Cloud
Computing: who should use it?
•Cloud
computing definitely makes sense if your own security is weak, missing features,
or below average.
–the web-services interfaces don’t introduce
too many new vulnerabilities, and
–the cloud provider aims at least as high as
you do, at security goals,
then
cloud computing has better security.
IoT Solutions & Challenges Internet of Things (IoT) and Big Data Solutions • Adding Big Data platform allows to store all raw data in the distributed file system in a scalable and reliable manner Challenges • How can we leverage the Big Data platform for more than just storing raw data? How does it combine with the stream processing?
Continuous Ingestion / Fan-In from the Edge DB Source Big Data Log Stream Processing IoT Sensor Event Hub Topic Topic REST Topic IoT GW CDC GW Connect CDC DB Source Log CDC Native IoT Sensor IoT Sensor, Dataflow GW Topic Topic Queue MQTT GW Topic Dataflow GW Dataflow TopicREST 37 File Source Log Log Log Social Native Internet of Things (IoT) and Big Data37 Topic Topic
Challenges for Ingesting Sensor Data Internet of Things (IoT) and Big Data • Multitude of sensors • Multiple Firmware versions • Bad Data from damaged sensors • Data Quality.
REST / SOAP REST / SOAP IoT 6a) Adding Data Mining / Machine Learning and Model execution 40 Mobile Apps D B Rich (Web) Client Apps D B (ESB) / Data Integration IoT Devices IoT Gateways IoT Smart Devices Event Hub Event Hub Enterprise Apps WS External Cloud Service Providers BPM and SOA Platform Event Business Logic/Rules Business Intelligence Services WS Event Processes Visualization Analytics DB Service Bus Oracle Data IntegratorKafka Kafka Kafka SOAP Various SQL SOAP REST WebSocket JMS JMSAPI GatewayAPI Gateway REST REST Kafka Kafka SQL REST REST REST / SOAP Stream Processing ESP/CEP DB DB Big Data Processing HDFS Batch Processing DB Kafka Kafka HDFS ESP/CEP Edge Analytics MQTT MQTT Stream Analytics Hadoop / Spark Oracle Big Data Appliance SOA Suite BPM Suite Business Activity Monitoring Internet of Things (IoT) and Big Data40 Kafka / MQTT / REST Kafka / MQTT / REST = one way = request/response I 4.0 Machine DB CDC GoldenGate MQTT Kafka / MQTT / REST Kafka.
IoT Reference Architecture Internet of Things (IoT) and Big Data
IoT Services IoT Logical Reference Architecture IoT Device Sensor Actuator IoT Gateway Storage UIApp Streaming Analytics Enterprise Applications BPM and SOA PlatformStreaming Analytics Storage Endpoint Management Event Hub Service Bus Event Hub Event Hub Service Bus Big Data / BI Storage Services Processes UIApp Storage Bulk Analytics UI Bulk Analytics UI Storage Streaming Analytics Service Bus API REST SOAP HTTP KAFKA MQTT CoAP XMPP DDS AMQP KAFKA WIFI BLE ZigBee WIFI Wired Internet of Things (IoT) and Big Data43
IoT Services IoT Logical Reference Architecture – Oracle on premises IoT Device Sensor Actuator IoT Gateway Storage UIApp Streaming Analytics Enterprise Applications BPM and SOA PlatformStreaming Analytics Storage Endpoint Management Event Hub Service Bus Event Hub Event Hub Service Bus Big Data / BI Storage Services Processes UIApp Storage Bulk Analytics UI Bulk Analytics UI Storage Streaming Analytics Service Bus API REST SOAP HTTP KAFKA MQTT CoAP XMPP DDS AMQP KAFKA WIFI BLE ZigBee WIFI Wired Edge Analytics Business Activity Monitoring SOA Suite BPM Suite Service Bus Oracle Data Integrator Stream Analytics Big Data Appliance Stream Analytics Service Bus API Gateway Internet of Things (IoT) and Big Data44 Oracle IoT CS Gateway Oracle IoT CS Client Library
IoT Services IoT Logical Reference Architecture – Oracle Cloud Services IoT Device Sensor Actuator IoT Gateway Storage UIApp Streaming Analytics Enterprise Applications BPM and SOA PlatformStreaming Analytics Storage Endpoint Management Event Hub Service Bus Event Hub Event Hub Service Bus Big Data / BI Storage Services Processes UIApp Storage Bulk Analytics UI Bulk Analytics UI Storage Streaming Analytics Service Bus API REST SOAP HTTP KAFKA MQTT CoAP XMPP DDS AMQP KAFKA WIFI BLE ZigBee WIFI Wired Edge Analytics Oracle BI CS Oracle Big Data CS Oracle SOA CS Oracle Integration CS Oracle IoT CS Oracle Streaming Analytics CS Oracle Messaging CS Oracle Big Data Discovery CS Oracle Mobile CS Internet of Things (IoT) and Big Data45 Oracle IoT CS Gateway Oracle IoT CS Client Library Oracle Process CS Oracle DataFlow ML CS Big Data Preparation CS Application Container CS Container CS.
