Where is the Cloud Computing bus going?

Technological innovation patterns have often repeated themselves in history. So it is with Cloud Computing. Familiar patterns of change seem to emerge today

Here are some of main trends that I see in Cloud Computing

Advent of containers: Containers are the new hot topic in cloud computing. In virtualization guest OS’es run separately. Running separate guest OS over the hypervisor is associated with a lot of overhead for each of the heavy weight OS’es. Containers can be used as an alternative to OS-level virtualization to run multiple isolated systems on a single host. Containers within a single operating system are much more efficient being light weight while being able to provide the same level of isolation. Containers run the same kernel as the host. Here is an interesting article on containers Containers, not virtual machines are the future of the cloud.

In many ways this containers over VM innovation pattern is reminiscent of the advantages of lightweight ‘threads’ over the heavy and slow ‘process’ approach in the OS world.  It is inevitable that containers will eventually score over VMs

Open ‘something’ over proprietary’ness: Technology over the decades has always moved into an ‘open’ approach over proprietary solutions. Hence, for example, we have OpenStack for creating instances, provisioning storage, network to do many things that are being done separately by VMWare, Citrix, Hyper-V. The intent is to have a common approach over several disparate approaches. In the networking world there is OpenFlow which tries to have a uniform interface to the many different standards maintained by the Ciscos, Junipers and Brocades of the world.  There are also other technologies like OpenCV (Computer Vision processing), Open VPN (VPN protocol) etc. In all these approaches there is either to move to unify or to provide a layer over and above the disparate approaches.  I am not sure whether Openstack will prevail, only time will tell. I personally think we will move to a level abstraction that will be even above that of Open Stack.

Software Defined Everything: Cloud Computing started with the need to be able to provision computing resources through a user interface or the Web portal. This was made possible, thanks to virtualization. Users could now define and request computing resources. Soon this led to the need for being able to programmatically request storage. The trick in storage is to do ‘thin-provisioning’ or to provision resources that barely satisfies the needs of the application. The application will be able to request more storage programmatically. Not to be outdone, networking followed suit when Software Defined Networking became a reality when Stanford and University of California came with the Open Flow protocol. We have now entered into the era of Software Defined Datacenter. This is a dominant theme in Cloud Computing.

These are some of the predominant trends that are emerging in the Cloud Computing arena.

I have spent more than 2 decades of my career in telecom, implementing telecom protocols, starting in the mid-1980s. The mid 1980s was the time when digital switches started to emerge. This was followed by a spate of protocols and dizzying innovations like mobile telephony, ISDN, Intelligent Networks, Softswitch, UMTS,3G, HSDPA, LTE etc.

I personally think that Cloud computing, to use a very frayed and hackneyed term, is at a similar ‘inflexion point’. Trends are emerging and we will soon be caught in the maelstrom of rapid change and innovation.

In this post I am going to do a Marty McFly of the ‘Back to Future’ trilogy. I am going to set the clock of the Delorean DMC-12 to 2020 and ‘Whoosh…..’

21 Apr 2020:

It is 21 Apr 2020 and a sunny day.  Here is a look at the Cloud Computing landscape

• The Organization of Cloud Computing Standards (OCCS) now sets and governs the standards for all Cloud Providers of the world
• Common APIs govern provisioning of instances on the cloud regardless of the Cloud Provider. Instances are defined by RPE values, RAM and IOPS, LB, DNS requirements
• Networking bandwidth, security and storage are also standards based
• Enterprises use a ‘diffuse deployment’ strategy where the organization’s workloads are deployed to multiple cloud providers.
• Workloads are Cloud Provider agnostic.
• Enterprise applications themselves may span multiple cloud providers for e.g. the e-commerce in Cloud Provider 1, Analytics on HPC instances on Cloud Provider 2 and secure applications on Private Cloud of Cloud Provider 3. Appropriate contracts are maintained between the Cloud Providers for charging for the usage.
• Algorithms are used by enterprises to deploy workloads to cloud providers. The algorithms match the SLA and cost requirements of the application with those offered by the cloud provider to minimize the cost while meeting the SLA requirements of the applications.
• Compute, storage and networking costs fluctuate and enterprises use algorithms to optimize the deployment of workloads. Workloads are migrated to take advantage of these price changes
• Consolidation and acquisitions happen at an alarming pace. Cloud providers, storage, network and HPC providers aslo compete fiercely
• Cloud providers are swallowed by others and some lose out. The battle scene is bloody

Time to get back to Delorean. This time the clock on Delorean is set to 2025

18 Sep 2025

Today it is 18 Sep 2025, and it is sunny again, coincidentally.

