and conditionals for example.

The chapter builds upon the simple examples used on the first chapters showing how the Playbooks can be made to be a lot smarter. For example rather than a task to install each individual application required you can build a table of configuration values and get the task to iterate through the set of RPMs and versions for example. The structures to iterate over can be multi dimensional so you can define some advanced configuration and keep the tasks simple. By building on the earlier examples it helps highlight the benefits of the feature being explained which really helps.

Other features explained here include handlers, so you can trigger one or more activities to be performed once the playbook tasks have completed – so restarting processes can be executed only when all tasks are completed for example.  Other development like features like including other Playbooks are introduced (inline with the idea of DRY – Don’t Repeat Yourself). This leads into using roles, where than identifying your target servers by name or IP you can bring everything together by assigning the server roles e.g. DBTier, AppTier etc. The final two elements are the approach to templating using the Python Jinga2 framework and most crucially given that you will be handling configuration data and passwords Security.

Another couple of well written chapters that embody both insight into Ansible but also hung on the good development ideas so even if you choose not to use Ansible, some of the thinking here could be applied or at-least used to formulate questions as to how the ideas might translate to chef or puppet for example.

Learning Ansible Review Part 1

05 Thursday Feb 2015

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I was going to publish the first part of my review of the Packt book Learning Ansible after every couple of chapters, but the preface and 1st chapter are pretty substantive not mention starts to address some of my questions regarding Ansible compared to Puppet and Chef.

So the first thing that is sticking is that the author’s style is a very easy to read flowing style. It means that your entire focus is on the content, and you don’t feel like you’re being lectured.

The preface is carries a lot of really valuable content setting the context and capabilities into which Ansible is working. It openly identifies the other leading products covering the different aspects in which someone interested in the space would want to know about or may already understand. So the following areas are called out:

  • Configuration Management
  • Provisioning
  • Deployment
  • Orchestration
  • Monitoring and Alerting
  • Logging

Chapter 1 pretty much faces into the question of differentiating Ansible from Chef and Puppet. The key being that Ansible is not a master and distributed client model which Puppet and Chef offer (although both offer a Masterless models which just distribute the client). What is missing from this initial conversation is that consideration of security. In a master and client model security can be stronger because even if you compromise the master, you still have an intermediary in the agent to protect against malicious actions. Where as breaching the Ansible node means you will have obtained SSH access to all the nodes available for management as this is how Ansible interacts with the nodes it is managing.

Despite this, the arguments are simply laid out, particularly the other significant difference is that a lot of the client-agent approaches mean they offer an abstraction of the types of activities you might want for example install an application which are abstracted from the likes of msi, yum, Red Hat Network and so on. The argument for not having this is that to provide abstraction you potentially end up dropping to the lowest common denominator (unless the tool implements capabilities not naturally available on the platform). A very fair and valid argument. It is also likely in an enterprise environment you’re probably using a small set of different types of environment and potentially only type type of environment for different solutions I.e. Your website is unlikely to be hosted by servers running Red Hat, Debian, Ubuntu and Fedora.

The first chapter takes you through a series of simple examples derived from a classic variant of IT’s classic Hello World solution. This does make for a sizeable first chapter (about 1/5th of the book) but does introduce all the core principles, ideas and capabilities that are embodied and provided by Ansible. If you want to know whether Ansible is likely to meet what you want to do then reading just this chapter will probably give you a view on whether you’re likely to be able to do what you want.

Although the book makes references to the support of Windows, but this is still in Alpha phase (Ansible Windows is Coming).This does mean that the examples are Linux only. Additionally it appears from the ansible site (the book doesn’t provide any indication of this) the central Ansible node(s) will still have to be Linux. The book in this case appears to trying to future proof itself. We hope that the author will provide Windows equivalent downloadable demos.

The long and short of it, a great start to a book.