Introduction Internet of
Things (IoT) and Big Data.
Internet of Things (IoT) Wave Internet of
Things (IoT): Enabling communication between devices, people & processes to
exchange useful information & knowledge that create value for humans Term
was first proposed by Kevin Ashton in 1999 Source: The Economist Source:
Ericsson, June 2016 Internet of Things (IoT) and Big Data.
Reasons why IoT opportunity
is occurring now ?
Affordable hardware • Costs
of actuators & sensors have been cut in half over last 10 years Smaller,
more powerful hardware • Form factors of hardware have shrunk to millimetre or
even nanometer levels Ubiquitous & cheap mobility • Cost for mobile
devices, bandwidth and data processing has declined over last 10 years Availability of supporting tools •
Big data tools & cloud based infrastructure have become widely available
Mass market awareness • IoT has surpassed a critical tipping point • Vision of
a connected world has reached such a followership that companies have initiated
IoT developments • Commitment is irreversible Internet of Things (IoT) and Big
Data6
The Sensing-as-a-Service
Model Internet of Things (IoT) and Big Data.
Towards an IoT Architecture
Internet of Things (IoT) and Big Data
Key Challenges for building
an IoT application
1. Connect: How to collect
data from intelligent devices? • Abstract complexity associated with device
connectivity • Standardize integration of devices with enterprise
2. Analyze: How to analyze
IoT data? • Reduce noise and detect business event at real-time • Enable
historical big-data analysis
3. Integrate: How to
integrate IoT data & events with enterprise infrastructure? • Make
enterprise processes IoT friendly • Allow enterprise & mobile applications
to control devices Internet of Things (IoT) and Big Data.
Today) Existing Service-/API
Architecture as a base 19 Mobile Apps D B Rich (Web) Client Apps D B API
Gateway Enterprise Service Bus (ESB) / Data Integration Enterprise Apps WS
External Cloud Service Providers BPM and SOA Platform Event Business
Logic/Rules Business Intelligence Services WS Event Processes Visualization
Analytics DB REST / SOAP REST / SOAP REST / SOAP SOAP Various SQL SOAP REST
Service BusOracle Data Integrator API Gateway SOA Suite BPM Suite Business
Activity Monitoring Internet of Things (IoT) and Big Data = one way =
request/response.
REST / SOAP REST / SOAP IoT 1a) Reuse exiting
Service-/API-based Architecture IoT Smart Devices 20 Mobile Apps D B Rich (Web)
Client Apps D B Enterprise Service Bus (ESB) / Data Integration Enterprise Apps
WS External Cloud Service Providers BPM and SOA Platform Event Business
Logic/Rules Business Intelligence Services WS Event Processes Visualization
Analytics DB REST / SOAP REST REST JMS / REST SOAP Various SQL SOAP REST
WebSocket JMS Service BusOracle Data Integrator API Gateway API Gateway JMS JMS
WeblogicJMS SOA Suite BPM Suite Business Activity Monitoring Internet of Things
(IoT) and Big Data = one way = request/response.
What is a CMS?
A content management system - better known as a CMS - is a kind of software that’s designed for the creation and modification of digital content. Among its wide variety of features, it usually offers publishing options, version control, search engine optimization, access control, and different design templates. It streamlines the content creation and publishing processes by providing a simple user interface that supports your marketing strategy, without requiring any advanced technical knowledge from users. It is used to create user friendly environment.
Core functionality and managing assets factors should you pay attention to when choosing a technology to build a CMS?
A good CMS should provide multiple handy out-of-the-box functionalities; this will make working with content easier and more robust. It should also allow for easy asset management.
User interaction:
The CMS should be intuitive and user friendly; it should provide self-explanatory ways to manage content and even add new subpages.
SEO:
A good CMS should be prepared for SEO. The page structure, meta tags, and other auto-generated content have to be SEO-friendly.
Integration with other systems:
The CMS should be a place gathering in one spot different external services and providers necessary for your business to function, such as payment gateways or social media integrations.