• Cloud Computing is dead, mate. These days technology has moved to ‘Cloud Computing in a box’.
• The technology of these times are ‘Haze works’ where the computation happens in the stratosphere over the ether …

So much for looking into the future. It is now time to get back to the reality of VMs

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Revisiting Whats up, Watson - Using Watson's Question and Answer with Bluemix - Part 2

In this I revisit the Bluemix app based on Watson's Question and Answer service which I had posted in my earlier article "Whats up Watson? Using IBM Watson with Bluemix, NodeExpress - Part 1". In this post I removed some redundant code and also added some additional checks to the Jade templates to handle responses to "focusless"  questions viz. Am I...? or "Is X contagious?"

You can run the app at Whatsup Watson?

The code can be forked and cloned from Devops at Whatsup

The code is also available at GitHub at Whatsup

The section below briefly describes the details of the implementation of the WhatsupWatson app

A) app.js

In the app.js module the VCAP environment is parsed to get the credentials to use the Watson Question and Answer service as shown below

if (process.env.VCAP_SERVICES) {
  var VCAP_SERVICES = JSON.parse(process.env.VCAP_SERVICES);
  // retrieve the credential information from VCAP_SERVICES for Watson QAAPI
  hostname   = VCAP_SERVICES["question_and_answer"][0].name;               
  passwd = VCAP_SERVICES["question_and_answer"][0].credentials.password; 
  username = VCAP_SERVICES["question_and_answer"][0].credentials.username; 
  watson_url = VCAP_SERVICES["question_and_answer"][0].credentials.url;
}

There different ways of asking Watson questions. Watson's response will vary depending on the options and parameters that are used to POST the question to Watson. This app uses a route for each 'question type' and option. These are

a. Simple Synchronous Query: Post a simple synchronous query to Watson

This is the simplest query that we can pose to Watson. Here we need to just include the text of the question and the also a Sync Timeout. The Sync Timeout denotes the time client will wait for responses from the Watson service

// Ask Watson a simple synchronous query
app.get('/question',question.list);
app.post('/simplesync',simplesync.list);

b. Evidence based question: Ask Watson to respond to evidence given to it

Ask Watson for responses based on evidence given like medical conditions etc.

// Ask Watson for responses based on evidence provided
app.get('/evidence',evidence.list);
app.post('/evidencereq',evidencereq.list);

c. Request for a specified set of answers to a question: Ask Watson to give a specified number of responses to a question

// Ask Watson to provide specified number of responses to a query
app.get('/items',items.list);
app.post('/itemsreq',itemsreq.list);

d. Get a formatted response to a question: Ask Watson to format the response to the question

// Get a formatted response from Watson for a query
app.get('/format',format.list);
app.post('/formatreq',formatreq.list);

To get started with Watson we would need to connect the Bluemix app to the Watson’s QAAPI as a service by parsing the environment variable. This is shown below

B) simplesync.js

The code in simplesync.js, evidencereq.js, itemsreq.js,formatreq.js are similar. The modules construct the question in the format required. The details of the implementation of simplesync.js is included below a. The Watson's corpus will be set to 'healthcare' 

parts = url.parse(watson_url +'/v1/question/healthcare');

b. The POST headers are set

// Set the required headers for posting the REST query to Watson
headers = {'Content-Type'  :'application/json',
                  'X-synctimeout' : syncTimeout,
                  'Authorization' : "Basic " + new Buffer(username+":"+passwd).toString("base64")};

c. The POST request options are set

// Create the request options to POST our question to Watson
var options = {host: parts.hostname,
port: 443,
path: parts.pathname,
method: 'POST',
headers: headers,
rejectUnauthorized: false, // ignore certificates
requestCert: true,
agent: false};

The question that is to be asked of Watson needs to be formatted appropriately based on the input received in the appropriate form (for e.g. simplesync.jade)

// Get the values from the form
var syncTimeout = req.body.timeout;
var query = req.body.query;
// create the Question text to ask Watson
var question = {question : {questionText :query }};
var evidence = {"evidenceRequest":{"items":1,"profile":"yes"}};
// Set the POST body and send to Watson
req.write(JSON.stringify(question));
req.write("\n\n");
req.end();

Now you POST the Question to Watson and receive the stream of response using Node.js’ .on(‘data’,) & .on(‘end’) shown below

var req = https.request(options, function(result) {
result.setEncoding('utf-8');
// Retrieve and return the result back to the client
result.on(“data”, function(chunk) {
output += chunk;
});

result.on('end', function(chunk) {    
           var answers = JSON.parse(output);
         results = answers[0];
         res.render(
      'answer', {
                      "results":results
                                        
      });
   
});

The results are parsed and formatted displayed using Jade. For the Jade templates I have used a combination of Jade and in-line HTML tags.

