Category Archives: Technology

UK Oracle User Group Annual Conference

01 Thursday Nov 2018

Posted by in General, Technology, UKOUG

≈ Leave a comment

Tags

, , , , , , , , , , , ,

As we rapidly approach the end of the Year.  We’re still pretty busy.  The UK Oracle User Group Annual Conference covering Oracle Technology (Tech18) ranging from Database on premises to Polyglot development in Oracle and other clouds passing through Hybrid Integration, SOA and so on.  Alongside this is also Apps18 which covers Oracle Applications from EBusiness Suite and Seibel to the Fusion cloud solutions such HCM, Financials, Taleo and so on. Then finally the 3rd part covering all things JDEdwards.

tech18

Being on the committee for the conference means that I have been heavily involved in developing the conference agenda and choosing sessions.  So I can say with great confidence that there is a very diverse range of sessions from highly respected SMEs and presenters along with new blood presenting on subjects from Oracle JET to Robotic Process Automation (RPA) for example.

I hope we’ll see you there.

Value of Technical Capability Models

01 Thursday Nov 2018

Posted by in Enterprise architecture, General, Technology, TOGAF

≈ Leave a comment

Tags

, , ,

The use of Technical Capability models is not something I have seen a lot of use of, which is a little unfortunate as they can provide tremendous insight into an organizations IT needs.

Typically you want to use the Technical capability model to be used in conjunction with a business capability model, and this is where things can get tricky as developing the business views can take time.  I came across this short video which focuses on the more business aspect but helps explain the ideas behind the models:

Note how the model is largely groups of capabilities that happen in the business. Underlying this kind of diagram you would have a brief explanation of each capability.  If you want to go all out on EA modelling then you can link the capabilities to the documented associated processes etc.

Independently, the ideal is to then identify the technical capabilities that are likely to be needed. This will provide a similar looking model. The technical capabilities are probably best drawn from industry best practices, and specific business needs. The model should be completely product agnostic. The real value comes in by then mapping the technical capabilities to which business capabilities use.

This will now help inform a number of decisions identity areas of focus.  The technical capabilities should have mappings or fall into one of the following states, with the associated reasons:

  • Maps To Business Capabilities
    • This is healthy
  • Technology is Being Used but no Business Mapping
    • Gap in the business capability model?
    • Nuance of the business model not understood by IT?
    • Redundant processes being performed?
  • Business Process with no Technology
    • Opportunity for business improvement?
    • Genuinely no value in applying technology e.g. Business Value is something is hand made?
    • Capability delivered by Shadow IT?
  • Doesn’t Map to Any Business Capabilities
    • Capability isn’t needed and therefore jettisoned OR
    • Potential capability that the business are unaware or haven’t understood what can be offered

With the exception of the 1st condition, the other scenarios things should be examined more closely and adjust the models accordingly.

With the capability models linked and the miss matches addressed.  The Technical Capability model can really deliver value by linking the capabilities to the actual technologies being used.  Very quickly it is possible to see details such as:

  • Technology weaknesses (i.e. a key business area is not well supported by IT e.g. products being mapped are End of Life, not got the level of support). Whilst some of these will be ‘no brainers’ it is more than likely a free surprises will show up
  • Technology duplication – sometimes we’ll see multiple products in one area, can the product list be rationalized to maximize license investment? Would it be more cost effective to invest 1 one high-end product and eliminate lots of smaller niche pieces?
  • Where IT investment will likely improve key capabilities vs investment on niche capabilities
  • How technology change can impact the business, for example replacing a Content Management System may impact an organizations online presence, but it may also show to impact how we deliver support services to customers.
  • If the business prioritize a specific area, how does that map onto IT systems and processes?

Whilst a lot of this will seem pretty obvious, it will uncover unexpected details and most importantly provide a relatively simple set of visualizations as cross references that help understand the business and explain the impact of IT related decisions to the business in their terms.

The following deck provides a presentation on the value of Technical Capability Models:

Defining Boundaries for Logical Gateways on the API Platform a multi cloud / multi region context

31 Wednesday Oct 2018

Posted by in API Platform CS, General, Oracle, Technology

≈ 2 Comments

Tags

, , , ,

The Oracle API Platform takes a different licensing model to many platforms, rather than on CPU it works by the use of Logical Gateways and blocks of 25 million successful API calls per month. This means you can have as many actual gateway nodes as you like within a logical group to ensure resilience as you like, essentially how widely you deploy the gateways is more of a maintenance consideration (i.e. more nodes means more gateways to take through a maintenance process from the OS through to the gateway itself).