Popularity:
It’s super important to choose a technology which is backed by a large community, offers lots of integrations and extensions along with easy-to-find manuals.
Experts:
You need to have access to a broad market of IT specialists who will help you create your ideal team and be able to fill in any rotation gaps.
Performance:
The selected technology should start performing right out of the box, and be easy to install and deploy without bearing additional expenses on external support.
Cloud storage:
You might need a wide range of cloud solutions for installing and storing the entire system.
Security:
It’s safer to select a full-fledged technology - one that has already been tested in many different areas and is supported by a community that deals with any new bugs.
All of these factors appear to be outstanding in Python development.
Why is Python a good language of choice for creating a CMS?
1. Maturity:
Python has two big players in the world of CMSs: Wagtail and Django CMS. Both are well-tested and mature, quality solutions, with a large community of customers, editors and - above all - developers who are constantly working on new features and releasing updates and bug fixes. This is important because it makes the software even more functional and reliable.
2. Ease of use and speed :
Python frameworks are easy to adapt and convert into a tailor-made CMS, while at the same time act like building blocks for programming. This is extremely helpful when it comes to fast delivery with a limited team, as you can have a lot of functions, like contact forms, WYSIWYG editor or page hierarchy without coding, since they are already implemented.
3. Prebuilt admin dashboard:
Both Wagtail and Django CMS are built on top of the Django framework which comes with a prebuilt admin dashboard. This is a huge advantage in terms of the speed of developing a CMS that has a built-in space for admins to manage content, users, and so on. You can get a sneak peek by clicking on the links: DjangoCMS/Wagtail.
4. Advanced and ready-to-use features:
The biggest advantages of Python frameworks include: simplicity of deployment, the availability of cloud solutions (like AWS, GCP or Heroku) and a lot of single-click tools that make it possible to establish proper CI/CD pipelines for high degrees of automation in the process of delivering new code. These and many other things guarantee that your product will be well-tested and resistant to time.
What is crucial from business perspective?
All of these points are not only significant for devs, but also crucial from a business perspective.
When you use a mature and relatively secure framework backed by so many experts, you don’t have to spend a lot of time and money on any additional support.
You also have more specialized developers to choose from. Looking for someone to fill a vacancy is not so problematic.
The ease of use and many built-in features already available in the framework make development go much faster. It’s also more efficient and less costly.
The further development of your CMS also becomes simpler, so you can think about unwinding its full potential, making it as made-to-measure as possible.
Remember: if you don’t adjust the technology required for building a CMS properly, this may result in a lengthier development and very poor support in the case of a critical situation. There’s also a big chance that you will be dramatically limited by its functions, so scaling may be a nightmare. You might spend a lot of money on solving problems that wouldn’t have occurred if you had just selected a better option.
This is why creating a Python-based CMS may be the safest alternative.
There are many reasons behind the state of insecurity in IoT. Some of it has to do with the industry being in its “gold rush” state, where every vendor is hastily seeking to dish out the next innovative connected gadget before competitors do.
• Under such
circumstances, functionality becomes the main focus and #security takes a back
seat.
Connectivity • Connecting so many devices will be
one of the biggest challenges of the future of IoT, and it will defy the very
structure of current communication models and the underlying technologies.
• At present we rely on the centralized,
server/client paradigm to authenticate, authorize and connect different nodes
in a network.
This model is sufficient for current IoT
ecosystems, where tens, hundreds or even thousands of devices are involved. But
when networks grow to join billions and hundreds of billions of devices,
centralized brokered systems will turn into a bottleneck.
• Such systems will require huge investments and
spending in maintaining cloud servers that can handle such large amounts of
information exchange, and entire systems can go down if the server becomes
unavailable.
• The future of IoT will very much have to depend
on decentralizing IoT networks. Part of it can become possible by moving
functionality to the edge, such as using #fog computing models where smart
devices such as IoT hubs take charge of time-critical operations and cloud
servers take on data gathering and analytical responsibilities.
• Other solutions involve the use of peer-to- peer
communications, where devices identify and authenticate each other directly and
exchange information without the involvement of a broker. Networks will be
created in meshes with no single point of failure.
• This model will have its own set of challenges,
especially from a security perspective, but these challenges can be met with
some of the emerging IoT technologies such as #Blockchain.
• IoT is growing in many different directions, with
many different technologies competing to become the standard. This will cause
difficulties and require the deployment of extra hardware and software when
connecting devices.
• Other compatibility issues stem from non- unified
cloud services, lack of standardized #M2M protocols and diversities in firmware
and operating systems among IoT devices.