Included below is the part of the jade template with in-line HTML tagging

c) answer.jade

mplementation details of WhatsupWatsonapp

The section below briefly describes the details of the implementation of the WhatsupWatson app

A) app.js

In the app.js module the VCAP environment is parsed to get the credentials to use the Watson Question and Answer service as shown below

if (process.env.VCAP_SERVICES) {
  var VCAP_SERVICES = JSON.parse(process.env.VCAP_SERVICES);
  // retrieve the credential information from VCAP_SERVICES for Watson QAAPI
  hostname   = VCAP_SERVICES["question_and_answer"][0].name;               
  passwd = VCAP_SERVICES["question_and_answer"][0].credentials.password; 
  username = VCAP_SERVICES["question_and_answer"][0].credentials.username; 
  watson_url = VCAP_SERVICES["question_and_answer"][0].credentials.url;
}

There different ways of asking Watson questions. Watson's response will vary depending on the options and parameters that are used to POST the question to Watson. This app uses a route for each 'question type' and option. These are

a. Simple Synchronous Query: Post a simple synchronous query to Watson

This is the simplest query that we can pose to Watson. Here we need to just include the text of the question and the also a Sync Timeout. The Sync Timeout denotes the time client will wait for responses from the Watson service

// Ask Watson a simple synchronous query
app.get('/question',question.list);
app.post('/simplesync',simplesync.list);

b. Evidence based question: Ask Watson to respond to evidence given to it

Ask Watson for responses based on evidence given like medical conditions etc.

// Ask Watson for responses based on evidence provided
app.get('/evidence',evidence.list);
app.post('/evidencereq',evidencereq.list);

c. Request for a specified set of answers to a question: Ask Watson to give a specified number of responses to a question

// Ask Watson to provide specified number of responses to a query
app.get('/items',items.list);
app.post('/itemsreq',itemsreq.list);

d. Get a formatted response to a question: Ask Watson to format the response to the question

// Get a formatted response from Watson for a query
app.get('/format',format.list);
app.post('/formatreq',formatreq.list);

To get started with Watson we would need to connect the Bluemix app to the Watson’s QAAPI as a service by parsing the environment variable. This is shown below

B) simplesync.js

The code in simplesync.js, evidencereq.js, itemsreq.js,formatreq.js are similar. The modules construct the question in the format required. The details of the implementation of simplesync.js is included below a. The Watson's corpus will be set to 'healthcare' 

parts = url.parse(watson_url +'/v1/question/healthcare');

b. The POST headers are set

// Set the required headers for posting the REST query to Watson
headers = {'Content-Type'  :'application/json',
                  'X-synctimeout' : syncTimeout,
                  'Authorization' : "Basic " + new Buffer(username+":"+passwd).toString("base64")};

c. The POST request options are set

// Create the request options to POST our question to Watson
var options = {host: parts.hostname,
port: 443,
path: parts.pathname,
method: 'POST',
headers: headers,
rejectUnauthorized: false, // ignore certificates
requestCert: true,
agent: false};

The question that is to be asked of Watson needs to be formatted appropriately based on the input received in the appropriate form (for e.g. simplesync.jade)

// Get the values from the form
var syncTimeout = req.body.timeout;
var query = req.body.query;
// create the Question text to ask Watson
var question = {question : {questionText :query }};
var evidence = {"evidenceRequest":{"items":1,"profile":"yes"}};
// Set the POST body and send to Watson
req.write(JSON.stringify(question));
req.write("\n\n");
req.end();

Now you POST the Question to Watson and receive the stream of response using Node.js’ .on(‘data’,) & .on(‘end’) shown below

var req = https.request(options, function(result) {
result.setEncoding('utf-8');
// Retrieve and return the result back to the client
result.on(“data”, function(chunk) {
output += chunk;
});

result.on('end', function(chunk) {    
           var answers = JSON.parse(output);
         results = answers[0];
         res.render(
      'answer', {
                      "results":results
                                        
      });
   
});

The results are parsed and formatted displayed using Jade. For the Jade templates I have used a combination of Jade and in-line HTML tags.

