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Books > Computing & IT > Computer software packages > Other software packages > Enterprise software
Apply cloud design patterns to overcome real-world challenges by
building scalable, secure, highly available, and cost-effective
solutions Key Features Apply AWS Well-Architected Framework
concepts to common real-world use cases Understand how to select
AWS patterns and architectures that are best suited to your needs
Ensure the security and stability of a solution without impacting
cost or performance Book DescriptionOne of the most popular cloud
platforms in the world, Amazon Web Services (AWS) offers hundreds
of services with thousands of features to help you build scalable
cloud solutions; however, it can be overwhelming to navigate the
vast number of services and decide which ones best suit your
requirements. Whether you are an application architect, enterprise
architect, developer, or operations engineer, this book will take
you through AWS architectural patterns and guide you in selecting
the most appropriate services for your projects. AWS for Solutions
Architects is a comprehensive guide that covers the essential
concepts that you need to know for designing well-architected AWS
solutions that solve the challenges organizations face daily.
You'll get to grips with AWS architectural principles and patterns
by implementing best practices and recommended techniques for
real-world use cases. The book will show you how to enhance
operational efficiency, security, reliability, performance, and
cost-effectiveness using real-world examples. By the end of this
AWS book, you'll have gained a clear understanding of how to design
AWS architectures using the most appropriate services to meet your
organization's technological and business requirements. What you
will learn Rationalize the selection of AWS as the right cloud
provider for your organization Choose the most appropriate service
from AWS for a particular use case or project Implement change and
operations management Find out the right resource type and size to
balance performance and efficiency Discover how to mitigate risk
and enforce security, authentication, and authorization Identify
common business scenarios and select the right reference
architectures for them Who this book is forThis book is for
application and enterprise architects, developers, and operations
engineers who want to become well-versed with AWS architectural
patterns, best practices, and advanced techniques to build
scalable, secure, highly available, and cost-effective solutions in
the cloud. Although existing AWS users will find this book most
useful, it will also help potential users understand how leveraging
AWS can benefit their organization.
Quickly build and deploy machine learning models without managing
infrastructure, and improve productivity using Amazon SageMaker's
capabilities such as Amazon SageMaker Studio, Autopilot,
Experiments, Debugger, and Model Monitor Key Features Build, train,
and deploy machine learning models quickly using Amazon SageMaker
Analyze, detect, and receive alerts relating to various business
problems using machine learning algorithms and techniques Improve
productivity by training and fine-tuning machine learning models in
production Book DescriptionAmazon SageMaker enables you to quickly
build, train, and deploy machine learning (ML) models at scale,
without managing any infrastructure. It helps you focus on the ML
problem at hand and deploy high-quality models by removing the
heavy lifting typically involved in each step of the ML process.
This book is a comprehensive guide for data scientists and ML
developers who want to learn the ins and outs of Amazon SageMaker.
You'll understand how to use various modules of SageMaker as a
single toolset to solve the challenges faced in ML. As you
progress, you'll cover features such as AutoML, built-in algorithms
and frameworks, and the option for writing your own code and
algorithms to build ML models. Later, the book will show you how to
integrate Amazon SageMaker with popular deep learning libraries
such as TensorFlow and PyTorch to increase the capabilities of
existing models. You'll also learn to get the models to production
faster with minimum effort and at a lower cost. Finally, you'll
explore how to use Amazon SageMaker Debugger to analyze, detect,
and highlight problems to understand the current model state and
improve model accuracy. By the end of this Amazon book, you'll be
able to use Amazon SageMaker on the full spectrum of ML workflows,
from experimentation, training, and monitoring to scaling,
deployment, and automation. What you will learn Create and automate
end-to-end machine learning workflows on Amazon Web Services (AWS)
Become well-versed with data annotation and preparation techniques
Use AutoML features to build and train machine learning models with
AutoPilot Create models using built-in algorithms and frameworks
and your own code Train computer vision and NLP models using
real-world examples Cover training techniques for scaling, model
optimization, model debugging, and cost optimization Automate
deployment tasks in a variety of configurations using SDK and
several automation tools Who this book is forThis book is for
software engineers, machine learning developers, data scientists,
and AWS users who are new to using Amazon SageMaker and want to
build high-quality machine learning models without worrying about
infrastructure. Knowledge of AWS basics is required to grasp the
concepts covered in this book more effectively. Some understanding
of machine learning concepts and the Python programming language
will also be beneficial.