In our book (here) we described the use of logical gateways (groups of gateway nodes operating together) based on the classic development model, which provides a solid foundation and can leverage the gateway based routing policy very effectively.

logical partitions

But, things get a little trickier if you move into the cloud and elect to distribute the back end services geographically rather than perhaps have a single global instance for the back-end implementation and leverage technologies such as Content Delivery Networks to cache data at the cloud edge and their rapid routing capabilities to offset performance factors.

map1

Classic Global split of geographies

Some of the typical reasons for geographically distributing solutions are …

  • Low hit rate on data meaning caching solutions like CDNs are unlikely to yield performance benefits wanted and considerable additional work is needed to ‘warm’ the cache,
  • Different regions require different back end implementations ordering of products in one part of the world maybe fulfilled using a partner, but in another it is directly satisfied,
  • Data is subject to residency/sovereignty rules – consider China for example. But Germany and India also have special considerations as well.

So our Global splits start to look like:

map2

Global Split now adding extra divisions for India, China, Russia etc

The challenge that comes, is that the regional routing which maybe resolved on the Internet side of things through Geo Routing such as the facilities provided by AWS Route53 and Oracle’s Dyn DNS as a result finding nearest local gateway. However Geo DNS may not be achievable internally (certainly not for AWS), as a result routing to the nearest local back-end needs to be handled by the gateway. Gateway based routing can solve the problem based on logical gateways – so if we logically group gateways regionally then that works. But, this then conflicts with the use of gateway based routing for separation of Development, Test etc.

Routing Options

So, what are the options? Here are a few …

  • Make you Logical divisions both by environment and by region – this is fine if you’re processing very high volumes i.e. hundreds of millions or more so the cost of additional Logical gateways is relatively small it the total budget.
map3

Taking the geo split and applying the traditional layers as well has increased the number of Logical gateways

This problem can be further exacerbated, if you consider many larger organisations are likely to end up with different cloud vendors in the same part of the world for example AWS and Azure, or Oracle and Google. So continuing the segmentation can become an expensive challenge as the following view helps show:

map4

It is possible contract things slightly by only have development and test cloud services where ever your core development center is based. Note that in the previous and next diagrams we’ve removed the region/country specific gateway drivers.

map5

  • Don’t segment based on environment, but only on region – but then how do you control changes in the API configuration so they don’t propagate immediately into production?
  • Keep the existing model but clone APIs for each region – certainly the tooling we’ve shared (Managing API Policy Versioning in Oracle API Platform) makes this possible, but it’s pretty inelegant and error prone as it be easy to forget to clone a change, and the cloning logic needs to be extended to take into account the bits that must be region specific.
  • Assuming you have a DNS address for the target, you could effectively rewrite the resolution of the address by changing its meaning in each gateway node’s host file. Inelegant, but effective if you have automated deployment and configuration of your gateway servers.
  • Header based routing with the region and environment as header attributes. This does require either the client to set the values (not good as you’re revealing to your API consumer traits of the implementation), or you apply custom policies before the header based routing that insert those attributes based on the gateway’s location etc.
  • Build a new type of gateway based routing which allows both the environment (dev, test etc) and location (region) to inform the routing,

Or, and the point of this blog, use gateway based routing and leverage some intelligent DNS naming and how the API Platform works with a little bit of Groovy or a custom Java policy.

Continue reading →

Helidon and the embracing of micro services

24 Wednesday Oct 2018

Posted by in development, General, Oracle, Technology

≈ 2 Comments

Tags

, , , , , , , , , , , , , ,

XEYO9H51_400x400Oracle have announced another Open Source project called Helidon (Helidon.io) as a microservices platform built on top of Netty (which is built around a contemporary async model). If you look at the literature you’ll note two flavours one called SE which aligns to the programming characteristics or Node.js – asynchronous. The other is MP which aligns to the rapidly evolving J2EE MicroProfile which essentially follows a coding style along the lines of J2EE annotations.