Next Generation SOA book – part of the Thomas Erl Series

14 Sunday Sep 2014

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I recently contributed to the prepublication review of the Next Generation SOA book. Aside from offering feedback, I also provided some praise for the book which has been published at servicetechbooks.com/nextgen and quoted below …

“This is the perfect book for anyone who wants to refresh, or get a handle on the foundations of SOA without delving into the deep technical details & implementation specifics. By working from the principles, the book shows how the SOA concepts and goals have matured, influenced and grown with technologies such as Master Data, Virtualization and Cloud. The book points to other volumes in the series for the depth of detail and technicalities, allowing you to get the broad picture view and without any vendor colouration.”

– Phil Wilkins, Enterprise Integration Architect

I would actively recommend the book to anyone who has an IT leadership role.

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Puppet Reporting & Monitoring Book Review

27 Friday Jun 2014

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So the Packt book (Puppet Reporting and Monitoring) focuses down on a couple of aspects of the Puppet Toolset, as a result this is a relatively short book with only a couple hundred pages. As an enterprise architect I am no expert Puppet practitioner, my knowledge of Ruby is high level (part of the reason I reviewed this book is I wanted to better understand the art of the possible in these areas).  But despite this the book does an exceptionally good job defining a context and then explaining and showing what could be done, down to code examples.  In doing so, the author Michael Duffy introduces a number of open source libraries that can be leveraged to provide dashboard views, presentation of report content whilst maximising the leveraging of the Puppet ecosystem such as the Puppet DB (an abstracted database with a REST + JSON API).  The book goes beyond just implementation of monitoring and reporting but also engages with considerations such as deployment.  without ‘boiling the ocean’ the book provides a very good illustrations of the art of the possible and provides plenty of references to source information so working how you want to implement you own solutions.

My only criticism of the book, and it is a minor one at that is a few more diagrams to help illustrate ideas (particularly in the first chapter when discussing deployment considerations) would help get ideas across easily.

On the strength of this  book,  I hope that Michael considers taking on other authoring projects as this has been one of the best written technical books I’ve read in sometime.

Puppet Reporting & Monitoring
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Oracle Big Data Handbook – summary review

05 Monday May 2014

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Having written several detailed reviews of Oracle Press’ Oracle Big Data Handbook (links below) I thought it useful to produce a summary. Over all is a very insightful and informative book covering the range of technologies that Oracle offers to address the ‘Big Data’ space from a number of view points such hardware with the Big Data Appliance (BDA), software with NoSQL, Enterprise R and Hadoop along with the various adapters (e.g. ODI) and existing product features that existing products make available to support the big data story and contribute to make a cohesive ecosystem. The book looks beyond the technologies classically linked to the ‘Big Data’  term to explore products such as Endeca. I like the act that the book tries to explain the rational behind some of the approaches adopted and the associated value propositions. Finally book looks at governance, maturity and architectural capabilities. All of which makes for an informative and insightful book.

The book isn’t flawless a few challenges that can make the reading a little frustrating occasionally (at least for me as I went cover to cover), for example,looking at the Big Data Appliance we seem to revisit the hardware specifications multiple times. The data governance perspective is data governance not specific to big data in my opinion. Occasionally the book seems to jump about when explaining a number of related areas which means that using the book as more a reference isn’t so easy. Don’t get me wrong these issues are hugely out weighed by the value it brings.

my detailed reviews:

