DevOps Training Classes in Lakewood, Washington

Learn DevOps in Lakewood, Washington and surrounding areas via our hands-on, expert led courses. All of our classes either are offered on an onsite, online or public instructor led basis. Here is a list of our current DevOps related training offerings in Lakewood, Washington: DevOps Training

We offer private customized training for groups of 3 or more attendees.
Lakewood  Upcoming Instructor Led Online and Public DevOps Training Classes
Docker Training/Class 29 April, 2024 - 1 May, 2024 $1690
HSG Training Center instructor led online
Lakewood, Washington 98498
Hartmann Software Group Training Registration
DOCKER WITH KUBERNETES ADMINISTRATION Training/Class 6 May, 2024 - 10 May, 2024 $2490
HSG Training Center instructor led online
Lakewood, Washington 98498
Hartmann Software Group Training Registration
RED HAT SATELLITE V6 (FOREMAN/KATELLO) ADMINISTRATION Training/Class 1 April, 2024 - 4 April, 2024 $2590
HSG Training Center instructor led online
Lakewood, Washington 98498
Hartmann Software Group Training Registration

DevOps Training Catalog

subcategories

cost: $ 470length: 1 day(s)
cost: $ 2800length: 5 day(s)
cost: $ 790length: 1 day(s)
cost: $ 1690length: 3 day(s)
cost: $ 1190length: 2 day(s)
cost: $ 1690length: 3 day(s)
cost: $ 1690length: 3 day(s)
cost: $ 1690length: 3 day(s)
cost: $ 1090length: 2 day(s)
cost: $ 1090length: 2 day(s)

Linux Unix Classes

cost: $ 1990length: 3 day(s)
cost: $ 2490length: 5 day(s)
cost: $ 1290length: 3 day(s)
cost: $ 1890length: 4 day(s)
cost: $ 2490length: 4 day(s)

Course Directory [training on all levels]

Upcoming Classes
Gain insight and ideas from students with different perspectives and experiences.

Blog Entries publications that: entertain, make you think, offer insight

What are some of the software development headaches associated with iPhone vs Android development?

The Boss (hereafter referred to as TB), handed me this research assignment. Hey, I finally got a little bit of one ups man ship on TB.

This is a significant moment in my life. Like me, TB isn't really human. I know because neither of us seem to indulge in that luxury known as sleep. That makes it extremely difficult to have any sort of 'gotcha'. I'm dancing. I got one.

In the warp speed development cycles we are now facing, TB must have gone to sleep, which in human terms is known as a wink. (About a 40th of the second).
18 June 2012 Monday, 3:30 PM (15:30 HRS) UTC -8, in Los Angeles Microsoft is making a major tablet announcement, revealing its own hardware that is tablet-based. Do not be surprised if it entails a Hollywood Inc. focus.

Writing Python in Java syntax is possible with a semi-automatic tool. Programming code translation tools pick up about 75% of dynamically typed language. Conversion of Python to a statically typed language like Java requires some manual translation. The modern Java IDE can be used to infer local variable type definitions for each class attribute and local variable.


Translation of Syntax
Both Python and Java are OO imperative languages with sizable syntax constructs. Python is larger, and more competent for functional programming concepts. Using the source translator tool, parsing of the original Python source language will allow for construction of an Abstract Source Tree (AST), followed by conversion of the AST to Java.

Python will parse itself. This capability is exhibited in the ast module, which includes skeleton classes. The latter can be expanded to parse and source each node of an AST. Extension of the ast.NodeVisitor class enables python syntax constructs to be customized using translate.py and parser.py coding structure.

The Concrete Syntax Tree (CST) for Java is based on visit to the AST. Java string templates can be output at AST nodes with visitor.py code. Comment blocks are not retained by the Python ast Parser. Conversion of Python to multi-line string constructs with the translator reduces time to script.