• Some of these technologies will eventually become
obsolete in the next few years, effectively rendering the devices implementing
them useless.
• This is especially important, since in contrast
to generic computing devices which have a lifespan of a few years, IoT
appliances (such as smart fridges or TVs) tend to remain in service for much
longer, and should be able to function even if their manufacturer goes out of
service.
Standards • Technology standards which include
network protocols, communication protocols, and data-aggregation standards, are
the sum of all activities of handling, processing and storing the data collected
from the sensors. • This aggregation increases the value of data by increasing,
the scale, scope, and frequency of data available for analysis.
Challenges facing the adoptions of standards within
IoT
• Standard for handling unstructured data:
Structured data are stored in relational databases and queried through #SQL for
example. Unstructured data are stored in different types of #NoSQL databases
without a standard querying approach.
• Technical skills to leverage newer aggregation
tools: Companies that are keen on leveraging big-data tools often face a
shortage of talent to plan, execute, and maintain systems.
Intelligent Analysis & Actions • The last stage
in IoT implementation is extracting insights from data for analysis, where
analysis is driven by cognitive technologies and the accompanying models that
facilitate the use of cognitive technologies.
• Artificial intelligence (#AI) models can be
improved with large data sets that are more readily available than ever before,
thanks to the lower storage
• Growth in #crowdsourcing and open- source
analytics software: Cloud-based crowdsourcing services are leading to new
algorithms and improvements in existing ones at an unprecedented rate.
• Real-time data processing and analysis: Analytics
tools such as complex event processing (CEP) enable processing and analysis of
data on a real-time or a near real- time basis, driving timely decision making
and action
• Inaccurate analysis due to flaws in the data
and/or model: A lack of data or presence of outliers may lead to false
positives or false negatives, thus exposing various algorithmic limitations
• Legacy systems’ ability to analyze unstructured
data: Legacy systems are well suited to handle structured data; unfortunately,
most IoT/business interactions generate unstructured data
• Legacy systems’ ability to manage real- time
data: Traditional analytics software generally works on batch-oriented
processing, wherein all the data are loaded in a batch and then analyzed
• The second phase of this stage is intelligent
actions which can be expressed as #M2M and M2H interfaces for example with all
the advancement in UI and UX technologies.
• Lower machine prices
• Improved machine functionality
• Machines “influencing” human actions through
behavioral-science rationale
• Deep Learning tools
• Machines’ actions in unpredictable situations
• Information security and privacy
• Machine interoperability
• Mean-reverting human behaviors
• Slow adoption of new technologies
Business • The bottom line is a big motivation for
starting, investing in, and operating any business, without a sound and solid
business model for IoT we will have another bubble this model must satisfy all
the requirements for all kinds of e-commerce; vertical markets, horizontal
markets, and consumer markets.
• End-to-end solution providers operating in
vertical industries and delivering services using cloud analytics will be the
most successful at monetizing a large portion of the value in IoT.
• While many
IoT applications may attract modest revenue, some can attract more. For little
burden on the existing communication infrastructure, operators have the
potential to open up a significant source of new revenue using IoT
technologies.
IoT can be divided into 3 categories based on usage
and clients base:
1. Consumer IoT includes the connected devices such
as smart cars, phones, watches, laptops, connected appliances, and
entertainment systems.
2. Commercial IoT includes things like inventory
controls, device trackers, and connected medical devices.
3. Industrial IoT covers such things as connected
electric meters, waste water systems, flow gauges, pipeline monitors,
manufacturing robots, and other types of connected industrial devices and
systems.
• Clearly, it is important to understand the value
chain and business model for the IoT applications for each category of IoT.
Society • Understanding IoT from the customers and
regulators prospective is not an easy task for the following reasons:
• Customer demands and requirements change
constantly.
• New uses for devices—as well as new
devices—sprout and grows at breakneck speeds.
• Inventing
and reintegrating must-have features and capabilities are expensive and take
time and resources.
• The uses for Internet of Things technology are
expanding and changing—often in uncharted waters.
• Consumer Confidence: Each of these problems could
put a dent in consumers' desire to purchase connected products, which would
prevent the IoT from fulfilling its true potential.
• Lack of understanding or education by consumers
of best practices for IoT devices security to help in improving privacy, for
example change default passwords of IoT devices.
Privacy • The IoT creates unique challenges to
privacy, many that go beyond the data privacy issues that currently exist. Much
of this stems from integrating devices into our environments without us
consciously using them.
• This is becoming more prevalent in consumer
devices, such as tracking devices for phones and cars as well as smart
televisions.