Included below is the part of the jade template with in-line HTML tagging

c) answer.jade

if results.question.qclasslist
    for result in results.question.qclasslist
      p   Value   =  #{result.value}  
  if results.question.focuslist
    p   Focuslist   =  #{results.question.focuslist[0].value} 
  if latlist
    p   Latlist   =  #{results.question.latlist[0].value} 

Disclaimer: This article represents the author’s viewpoint only and doesn’t necessarily represent IBM’s positions, strategies or opinions

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What’s up Watson? Using IBM Watson’s QAAPI with Bluemix, NodeExpress – Part 1

In this post I take the famed IBM Watson through the paces (yes, that’s right!, this post is about  using the same  IBM  Watson which trounced 2 human Jeopardy titans in a classic duel in 2011).  IBM’s Watson (see  What is Watson?) is capable of understanding the nuances of the English language and heralds a new era in the domain of cognitive computing. IBM Bluemix now includes 8 services from Watson ranging from Concept Expansion, Language Identification, Machine Translation, Question-Answer etc. For more information on Watson’s QAAPI and the many services that have been included in Bluemix please see Watson Services.

In this article I create an application on IBM Bluemix and use Watson’s QAAPI (Question-Answer API) as a service to the Bluemix application. For the application I have used NodeExpress to create a Webserver and post the REST queries to Watson.  Jade is used format the results of Watson’s Response.

In this current release of Bluemix Watson comes with a corpus of medical facts. In other words Watson has been made to ingest medical documents in multiple formats (doc, pdf, html, text  etc) and the user can pose medical questions to Dr.Watson. In its current avatar, its medical diet consisted of dishes from (CDC Health Topics, National Heart, Lung, and Blood Institute (NHLBI) National Institute of Arthritis and Musculoskeletal and Skin Diseases (NIAMS), National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institute of Neurological Disorders and Stroke (NINDS), Cancer.gov (physician data query) etc.)

To get down to Watson QAAPI business with Bluemix app you can fork the code from Devops at whatsup. This can then be downloaded to your local machine. You can also clone the code from GitHub at whatsup

1. To get started go to the directory where you have cloned the code for Whatsup app

2.Push the app to Bluemix using Cloud Foundry’s ‘cf’ commands as shown below

cf login -a https://api.ng.bluemix.net
3. Next push the app to Bluemix

cf push whatsup –p . –m 512M

In the Bluemix dashboard you should see ‘whatsup’ app running. Now click ‘Add Service’ and under Watson add ‘Question Answer’

Add Qatson QAAPI

You will be prompted with ‘Restage Application’. Click ‘Ok’. Once you have the app running you should be able to get started with Doc Watson.

The code for this Bluemix app with QAAPI as a Service is based on the following article Examples using the Question and Answer API

4. Here’s a look at the code for the Bluemix & Watson app.

In this Bluemix app I show the different types of Questions we can ask Watson and the responses we get from it. The app has a route for each of the different types of questions and options

a. Simple Synchronous Query: Post a simple synchronous query to Watson
This is the simplest query that we can pose to Watson. Here we need to just include the text of the question and the also a Sync Timeout. The Sync Timeout denotes the time client will wait for responses from the Watson service
// Ask Watson a simple synchronous query

app.get('/question',question.list);
app.post('/simplesync',simplesync.list);
b. Evidence based question: Ask Watson to respond to evidence given to it
Ask Watson for responses based on evidence given like medical conditions etc. This would be a used for diagnostic purposes I would presume.
// Ask Watson for responses based on evidence provided
app.get('/evidence',evidence.list);
app.post('/evidencereq',evidencereq.list);
c. Request for a specified set of answers to a question: Ask Dr. Watson to give a specified number of responses to a question
// Ask Watson to provide specified number of responses to a query
app.get('/items',items.list);
app.post('/itemsreq',itemsreq.list);
d. Get a formatted response to a question: Ask Dr. Watson to format the response to the question
// Get a formatted response from Watson for a query
app.get('/format',format.list);
app.post('/formatreq',formatreq.list);

5. To get started with Watson we would need to connect the Bluemix app to the Watson’s QAAPI as a service by parsing the environment variable. This is shown below

//Get the VCAP environment variables to connect Watson service to the Bluemix application

question.js
o o o
if (process.env.VCAP_SERVICES) {
var VCAP_SERVICES = JSON.parse(process.env.VCAP_SERVICES);
// retrieve the credential information from VCAP_SERVICES for Watson QAAPI
var hostname   = VCAP_SERVICES["Watson QAAPI-0.1"][0].name;
var passwd = VCAP_SERVICES["Watson QAAPI-0.1"][0].credentials.password;
var userid = VCAP_SERVICES["Watson QAAPI-0.1"][0].credentials.userid;
var watson_url = VCAP_SERVICES["Watson QAAPI-0.1"][0].credentials.url;