Scripting Python Type Inference in Java
Programmers using Python source know that the language does not contain type information. The fact that Python is a dynamic type language means object type is determined at run time. Python is also not enforced at compile time, as the source is not specified. Runtime type information of an object can be determined by inspecting the __class__.__name__ attribute.

Python’s inspect module is used for constructing profilers and debugging.
Implementation of def traceit (frame, event, arg) method in Python, and connecting it to the interpreter with sys.settrace (traceit) allows for integration of multiple events during application runtime.

Method call events prompt inspect and indexing of runtime type. Inspection of all method arguments can be conducted. By running the application profiler and exercising the code, captured trace files for each source file can be modified with the translator. Generating method syntax can be done with the translator by search and addition of type information. Results in set or returned variables disseminate the dynamic code in static taxonomy.

The final step in the Python to Java scrip integration is to administer unsupported concepts such as value object creation. There is also the task of porting library client code, for reproduction in Java equivalents. Java API stubs can be created to account for Python APIs. Once converted to Java the final clean-up of the script is far easier.

 

Related:

 What Are The 10 Most Famous Software Programs Written in Python?

Python, a Zen Poem

data dictionary workThe mainstay of a corporation is the data that it possesses. By data, I mean its customer base, information about the use of its products, employee roles and responsibilities, the development and maintenance of its product lines, demographics of supporters and naysayers, financial records, projected sales ... It is in the organization of this data that advancements to the bottom line are often realized i.e. the nuggets of gold are found. Defining what is important, properly cataloging the information, developing a comprehensive protocol to access and update this information and discerning how this data fits into the corporate venacular is basis of this data organization and may be the difference between moving ahead of the competition or being the one to fall behind.

Whenever we attempt to develop an Enterprise Rule Application, we must begin by harvesting the data upon which those rules are built. This is by no means an easy feat as it requires a thorough understanding of the business, industry, the players and their respective roles and the intent of the application. Depending upon the scope of this undertaking, it is almost always safe to say that no one individual is completely knowledgeable to all facets needed to comprise the entire application.data dictionary

The intial stage of this endeavor is, obviously, to decide upon the intent of the application. This requires knowledge of what is essential, what is an add-on and which of all these requirements/options can be successfully implemented in the allotted period of time. The importance of this stage cannot be stressed enough; if the vision/goal cannot be articulated in a manner that all can understand, the knowledge tap will be opened to become the money drain. Different departments may compete for the same financial resources; management may be jockeying for their day in the sun; consulting corporations, eager to win the bid, may exaggerate their level of competency. These types of endeavors require those special skills of an individual or a team of very competent members to be/have a software architect, subject matter expert and business analyst.

Once the decision has been made and the application development stages have been defined, the next step is to determine which software development tools to employ. For the sake of this article, we will assume that the team has chosen an object oriented language such as Java and a variety of J EE components, a relationsional database and a vendor specific BRMS such as Blaze Advisor. Now, onto the point of this article.

Let’s face it, fad or not, companies are starting to ask themselves how they could possibly use machine learning and AI technologies in their organization. Many are being lured by the promise of profits by discovering winning patterns with algorithms that will enable solid predictions… The reality is that most technology and business professionals do not have sufficient understanding of how machine learning works and where it can be applied.  For a lot of firms, the focus still tends to be on small-scale changes instead of focusing on what really matters…tackling their approach to machine learning.

In the recent Wall Street Journal article, Machine Learning at Scale Remains Elusive for Many Firms, Steven Norton captures interesting comments from the industry’s data science experts. In the article, he quotes panelists from the MIT Digital Economy Conference in NYC, on businesses current practices with AI and machine learning. All agree on the fact that, for all the talk of Machine Learning and AI’s potential in the enterprise, many firms aren’t yet equipped to take advantage of it fully.

Panelist,  Michael Chui, partner at McKinsey Global Institute states that “If a company just mechanically says OK, I’ll automate this little activity here and this little activity there, rather than re-thinking the entire process and how it can be enabled by technology, they usually get very little value out of it. “Few companies have deployed these technologies in a core business process or at scale.”