Whilst it is perfectly possible to run Helidon based solutions in either profile natively, it is clearly geared up for running in any Docker+Kubernetes style environments such as Oracle Kubernetes Cloud (OKE) or even ACCS. Helidon website provides the means to quickly package your solution into Docker.

In both SE and MP forms the dependencies are hugely stripped back compared to the giants of WebLogic, GlassFish (now EE4J with the handover of J2EE to the Eclipse Foundation.

It does raise a number of questions what are the futures of WebLogic and Oracle support of EE4J (some answers here, but no Oracle specific)? WebLogic has never been the fastest to align to the latest J2EE standards (EE8 standard released last year should be become available sometime this year for WLS – see here), but today it is so central to many Oracle products it isn’t going to disappear, will it just end up slowly ebbing away? Which would be a shame, I have heard it said by Oracle insiders that if the removing the end of one component could be sorted then WebLogic could be easily be configured to have a small lightweight foot print.

The other interesting thing is what is happening to Open Source and what it might mean for the future.  Up until perhaps 3 or 4 years ago the use of open source you would think of software made available on of a small group of key sponsored organisations such as Apache, Linux Foundation, Eclipse which through its governance framework, provided levels of equality and process. As result, levels of quality, trust crucially married to strong level of use and contribution that meant that to extrapolate Linus’ Law – bugs could be weeded out quickly and easily.  However with the advent of services like GitHub, whilst it has become easier to contribute and fulfill Linus’ Law. It also means that it is very easy to offer a solution that is Open Source. But, doesn’t necessarily garner the benefits of Linus’ Law and the other preconceptions we often have about Open Source such as it is/can be as good as a commercial solution. After all, throwing code into GitHub does not guarantee the many eyes/contributors. Nor does it assure the governance, checks and balances that an Apache project for example will assure.

It is important to say that I am not against github, in fact I am very much pro, and use GitHub myself to host utilities I make freely available (here). The important point is we have to be more aware of what open source actually means, in each context and can’t assume it is likely to have a strong community driving things forward, and critically dealing with bugs, and ensuring quality assurance processes are realized.

Helidon joins a number of other offerings in this space such as Micronaut (also built on Netty). Micronaut takes a different approach to Helidon by adopting a strong inversion of control / injection approach. In and in some respects feels a bit like the earlier versions of JBoss Application Server (now known as WildFly) which had a small footprint and made good use of Spring. This is in addition to Spark and Javalin. There is a good illustration of the different servers from Dmitry Kornilov  shown below and the associated article can be seen here (who also happens to the Lead Engineer for Helidon).

helidon_landscape

Unlike Spark, Micronaut and a couple of others, Helidon only supports Java today rather than JDK based languages such as Kotlin and Groovy for example, but is the only solution that can cover both the Micro Profile and Framework domains. It also has a challenge in terms of getting established, Spark has been around since 2015. Javalin appeared in May 2017. The J2EE Micro Profile standard is also driving a lot forward progress, so getting established will continue to get harder. Liberty, another Micro Profile solution is based on IBM WebSphere and Thorntail has links to WildFly (more here). We hope that it will make good headway with a Reactive engine in the form of Netty and avoiding IoC or introspection from the core should mean it will be very quick (particularly during startup) but it needs to show its value differentiation and importantly build a strong community contributing to it.

We hopefully will get the chance to further experiment with Helidon and write more about it here.

ODC Appreciation Day : ODC Podcasts

11 Thursday Oct 2018

Posted by in General, Oracle

≈ Leave a comment

Tags

, , ,

So I’m probably up bending the spirit of the ODC Appreciation Day, as the focus should be on tech. But this year I’d like to flag the podcasts put together by Bob Rhubart. These are as at-least diverse in subject as the Oracle technology portfolio. One month the podcast will be about API and the next AI, from Women in Technology to NoOps. Even if the subject is not an area that maybe of interest to you technically, the podcasts are still worth a listen you’ll encounter at-least one nugget of interesting information.

I have been fortunate enough to participate in the recording of a couple of podcasts. That combined with having In a previous roles been involved in recording and editing audio and video together means I can appreciate the effort that goes into producing the podcast. From gathering a group of different people together, often from around the world into a call isn’t always easy. Then editing the conversation to smooth out the introductions, pauses that can occur as all those non verbal cues are lost, shed any background noise to give a cohesive podcast takes time and practise.