Oracle Big Data Handbook

Oracle Big Data Handbook

Oracle Big Data Handbook – part 3 reviewed

05 Monday May 2014

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This is the third and final part of the review of Oracle Press’ Oracle Big Data Handbook (and last part of our detailed review – previous parts can be seen Part 1 here and Part 2 here). With the first sections having introduced the Big Data Appliance and the case for adopting an appliance, followed by an in depth look at the technologies provided on the BDA for storing data we move into the section that really delivers the pay off, namely the mechanics of converting data to information i.e. Analytics. This means this section of the book concentrates on the likes of Oracle Data Mining (ODM), Oracle R Enterprise and Endeca. The first of the chapters in this part of the book looks at different types of analytics you might need to perform for example data mining, predictive analytics, text mining and so on, the result is that the chapter does seem to flip flop between more classic data warehousing (still Big Data in terms of shear data volumes) to the more contemporary hip and trendy of ‘Big Data’ in the form of Hadoop and R. This may work nicely for a DBA/Data Scientist, but as a technologist and enterprise architect it isn’t so easy as personally I’d prefer to get a sense of each product stack then look at how they compliment/overlap. That said, after the first couple of sections where both the tools and ideas are introduced the flip/flopping is quicker making it easier to cope with, but it also makes for a sizeable opening chapter for this section of the book. But let me show you the kinds in sights that can be gained from the book.

ODM extensions are built around the common Oracle toolkits of RDBMS, SQLDeveloper and additional packages to provide powerful visual paradigms and precanned analytics functionality. Not being a data warehouse expert, I like the fact that the book takes time to describe the processes for building a data model and predictive engine and the likely paths through these steps. The books goes onto to explaining the available Excel tooling. Most of this is helped along with the context of a scenario. Given the claim of realtime capability to take a transaction and use a predictive model against the transactions values to ascertain whether the transaction is likely to be indicative of the characteristics being sought after it would have been nice for the book to provide some outline benchmarks for the scenario. Realtime could be interpreted as a second or two. Which when you’re running millions of transactions with small profit margins per transaction means using such capabilities is a also expectation. Still this doesn’t take away from the clarity of the information that is explained.

From ODM the chapter moves onto introducing the R language. What really got my attention by the book is the apparent willingness to engage with an Open Source model (given the other major players in the evolution of R – Google, Facebook, LinkedIn etc you might argue there is no choice). But the book upfront addresses the fact that Oracle hasn’t (or not yet) incorporated an R editor into SQLDeveloper or JDeveloper and the book suggests a specific tool of RStudio. Then there is the engagement with a library of R extensions (CRAN – Comprehensive R Archive Network with over 5000 extensions).

Google Trends view of Analytics Tools

All of which begs the question, what is Oracle’s value proposition in this pace. The book answers this be describing the challenges of using the Open Source edition of R (memory consumption and single threaded characteristics) and how they have addressed those by extending R into Oracle R Enterprise. In addition to these constraints Oracle’s extension recognises and works with the database governance and security layers properly. It is at this point we’re brought back to earlier focus of the BDA as the extensions allow the BDA Hadoop deployment to be used as a data source (along with Oracle RDBMS). In many respects it feels like a similar proposition to Revolution Analytics (other than the RDBMS emphasis being different). As with the Data Mining the example scenario is used to illustrate the applications of R in conjunction with Hadoop and Oracle RDBMS. To support the illustration the different additional libraries are explained (such as the Hadoop connector, RDBMS connector etc).

R enterprise doesn’t stop here, but has been integrated with PL/SQL, OBIEE and BI Publisher meaning that although some of the tools and the core solution are open source Oracle has achieved a rather rich ecosystem – a point not really called out by the book, but the presentation of the details really makes this jump out.

Still with Chapter 9 we move onto text mining for activities such as sentiment analysis and jump back to ODM with an explanation of the product’s capability in this space and the challenges that this kind of analysis presents. Which is followed by a view of the support R offers. The chapter moves onto things like Spatial analytics and so on. The later forms of analytics don’t confront the ideas of ‘Big Data’ based on the book’s opening definition of big data. That isn’t to say that a brief overview of how Oracle Spatial works and its capabilities to support ideas such as Location Intelligence isn’t interesting but I don’t see any differentiation between big data and normal patterns of use for Oracle Spatial. The examples provided such as knowing if there are patterns of location based usage, but such analysis can be done by ensuring a consistent representation of location from which you can select by a range – either a postal/zip code or by latitude and longitude for example, for which there are more cost effective tools and don’t necessitate pulling data out of a Hadoop cluster to perform such analysis. I would conceded that Oracle Spatial has an information rich data set that could be very effective, but to explore such ideas should we not be looking at ideas like that of ESRI’s integration to Hadoop (and more here) for example if Oracle offer such a capability.