Nature-Inspired Computing Paradigms in Systems: Reliability,
Availability, Maintainability, Safety and Cost (RAMS+C) and
Prognostics and Health Management (PHM) covers several areas that
include bioinspired techniques and optimization approaches for
system dependability. The book addresses the issue of integration
and interaction of the bioinspired techniques in system
dependability computing so that intelligent decisions, design, and
architectures can be supported. It brings together these emerging
areas under the umbrella of bio- and nature-inspired computational
intelligence. The primary audience of this book includes experts
and developers who want to deepen their understanding of
bioinspired computing in basic theory, algorithms, and
applications. The book is also intended to be used as a textbook
for masters and doctoral students who want to enhance their
knowledge and understanding of the role of bioinspired techniques
in system dependability.
Design and build high-performance, secure, and scalable Salesforce
solutions to meet business demands and gain practical experience
using real-world scenarios by creating engaging end-to-end solution
presentations Key Features Learn common integration, data
migration, and security patterns for designing scalable and
reliable solutions on the Salesforce Lightning platform Build an
end-to-end delivery framework pipeline for delivering successful
projects within specified timelines Gain access to an exclusive
book club of skilled Salesforce professionals, to discuss ideas,
best practices, and share experiences of designing modern solutions
using Salesforce Book DescriptionSalesforce Certified Technical
Architect (CTA) is the ultimate certification to validate your
knowledge and skills when it comes to designing and building
high-performance technical solutions on the Salesforce platform.
The CTA certificate is granted after successfully passing the CTA
review board exam, which tests your platform expertise and soft
skills for communicating your solutions and vision. You'll start
with the core concepts that every architect should master,
including data lifecycle, integration, and security, and build your
aptitude for creating high-level technical solutions. Using
real-world examples, you'll explore essential topics such as
selecting systems or components for your solutions, designing
scalable and secure Salesforce architecture, and planning the
development lifecycle and deployments. Finally, you'll work on two
full mock scenarios that simulate the review board exam, helping
you learn how to identify requirements, create a draft solution,
and combine all the elements together to create an engaging story
to present in front of the board or to a client in real life. By
the end of this Salesforce book, you'll have gained the knowledge
and skills required to pass the review board exam and implement
architectural best practices and strategies in your day-to-day
work. What you will learn Explore data lifecycle management and
apply it effectively in the Salesforce ecosystem Design appropriate
enterprise integration interfaces to build your connected solution
Understand the essential concepts of identity and access management
Develop scalable Salesforce data and system architecture Design the
project environment and release strategy for your solution
Articulate the benefits, limitations, and design considerations
relating to your solution Discover tips, tricks, and strategies to
prepare for the Salesforce CTA review board exam Who this book is
forThis book is for Salesforce architects who want to become
certified technical architects by learning how to design secure and
scalable technical solutions for their organizations. A solid
understanding of the Salesforce platform is required, ideally
combined with 3 to 5 years of practical experience as an
application architect, system architect, enterprise architect, or
solution architect.
Explore a wide range of low-code tools in the Salesforce platform
for building customized CRM applications without writing any code
Key Features Create apps with a rich user experience without paying
for costly developers Leverage Salesforce Lightning Platform's
declarative features to build professional-grade applications
Improve productivity with business process automation using
Workflow, Process Builder, and Flow Book DescriptionLow-code
platforms allow users to focus on business logic to create
solutions without getting trapped in programming complexities.