Bob and Javed might make it look easy when recording Periscope videos at Open World and other events, but that comes from being able to control the environment – something you can’t do when participants are so far apart.

Analytics and Stats for APIs

05 Friday Oct 2018

Posted by in API Platform CS, General, Oracle, Technology

≈ 1 Comment

Tags

, , , , , , , ,

NOTE:This utility needs revamping to support IDCS for more see Making Scripts Work with IDCS Deployed PaaS

The Oracle API Platform provides the means to examine statistics and slice and dice the numbers by application, gateway, duration and so on resulting in visually appealing graphical representations.  The way the analytics works means you can book mark specific views, so you can return the same report view with the relevant features as often as you like.  However, presently there is no data export option.

The question why would I want to export the information comes down to several possible use cases, all of which relate to cost management.  The API Platform will eventually have all the desired data views, but now something to help address the following:

  • money-tization, we can see which consumer has been using the services by how much and then send the data to a companies accounting systems to invoice the users
  • Ability to examine demand and workload over time to create a projection of the likely infrastructure – to achieve this the API statistics need to be overlaid with infrastructure and performance details so we can extrapolate API growth against server workload.

To address these kinds of requirements, we have taken advantage of the fact the API Platform has drunk its own Champagne as they say and made many of the analytics querying APIs publicly available.  As with the other API Platform tools, the logic has been written in Groovy, and freely available for use – we’ve covered the code through a Create Common license.

Tool includes a range of parameters to allow the data retrieved into a CSV file having filtered in a number of different ways – which logical gateways to examine, which API or Application(s) to report on.  Finally, just to help some basic stats are produced with a count of logical gateways, API calls, APIs defined and Application definitions. The first three factors inform your cloud costs. Together the stats can help Oracle understand your use case. Note that the parameters which impact the CSV generation can also materially impact the reporting numbers.

Parameters:

The 1st three values must always be provided and in the order shown here

  1. user name to access the source management cloud
  2. password for the source management cloud
  3. The server address without any attributes e.g. https://1.2.3.4

All the following values are optional

  • -h or -help – provides this information
  • -g – Logical gateway to retrieve numbers from e.g. production or development. using ALL with this parameter will result in ALL gateways being examined
  • -f – the file to target the CSV data should be written to. If not set then the default of
  • -t – indicates whether the data provided should be taken from an APPS perspective or from an API view by passing either APPS | API
  • -d – will get script to report more information about what is happening
  • -p – reporting period which is defined by a number as follows:
    • 0 – Last 365 days – data is given as per month
    • 1 – Last 30 days – this is the default if no information is provided – data is given as per day
    • 2 – Last 7 days – data is given as per day
    • 3 – Last day – data is given as per hour

NB – still testing the utility at this moment – will remove this comment once happy

Oracle Developer Meetup London – September 2018

18 Tuesday Sep 2018

Posted by in APIs & microservices, Dev Meetup, General, Technology

≈ Leave a comment

Tags

, , , , , , , , , ,

#OracleDevMeetup in London - GraphQL

Last night we ran the latest of the Oracle Developer Meetups in London. This time Luis Weir presented on GraphQL, which got an very engaged discussion about the strengths and weaknesses of GraphQL, in-depth points about how the error paths should be handled among many other things.

The presentation material Luis used is based upon his Devoxx session earlier this year and can be seen here:

The links to Luis’ examples can be found on his GitHub account – https://github.com/luisw19/graphql-samples

After a insightful and thought provoking presentation on GraphQL the Drones with APIs project had its latest update.  Providing a lot of laughter to the evening’s proceedings. Including demonstration of flying the drone using REST APIs published via a gateway and Go back-end.  This included the DroneDash presenting a visual presentation of the commands being issues via REST, as seen here:

All the code, API definitions and documentation for people to add or extend can be found in the meetup’s GITHub – https://github.com/oracledeveloperslondon/.

A few of the useful links used or mentioned last night are:

 

The next meetup is planned for Monday November 19th.  Topics  will be published soon.