Having crossed a range of technologies Chapter 10 briefly talks about IDEs, but then goes for a deeper dive into R covering the supported Open Source Edition and Enterprise Edition (ORE). The differences between the two versions and the licensing issues are well explained. Based on the description what Oracle have done to make the optimisation and ability to transparently leverage the database seems pretty impressive. The only thing to remember is by transparently moving R’s computational load into the DB is what impact on other processes. Oracle have also enabled ORE to access the predictave analytics capabilities that can reside within an Enterprise Database which are also illustrated here.

After looking at ORE’s capabilities the book moves onto its connection to Hadoop for R (Oracle R Connector for Hadoop – ORCH). ORCH provides the means to interact with HDFS along with the file system and RDBMS. The connector allows for the creating of MapReduce jobs using the R language and interacting the the job scheduler. To fully leverage these capabilities you do want to pull in CRAN libraries. The book then walks through a detailed example of using ORCH with MapReduce (including R script elements). This is then followed by a similar set of examples demonstrating direct interaction with HDFS.

Chapter 11, gives us a focus change again, this time to Endeca for Information Discovery. The book takes us through the history of Endeca and Oracle explaining the component naming – before and after the acquisition and the two dimensions of the Endeca product stack – eCommerce specific and for more general BI.

The chapter looks at the Endeca data model as it is a faceted or tagged model (i.e. all values are represented as label & value). The book emphasis’ the benefits of this model – but not downsides (needing to use the label to determine semantic meaning can have performance implications). This is important is it has implications of the flexibility to enrich data that Endeca can then leverage. Once the basic product and technicalities are examined the book actually steps back to explain the differences between BI and information Discovery and therefore the approaches to using these tools. Then onto to the tooling such as the studio, engine and integration capabilities. The book continues to build on the technical side with the classic NFRs of how to make the technology scale. We then flip back to look at a number of example use cases. Before a final jump to look at mechanics of deploying Endeca and getting some development work underway. The sequencing of the chapter sections does seem a little odd, but it does work, but trying to dive into just the technical dimensions alone probably not a practical proposition here.

 

Big Data governance is taken on the final chapter of the book – Chapter 12. The emphasis here is to look at the definition of Data Management (e.g. definition by Data Management Association – DAMA) and how Big Data relates to this. So the chapter walks through the key data governance factors – many of which are characterised in the diagram above for example focusing on common legislative considerations such as HIPAA, and Patriot’s Act KYC (Know Your Customer) through to EU Data Protection and UK Financial Services Act. Having a breadth wise view of Data Governance then the book starts to look at how Big Data scenarios differ from raw data and day to day data sets. The problem I have with the chapter here, that all the points being made are valid, but they’re not Big Data issues they are any data governance issues. What Big Data does is introduce technology to capture and use data in ways previously not considered so using the technologies in this way may impact declarations that you may have made to data protection registrar e.g. declare you keep customer data to enable order fulfillment but then use the data to determine effectiveness of sales channels would be an issue. But you dont have to have big data technology to create such an issue (the book itself acknowledges that you could do the analysis with older approaches but the difference is it is easier and quicker now). Having described some ‘any data’ guidance for your big data scenarios the book goes into a raft of big data scenarios in different domains and references some of the relevant legislation. If you read the chapter as just data governance it is a good reminder of the different considerations in data governance.