Next we need to format the header for the POST request

var parts = url.parse(watson_url);
// Create the request options to POST our question to Watson
var options = {host: parts.hostname,
port: 443,
path: parts.pathname,
method: 'POST',
headers: headers,
rejectUnauthorized: false, // ignore certificates
requestCert: true,
agent: false};

The question that is to be asked of Watson needs to be formatted appropriately based on the input received in the appropriate form (for e.g. simplesync.jade)

question.js

// Get the values from the form
var syncTimeout = req.body.timeout;
var query = req.body.query;
// create the Question text to ask Watson
var question = {question : {questionText :query }};
var evidence = {"evidenceRequest":{"items":1,"profile":"yes"}};
// Set the POST body and send to Watson
req.write(JSON.stringify(question));
req.write("\n\n");
req.end();

Now you POST the Question to Dr. Watson and receive the stream of response using Node.js’ .on(‘data’,) & .on(‘end’) shown below

question.js
…..
      var req = https.request(options, function(result) {
// Retrieve and return the result back to the client
result.on("data", function(chunk) {
output += chunk;
});

result.on('end', function(chunk) {
// Capture Watson's response in output. Parse Watson's answer for the fields
var results = JSON.parse(output);
res.render(
'answer', {
"results":results
});
});
});

The results are parsed and formatted displayed using Jade. For the Jade templates I have used a combination of Jade and inline HTML tags (Jade can occasionally be very stubborn and make you sweat quite a bit. So I took the easier route of inline HTML tagging. In a later post I will try out CSS stylesheets to format the response.)

Included below is the part of the jade template with inline HTML tagging

Answer.jade
o o o

  Question Details

for result in results.question.qclasslist
p   Value   = #{result.value}
p   Focuslist  = #{results.question.focuslist[0].value}
// The 'How' query's response does not include latlist. Hence conditional added.
if latlist
p   Latlist  = #{results.question.latlist[0].value}

o o o

Now that the code is all set you can fire the Watson. To do this click on the route

Click the route whatsup.mybluemix.net and ‘Lo and behold’ you should see Watson ready and raring to go.

As the display shows there are 4 different Question-Answer options that there is for Watson QAAPI

Simple Synchronous Question-Answer

This option is the simplest option. Here we need to just include the text of the question and the also a Sync Timeout. The question can be any medical related question as Watson in its current Bluemix avatar has a medical corpus

For e.g.1) What is carotid artery disease?

2) What is the difference between hepatitis A and hepatitis B etc.

The Sync Timeout parameter specifies the number of seconds the QAAPI client will wait for the streaming response from Watson. An example question and Watson’s response are included below

;

When we click Submit Watson spews out the following response

Evidence based response:

In this mode of operation, questions can be posed to Watson based on observed evidence. Watson will output all relevant information based on the evidence provided. As seen in the output Watson provides a “confidence factor” for each of its response

Watson gives response with appropriate confidence values based on the given evidence

Question with specified number of responses

In this option we can ask Watson to provide us with at least ‘n’ items in its response. If it cannot provide as many items it will give an error notification

This will bring up the following screen where the question asked is "What is the treatment for Down's syndrome?" and Items as 3.

Watson gives 3 items in the response as shown below

Formatted Response: Here Watson gives a formatted response to question asked. Since I had already formatted the response using Jade it does not do extra formatting as seen in the screen shot.

Updated synonym based response. In this response we can change the synonym list based on which Watson will search its medical corpus and modify its response. The synonym list for the the question "What is fever?" is shown below. We can turn off synonyms by setting to 'false' and possibly adding other synonyms for the search

This part of the code has not been included in this post and is left as an exercise to the reader :-)

As mentioned before you can fork and clone the code from IBM devops at whatsup or clone from GitHub at whatsup

There are many sections to Watson's answer which cannot be included in this post as the amount of information is large and really needs to be pared to pick out important details. I am including small sections from each part of Watson's response below to the question "How is carotid artery disease treated/"

I will follow up this post with another post where I will take a closer look at Watson's response which has many parts to it

namely

- Question Details

- Evidence list

- Synonym list

- Answers

- Error notifications

There you have it.  Go ahead and get all your medical questions answered by Watson.

Disclaimer: This article represents the author’s viewpoint only and doesn’t necessarily represent IBM’s positions, strategies or opinions

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