Thanks to its powerful features for designing, developing, and
deploying apps without having to hand-code, Salesforce is at the
forefront of the low-code development revolution. This book will
guide you in building creative applications for solving your
business problems using the declarative framework provided by
Salesforce. You'll start by learning how to design your business
data model with custom objects, fields, formulas, and validation
rules, all secured by the Salesforce security model. You'll then
explore tools such as Workflow, Process Builder, Lightning Flow,
and Actions that will help you to automate your business processes
with ease. This book also shows you how to use Lightning App
Builder to build personalized UIs for your Salesforce applications,
explains the value of creating community pages for your
organization, and teaches you how to customize them with Experience
Builder. Finally, you'll work with the sandbox model, deploy your
solutions, and deliver an effective release management strategy. By
the end of this Salesforce book, you'll be ready to customize
Salesforce CRM to meet your business requirements by creating
unique solutions without writing a single line of code. What you
will learn Get to grips with the fundamentals of data modeling to
enhance data quality Deliver dynamic configuration capabilities
using custom settings and metadata types Secure your data by
implementing the Salesforce security model Customize Salesforce
applications with Lightning App Builder Create impressive pages for
your community using Experience Builder Use Data Loader to import
and export data without writing any code Embrace the Salesforce
Ohana culture to share knowledge and learn from the global
Salesforce community Who this book is forIf you are a citizen
developer, business analyst, Salesforce administrator, or anyone
interested in developing applications or solutions for business
problems but lack technical knowledge, this book is for you. No
prior programming experience is required.
Learn how to extend the capabilities of Power Apps by building code
components using Power Apps Component Framework Key Features
Understand how to extend Power Apps' capabilities Enhance your
skills with the help of practical code components used throughout
the book Overcome common challenges, avoid pitfalls, and improve
your code Book DescriptionPower Apps Component Framework is used by
professional developers to extend the capabilities of model-driven
and canvas apps. Extending Microsoft Power Apps with Power Apps
Component Framework will take you through the basic as well as
advanced topics using practical examples. The book starts by
helping you understand the fundamentals of the framework, its
lifecycle, and the tools that you'll use to build code components
using best practices and file management guidelines. You'll then
learn how to extend Power Apps step by step and apply the
principles and concepts covered in the book to build code
components for field type attributes. The book covers different
ways of debugging code components and guides you through the
process of building code components for datasets. You'll also
explore the functions and methods provided by the framework to
enhance your controls using powerful sets of libraries and
extensions. As you advance, you'll get to grips with creating and
managing authentication profiles, discover different ways of
deploying code components, and configure code components in
model-driven and canvas apps. Finally, you'll learn some of the
important features of the framework and learn modern web
development practices. By the end of this Power Apps book, you'll
be able to build, debug, enrich, and deploy code components
confidently. What you will learn Understand the fundamentals of
Power Apps Component Framework Explore the tools that make it easy
to build code components Build code components for both a field and
a dataset Debug using test harness and Fiddler Implement caching
techniques Find out how to work with the Dataverse Web API Build
code components using React and Fluent UI controls Discover
different deployment strategies Who this book is forThis book is
for developers who are looking to build advanced skills for
extending the capabilities of Power Apps. Basic knowledge of Power
Apps and web development is necessary to get started with this
book.
Secure your container environment against cyberattacks and deliver
robust deployments with this practical guide Key Features Explore a
variety of Kubernetes components that help you to prevent
cyberattacks Perform effective resource management and monitoring
with Prometheus and built-in Kubernetes tools Learn techniques to
prevent attackers from compromising applications and accessing
resources for crypto-coin mining Book DescriptionKubernetes is an
open source orchestration platform for managing containerized
applications. Despite widespread adoption of the technology, DevOps
engineers might be unaware of the pitfalls of containerized
environments. With this comprehensive book, you'll learn how to use
the different security integrations available on the Kubernetes
platform to safeguard your deployments in a variety of scenarios.