The final Chapter takes on architectural and road mapping considerations. A good way to conclude as this sort of thing will draw on all the preceeding chapters’ points; and this precisely how the chapter starts recapping the value proposition described up front followed the infrastructure considerations – data volumes need to process in parrallel to handle the volumes in timeframes that mean the insights can be assessed and reacted to in a meaningful manner. After the recap the book moves into a maturity model although the origins of the model aren’t clear (I’d have thought that the basis of what is presented is routed in a wider model). This naturally leads into looking at the Oracle Architecture Design Process (OADP). The details of OADP walks thought the goals and mechanics of developing your ‘As-Is’ and ‘To-Be’ architecture so you develop a transitional roadmap. The final step is obviously enabling the journey by developing the human skills necessary to perform such as journey.

 

Previous Reviews:

Oracle Big Data Handbook – part 2 reviewed

22 Tuesday Apr 2014

Posted by in Book Reviews, General, Oracle, Oracle Press, Technology

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After an excellent start in Part 1 of Oracle Press’ Oracle Big Data Handbook (reviewed here). Part 2 moves on to looking at Apache Hadoop, Oracle’s Big Data Appliance and Oracle’s NoSQL offerings.

So chapter 3 provides a brilliant overview of Hadoop and the echo system that has been developed around it. Addressing the divergent versions of Map Reduce leading to the likes of YARN. Touching on how commericalised versions of Hadoop have been taken forward with this (such as Cloudera).

 

Apache Hadoop echo system

Moving onto to describe the core solution components such as Node Managers and the relationship to hardware and the use of more commodity kit rather than using nice expensive SAN technology.

Hadoop Structure

So now we have good (pretty much uncoloured by Oracle) view of Hadoop. Which leads into the the next chapter (chapter 4) which looks at why Oracle have taken the approach of an Appliance (which could be seen as contrary to the previous stated adoption of commodity kit).

Oracle Big Data

So as you can see Oracle woven together a set of technologies into an Exadata based platform which would not only deal with Big Data Analytics but ideally support other volume scenario needs so you’re not adding another data silo. all of which fits with Oracle’s Engineered Solutions view point. The book takes on a explains the other factors involved in the BDA design – those of commercial considerations and value propositions in relation to its customer base – very refreshing to see (rather than rationalisation through technical arguments alone).

The book addresses the challenge of why should I go to Oracle for big data? Which is well argued on the experience of very large relational deployments. Oracle’s contributions to Hadoop via Cloudera and so on. The chapter finishes with the argument around cost comparison between buying a comparable hardware solution to build your own cluster. Taking just list prices compared to HP and the hardware costs come in more or less the same, that’s before you account for the fact the Oracle price includes all the software.

 

Chapter 5 addresses the deployment of the BDA, explaining the configuration process, which with the combination of a tool called Mammoth (appropriate really) and the lies of Puppet seems pretty simple as a lot of the solution is preconfigured on the box ready. all of which is reasonably well explained. my only grumble is that we do seem to revisit the details of the hardware fairly regularly as the details are again presented here, although we go into a deeper dive in the configuration. One surprise that I’d not picked up on is that Oracle have made their NoSQL solution available as open source, although a little digging might contribute to why as it has links back to Sleepycat’s BerkeleyDB that Oracle acquired (more here). As the chapter move through the physical aspects of the deployment it also highlights in clear terms any constraints Oracle imposes to ensure that the whole appliance is supportable, the most significant of these areas is the advanced networking that is setup.

Chapter 5 as it moves through deployment considerations addresses the means to know that the appliance is running properly – so we’re talking about system monitoring not just of the hardware but the distributed nature of Hadoop and Map Reduce. So a brief view of the products deployed is given. Obviously this centres on the Enterprise Manager extensions, but also the component level tooling such as Cloudera’s Hadoop Manager.

Chapter 6 in many respects continues building out the view of Hadoop to describe briefly the analytics tooling both in the Oracle RDBMS, R language and data mining/discovery of Endeca. The interesting points in the chapter are about the relationship with RDBMS particularly as an enterprise data warehouse – something I’ve not seen really addressed elsewhere as the common world view seems to put Hadoop in the same camp as NoSQL which seems to be gaining the zeal and polarity that Linux vs Windows used to have when it comes to RDBMS. But I think the book makes a good case for right tool for the right job.