 

#OracleDevMeetup in London - GraphQL

Oracle Developer Podcast – Developer Evolution

19 Sunday Aug 2018

Posted by in development, General, Oracle, Technology

≈ Leave a comment

Tags

, ,

podcast-356-dev-evolutionLast month I was fortunate enough to have been invited to participate in another Oracle Developer Podcast.  Rather than focusing on specific technologies, this focused on more how the thew job market is changing for IT and what might be driving change, and how things may change in the future. Check it out here.

As ever thanks to Bob Rhubart of the invitation, and putting together these excellent recordings.

GraalVM – why a different VM?

09 Thursday Aug 2018

Posted by in development, General, Oracle, Technology

≈ Leave a comment

Tags

, , , ,

If you read press around Java you’ll have come across references to GraalVM. So what is it and why would I use it?

There is an excellent podcast from Software Engineering Daily that digs into the subject and can be found here and here. But let draw out some of the reasons as to why GraalVM is interesting.

Whilst multiple languages on top of the JVM is nothing new, such as Scala , Kotlin, and Groovy to name a few, GraalVM through the use of its Truffle framework takes it a new level. Truffle provides an Abstract Syntax Tree (AST) which describes the language syntax (more here about AST). The net result is any language can be described and therefore executed using the GraalVM. To this end the GraalVM team have got Node and JavaScript ported in addition to defining existing languages using this approach. Not all of this is proven robustly in production, but some of the languages VM certainly is, for example Twitter have been using the Scala port.

Because the languages are described through the same framework this means the work to optimise the VM performance becomes a lot easier.

It would be easy to assume that using the framework would mean the execution of languages using this mechanism would slow be slower. But, Truffle works by translating the code to standard byte code before execution, so ‘ported’ languages are now no less efficient than Java come runtime.

There is an interesting bi-product of this model, that at runtime with the right object exposures it is possible for multiple languages to interact with the same object easily, no JNI or dropping to the lowest common denominator such as a JSON+REST. This does raise interesting possibilities for thick client solutions or polyglot monoliths!

Probably one of the biggest pay offs for using GraalVM and its ability to run multiple languages is that the base Container images can be simplified as you don’t need different container images. This makes the work of patching and testing configurations of these container a lot simpler as the permutations will drop, particularly for organisations that have wholehearted embraced polyglot micro-service ideas.

One common reason for changing implementations of the JVM particularly at the more performance sensitive use cases (checkout Azul as an example) is how the JVM is optimised and the JIT algorithms and processes particularly the Garbage Collector work (checkout this list of JVMs. For example GraalVM will provide better performance for processes that less heap hungry than Oracle’s JVM.

It is interesting that Oracle are investing in a new VM when it wasn’t that long ago that JRockit was wound down. Given the legal dispute between Oracle and Google (see here) the new VM would give Google a means to escape from the copyright breaches and retain support for Java.

Could RedHat’s absolute commitment to OpenShift put them into difficult waters?

26 Thursday Jul 2018

Posted by in APIs & microservices, General, Oracle, Technology

≈ Leave a comment

Tags

, , , , , , ,

As a middleware (to use a fading term) or technical architect, I preferred not to get too involved in the detailed OS layer considerations when it can be helped (my Infrastructure Architect colleagues will always know more about NICs, port bonding, kernel versions etc etc than I ever will) and why I prefer to work with PaaS over IaaS.

But there is an undeniable trend where having a greater understanding of the OS is necessary, this is because we’re seeing PaaS expanding to cover code abstracted solutions such as Oracle’s Integration Cloud, Mulesoft, Dell’s Boomi etc. down to every things as code in the form of Terraform, Kubernetes, Docker and of course  microservices.

So what does this have to do with OpenShift?  Well to apply those heady aspirations we’ve had with middleware of “I can build my solution and run it on my platform anywhere” means in the world of microservices I need to find a common denominator on which I can be portable.  This comes in the form of Kubernetes and Docker and we’ll probably see service meshs in due course (Istio, Linkerd etc). Docker obviously brings the need to understand the OS albeit not at the level of bonding network connections, but still a good level of OS knowledge to do things properly. Over the last couple of years there has been a fair bit of work to achieve this with the inertia of Cloud Native Computing Foundation (CNCF), Open Container Initiative (OCI).

Continue reading →