Learn Kubernetes Security starts by taking you through the
Kubernetes architecture and the networking model. You'll then learn
about the Kubernetes threat model and get to grips with securing
clusters. Throughout the book, you'll cover various security
aspects such as authentication, authorization, image scanning, and
resource monitoring. As you advance, you'll learn about securing
cluster components (the kube-apiserver, CoreDNS, and kubelet) and
pods (hardening image, security context, and PodSecurityPolicy).
With the help of hands-on examples, you'll also learn how to use
open source tools such as Anchore, Prometheus, OPA, and Falco to
protect your deployments. By the end of this Kubernetes book,
you'll have gained a solid understanding of container security and
be able to protect your clusters from cyberattacks and mitigate
cybersecurity threats. What you will learn Understand the basics of
Kubernetes architecture and networking Gain insights into different
security integrations provided by the Kubernetes platform Delve
into Kubernetes' threat modeling and security domains Explore
different security configurations from a variety of practical
examples Get to grips with using and deploying open source tools to
protect your deployments Discover techniques to mitigate or prevent
known Kubernetes hacks Who this book is forThis book is for
security consultants, cloud administrators, system administrators,
and DevOps engineers interested in securing their container
deployments. If you're looking to secure your Kubernetes clusters
and cloud-based deployments, you'll find this book useful. A basic
understanding of cloud computing and containerization is necessary
to make the most of this book.
Learn the foundations of blockchain technology - its core concepts
and algorithmic solutions across cryptography, peer-to-peer
technology, and game theory. Key Features Learn the core concepts
and foundations of the blockchain and cryptocurrencies Understand
the protocols and algorithms behind decentralized applications
Master how to architect, build, and optimize blockchain
applications Book DescriptionBlockchain technology is a combination
of three popular concepts: cryptography, peer-to-peer networking,
and game theory. This book is for anyone who wants to dive into
blockchain from first principles and learn how decentralized
applications and cryptocurrencies really work. This book begins
with an overview of blockchain technology, including key
definitions, its purposes and characteristics, so you can assess
the full potential of blockchain. All essential aspects of
cryptography are then presented, as the backbone of blockchain. For
readers who want to study the underlying algorithms of blockchain,
you'll see Python implementations throughout. You'll then learn how
blockchain architecture can create decentralized applications.
You'll see how blockchain achieves decentralization through
peer-to-peer networking, and how a simple blockchain can be built
in a P2P network. You'll learn how these elements can implement a
cryptocurrency such as Bitcoin, and the wider applications of
blockchain work through smart contracts. Blockchain optimization
techniques, and blockchain security strategies are then presented.
To complete this foundation, we consider blockchain applications in
the financial and non-financial sectors, and also analyze the
future of blockchain. A study of blockchain use cases includes
supply chains, payment systems, crowdfunding, and DAOs, which
rounds out your foundation in blockchain technology. What you will
learn The core concepts and technical foundations of blockchain The
algorithmic principles and solutions that make up blockchain and
cryptocurrencies Blockchain cryptography explained in detail How to
realize blockchain projects with hands-on Python code How to
architect the blockchain and blockchain applications Decentralized
application development with MultiChain, NEO, and Ethereum
Optimizing and enhancing blockchain performance and security
Classical blockchain use cases and how to implement them Who this
book is forThis book is for anyone who wants to dive into
blockchain technology from first principles and build a
foundational knowledge of blockchain. Familiarity with Python will
be helpful if you want to follow how the blockchain protocols are
implemented. For readers who are blockchain application developers,
most of the applications used in this book can be executed on any
platform.