Oracle’s Strategic Product View

Chapter 7 starts to drill in to how the connector package offers which consider Oracle database data transfer, combining the R language with MapReduce and ODI.

The database connector aim to provide efficiency in transferring data between Hadoop and the Oracle RDBMS over say using Sqoop to transfer data to and from an Oracle database (ODI connectors, JDBC, direct OCI etc). To fully understand the explanation of how this works you do need to understand the basics of MapReduce although as the chapter progresses the relevant MapReduce operations are elaborated upon. As the chapter progresses we start being shown configuration fragments for the different connection approaches.

The final chapter of this section of the book looks at the NoSQL database in detail, starting with high level ideas such as how NoSQL relates to ACID and BASE ideas, dropping down into significant (but valuable) detail by describing how clients are kept in sync through the use of separate threads picking up data about the data partitioning (sharding).  Once the key components have been well described the chapter moves onto explain how Oracle has optimized the process to make the NoSQL as performant as is possible whilst providing a solution that is elastic in nature and highly resilient but still predictable in its dynamics.

The chapter finishes off with considerations such as installation, how it integrates with Hadoop and OBIEE.

Overall, this a very informative chapter, occasionally it feels like some of the information is being repeated but in a different structure but it isn’t the end of the world, although if you’re reading from cover to cover you need to just press on.

 

Part 1 of the book is reviewed here.

Oracle Fusion Applications Development and Extensibility Handbook – Summary Review

14 Monday Apr 2014

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So having written a series of detailed blog entries reviewing a couple of chapters at at time I thought it might be worth just providing a very brief review. Writing a book that provides both breadth of coverage for a very large subject area as well as meaningful depth is a very difficult trick to pull off. But the authors of this book have succeeded magnificently. The book tackles the subject of basic customization that users can perform through to in-depth feature development using the Oracle SOA stack. Not to mention reporting and analytics. The book has been written in an engaging way providing context, background and Fusion Application principles and then taking examples of how to implement the different kinds of capabilities. From this book, you should have a good grasp of what to expect and how to approach Fusion application Extension work.

As a result I’d recommend this book to Architects, Project Manager’s who want to understand what their development team should be doing and the risks of their approach. This would also form a good roadmap into the detail for developers starting out in the Fusion applications space.

 

Detailed reviews can be seen at:

Oracle Fusion Applications Development and Extensibility Handbook – Chapters 13, 14 & 15 reviewed

12 Saturday Apr 2014

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Our final detailed visit to  Oracle Fusion Applications Development and Extensibility Handbook (Oracle Press) covers the final 3 chapters which engage with the Scheduler, Look and Feel customisation and the relationship with integration and service concepts (dare I use the acronym SOA).

The chapter on the scheduler is pretty short, but then compared to many other chapters the size of the product/component is small. The book relates how the scheduler behaves compared to the Schedule Management offered in EBusiness. The surprising things is that each product domain (Financials, HCM, CRM etc) has its own scheduler rather than a single shared service; the book doesn’t attempt to explain the rational here which is a shame.  It does describe how it deploys into each domain, where the configuration exists and how to work with the configuration of the scheduler itself (e.g. where logging goes etc) and attempts to address some obvious questions from a administration perspective.  It then goes onto how to create a custom scheduled process with a worked illustration. All very well done, although I have to admit to a nagging feeling of I’m missing something – it maybe simply that deployment is very much through server administration rather than through an automated mechanism (so if you develop and test in a preproduction environment, you can package up the process of deploying config custom app to your production environment without needing to repeat the admin UI interactions, so you can be assured there is no inconsistency between deployment instances).