Panelist, Hilary Mason, general manager at Cloudera Inc., had this to say, “With very few exceptions, every company we work with wants to start with a cost-savings application of automation.” “Most organizations are not set up to do this well.”

Tech Life in Washington

Not only is Washington a major player in the manufacturing industries such as aircraft and missiles, shipbuilding, lumber, food processing, metals and metal products, chemicals, and machinery, it?s the home of Microsoft Corporation and Bill Gates, chairman and former CEO of Microsoft. Other Washington state billionaires include Paul Allen (Microsoft), Steve Ballmer (Microsoft), Jeff Bezos (Amazon), Craig McCaw (McCaw Cellular Communications), James Jannard (Oakley), Howard Schultz (Starbucks), and Charles Simonyi (Microsoft).
Whoever ceases to be a student has never been a student. George Iles
other Learning Options
Software developers near Lakewood have ample opportunities to meet like minded techie individuals, collaborate and expend their career choices by participating in Meet-Up Groups. The following is a list of Technology Groups in the area.
Fortune 500 and 1000 companies in Washington that offer opportunities for DevOps developers
Company Name City Industry Secondary Industry
Symetra Financial Corporation Bellevue Financial Services Insurance and Risk Management
Alaska Air Group, Inc. Seattle Travel, Recreation and Leisure Passenger Airlines
Expedia, Inc. Bellevue Travel, Recreation and Leisure Travel Agents & Services
Itron, Inc. Liberty Lake Computers and Electronics Instruments and Controls
PACCAR Inc. Bellevue Manufacturing Automobiles, Boats and Motor Vehicles
Puget Sound Energy Inc Bellevue Energy and Utilities Gas and Electric Utilities
Expeditors International of Washington, Inc. Seattle Transportation and Storage Freight Hauling (Rail and Truck)
Costco Wholesale Corporation Issaquah Retail Grocery and Specialty Food Stores
Starbucks Corporation Seattle Retail Restaurants and Bars
Nordstrom, Inc. Seattle Retail Department Stores
Weyerhaeuser Company Federal Way Manufacturing Paper and Paper Products
Microsoft Corporation Redmond Software and Internet Software
Amazon.com, Inc. Seattle Retail Sporting Goods, Hobby, Book, and Music Stores

training details locations, tags and why hsg

the hartmann software group advantage
A successful career as a software developer or other IT professional requires a solid understanding of software development processes, design patterns, enterprise application architectures, web services, security, networking and much more. The progression from novice to expert can be a daunting endeavor; this is especially true when traversing the learning curve without expert guidance. A common experience is that too much time and money is wasted on a career plan or application due to misinformation.

The Hartmann Software Group understands these issues and addresses them and others during any training engagement. Although no IT educational institution can guarantee career or application development success, HSG can get you closer to your goals at a far faster rate than self paced learning and, arguably, than the competition. Here are the reasons why we are so successful at teaching:

  • Learn from the experts.
    1. We have provided software development and other IT related training to many major corporations in Washington since 2002.
    2. Our educators have years of consulting and training experience; moreover, we require each trainer to have cross-discipline expertise i.e. be Java and .NET experts so that you get a broad understanding of how industry wide experts work and think.
  • Discover tips and tricks about DevOps programming
  • Get your questions answered by easy to follow, organized DevOps experts
  • Get up to speed with vital DevOps programming tools
  • Save on travel expenses by learning right from your desk or home office. Enroll in an online instructor led class. Nearly all of our classes are offered in this way.
  • Prepare to hit the ground running for a new job or a new position
  • See the big picture and have the instructor fill in the gaps
  • We teach with sophisticated learning tools and provide excellent supporting course material
  • Books and course material are provided in advance
  • Get a book of your choice from the HSG Store as a gift from us when you register for a class
  • Gain a lot of practical skills in a short amount of time
  • We teach what we know…software
  • We care…
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Interesting Reads Take a class with us and receive a book of your choosing for 50% off MSRP.