Build powerful data analytics applications with this business
intelligence tool and overcome all your business challenges Key
Features Master time-saving techniques and make your QlikView
development more efficient Perform geographical analysis and
sentiment analysis in your QlikView applications Explore advanced
QlikView techniques, tips, and tricks to deliver complex business
requirements Book DescriptionQlikView is one of the most flexible
and powerful business intelligence platforms around, and if you
want to transform data into insights, it is one of the best options
you have at hand. Use this Learning Path, to explore the many
features of QlikView to realize the potential of your data and
present it as impactful and engaging visualizations. Each chapter
in this Learning Path starts with an understanding of a business
requirement and its associated data model and then helps you create
insightful analysis and data visualizations around it. You will
look at problems that you might encounter while visualizing complex
data insights using QlikView, and learn how to troubleshoot these
and other not-so-common errors. This Learning Path contains
real-world examples from a variety of business domains, such as
sales, finance, marketing, and human resources. With all the
knowledge that you gain from this Learning Path, you will have all
the experience you need to implement your next QlikView project
like a pro. This Learning Path includes content from the following
Packt products: QlikView for Developers by Miguel Angel Garcia,
Barry Harmsen Mastering QlikView by Stephen Redmond Mastering
QlikView Data Visualization by Karl Pover What you will learn
Deliver common business requirements using advanced techniques Load
data from disparate sources to build associative data models
Understand when to apply more advanced data visualization Utilize
the built-in aggregation functions for complex calculations Build a
data architecture that supports scalable QlikView deployments
Troubleshoot common data visualization errors in QlikView Protect
your QlikView applications and data Who this book is forThis
Learning Path is designed for developers who want to go beyond
their technical knowledge of QlikView and understand how to create
analysis and data visualizations that solve real business needs. To
grasp the concepts explained in this Learning Path, you should have
a basic understanding of the common QlikView functions and some
hands-on experience with the tool.
Learn a modern approach to data analysis using Python to harness
the power of programming and AI across your data. Detailed case
studies bring this modern approach to life across visual data,
social media, graph algorithms, and time series analysis. Key
Features Bridge your data analysis with the power of programming,
complex algorithms, and AI Use Python and its extensive libraries
to power your way to new levels of data insight Work with AI
algorithms, TensorFlow, graph algorithms, NLP, and financial time
series Explore this modern approach across with key industry case
studies and hands-on projects Book DescriptionData Analysis with
Python offers a modern approach to data analysis so that you can
work with the latest and most powerful Python tools, AI techniques,
and open source libraries. Industry expert David Taieb shows you
how to bridge data science with the power of programming and
algorithms in Python. You'll be working with complex algorithms,
and cutting-edge AI in your data analysis. Learn how to analyze
data with hands-on examples using Python-based tools and Jupyter
Notebook. You'll find the right balance of theory and practice,
with extensive code files that you can integrate right into your
own data projects. Explore the power of this approach to data
analysis by then working with it across key industry case studies.
Four fascinating and full projects connect you to the most critical
data analysis challenges you're likely to meet in today. The first
of these is an image recognition application with TensorFlow -
embracing the importance today of AI in your data analysis. The
second industry project analyses social media trends, exploring big
data issues and AI approaches to natural language processing. The
third case study is a financial portfolio analysis application that
engages you with time series analysis - pivotal to many data
science applications today. The fourth industry use case dives you
into graph algorithms and the power of programming in modern data
science. You'll wrap up with a thoughtful look at the future of
data science and how it will harness the power of algorithms and
artificial intelligence. What you will learn A new toolset that has
been carefully crafted to meet for your data analysis challenges
Full and detailed case studies of the toolset across several of
today's key industry contexts Become super productive with a new
toolset across Python and Jupyter Notebook Look into the future of
data science and which directions to develop your skills next Who
this book is forThis book is for developers wanting to bridge the
gap between them and data scientists. Introducing PixieDust from
its creator, the book is a great desk companion for the
accomplished Data Scientist. Some fluency in data interpretation
and visualization is assumed. It will be helpful to have some
knowledge of Python, using Python libraries, and some proficiency
in web development.
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