The Look and Feel chapter is about largely applying the changes so that the product feels like part of your business’ corporate solution – important if you’re exposing any aspects of it to the outside world. So aside from the use of the tools you have the ADF controls to effectively ‘skin’ the product. The chapter provides a brief but concise view of how skinning works, in relation to the old EBusiness technologies (CLAF and UIX) and current HTML technology of CSS and the key part of ADF (Rich Faces). More importantly it points out the relevant documentation on all the sources of information, and tooling such as the skinning editor. Not to mention addressing the issue of deployment. Obviously there is a short illustration demonstrating an element of skinning.

ADF Architecture

The initial emphasis on the last chapter is the reality that organisations can’t simply migrate all non Fusion Apps such as EBusines, Seibel etc to the Fusion solutions in one hit therefore you need to provide a degree of integration between solutions for as long as the transition may take. This neatly leads into the question of well how do I know what components exist to support integration, which brings OER (Oracle Enterprise Repository) into the picture. So obviously the book provides a brief overview to the use of OER. The various Fusion apps offer different interfaces for different tasks (from bulk data export to business events) so each of these ‘patterns’ are briefly explianed and as Fusion apps is offered as a SaaS solution how that might impact the ‘pattern’ availability. The chapter finishes by walking through the use of using a SCA Composite and web services to interact with a Fusion App – probably one of the most common approaches to integration at a transactional (rather than bulk) manner.  The only thing missing for me would be a brief discussion on Process Integration Packs (PIPs) which leverage all of  the technologies underpinning Fusion Apps into a custom package of integration operations or ready made integrations.

So the final chapters provide a strong close to the book continuing to offer an excellent overview, pointing you to resources to ‘deep dive’ as necessary.

 

Previous Chapter reviews:

Oracle Fusion Applications Development and Extensibility Handbook – Chapters 11 & 12 reviewed

08 Tuesday Apr 2014

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We continue on in our review of Oracle Fusion Applications Development and Extensibility Handbook (Oracle Press) to chapters 11 and 12 which look at Reporting and Analytics respectively.

Reporting in Fusion Apps is based upon OBIEE rather than vanilla BI Publisher against the application database. This means that you and build your reporting capability against a far more diverse set of data sources (license permitting of course). It does also mean that the steps for creating reports at least to start with are more complex as OBIEE realizes a multi-tier approach to report generation. The chapter goes onto to describe the types of data source, the means by which reports can be configured conditional execution and then through ideas such as ‘bursting’ where the report generating process can be partitioned and run in parallel by multiple processes each concentrate on a range of data (sound a little like Map Reduce doesn’t it). Finally how to format the output. All of which is then supported with a detailed illustration.  As you might imagine there are prepackaged reports and templates, so loading and configuring these in an environment is considered.

The book recognises that in a single chapter you can only really scratch the surface of reporting and makes reference to other tools in the OBIEE kit bag such as OTBI (Oracle Transactional Business Intelligence) BI and Mobile BI composer.  The only little trick here is the opportunity to point out some good sources of information.  But that isn’t a significant, there is such a thing as Google and it might take a bit more reading to find the best resources around these tools.

Chapter 12 looks briefly at the use of Analytics through OBIA (Oracle Business Intelligence Applications), Oracle Hyperion (also known as Essbase) that is available with Financial Reporting studio and focuses on OBTI. The chapter feels pretty standalone from the preceding chapter on reporting – which when using the book more as a reference is great, but from a cover to cover read can niggle a little, particularly when both chapters rely on OBIEE background.  But to be honest we are nit picking here. As with previous chapters there is an illustrated scenario walked through (the layout of which isn’t as good as previous chapters – but it is a relative observation), the illustration perhaps misses the opportunity for a killer blow of referencing the core app customisation to show how you might bind the dynamic reporting provided by OBTI view into the core CRM with the customisation. I have to say I am impressed by the OBTI technologies given the integration into the Fusion security framework, leveraging ADF and its optimisation strategies – all of which are clearly explained here.

It would have been nice to explore OBIA and Oracle Hyperion a bit further, but doing so would probably have warranted additional chapters. Overall a good chapter again, covering a lot of capability efficiently.

 

OTBI Architecture

Previous Chapter reviews: