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Table of Contents 

1 Introduction 2 Processor 3 Physical Memory

3.1 \Memory\Available Bytes 3.2 \Process(_Total)\Working Set 3.3 \Memory\Cache Bytes 3.4 \Memory\Pool Nonpaged Bytes 

4 Paging

4.1 \Memory\Pages/sec 4.2 \Memory\Page Reads/sec 4.3 \Memory\Page Writes/sec 4.4 \Paging File(_total)\% Usage 

5 CPU/System Stats

5.1 \Processor(_total)\% Privileged Time 5.2 \Processor(_total)\% User Time 5.3 \System\Processor Queue Length 

6 Disk Throughput

6.1 \PhysicalDisk(*)\Disk Read Bytes/sec 6.2 \PhysicalDisk(*)\Disk Write Bytes/sec 

7 Disk Queue Length

7.1 \PhysicalDisk(*)\Avg. Disk Queue Length 7.2 \PhysicalDisk(*)\Current Disk Queue Length 

8 Disk Latency and Fragmentation

8.1 \PhysicalDisk(*)\Avg. Disk sec/Read 8.2 \PhysicalDisk(*)\Avg. Disk sec/Write 8.3 \PhysicalDisk(*)\Split IO/sec 

9 Network Throughput

9.1 \Network Interface(*)\Bytes Received/sec 9.2 \Network Interface(*)\Bytes Sent/sec 

10 IIS / Webservice Counters

10.1 \Web Service(_Total)\Current Connections 10.2 \Web Service(_Total)\Current Anonymous Users 10.3 \Web Service(_Total)\Current NonAnonymous Users 10.4 \Web Service(_Total)\Get Requests/sec 10.5 \Web Service(_Total)\Put Requests/sec 10.6 \Web Service(_Total)\Post Requests/sec 

11 SQL Server Usage Stats

11.1 \SQLServer:General Statistics\User Connections 11.2 \SQLServer:SQL Statistics\SQL Compilations/sec 11.3 \SQLServer:SQL Statistics\SQL Re-Compilations/sec 11.4 \SQLServer:SQL Statistics\Batch Requests/sec 11.5 \SQLServer:Databases(_total)\Log Flushes/sec 11.6 \SQLServer:Buffer Manager\Lazy Writes/sec 11.7 \SQLServer:Access Methods\Page Splits/sec 

12 SQL Server Memory

12.1 \SQLServer:Buffer Manager\Buffer cache hit ratio 12.2 \SQLServer:Memory Manager\SQL Cache Memory (KB) 12.3 \SQLServer:Memory Manager\Total Server Memory (KB) 12.4 \SQLServer:Memory Manager\Target Server Memory (KB) 

13 SQL Server Stats

13.1 \SQLServer:General Statistics\Processes Blocked 13.2 \SQLServer:Locks(_total)\Number of DeadLocks/sec 13.3 \SQLServer:Locks(_total)\Average Wait Time (ms) 13.4 \SQLServer:Latches\Average Latch Wait Time (ms) 

14 Individual Process Statistics

lessons are:

agile data models are just barely good enough.

Agile developers solve today's problem today and trust that they can solve tomorrow's problem tomorrow.

Agile data modeling is both evolutionary and collaborative.

Your standards should be straightforward, simple, and sufficiently described so that the team can learn and then follow them. Critical data modeling standards focus on naming conventions and conventions for writing stored procedures.

Requirements change over time, so embrace this concept and adopt techniques which allow you to react effectively.

Shared whiteboard space which is owned by the team can significant enhance communication and productivity. Figure 9 -. sketching was the most common primary approach to modeling.

Become a generalizing specialist.

Data migration is an important part of implement most structural database refactorings, and database refactoring is a critical activity which supports evolutionary database development 

Save time and increase productivity:   collaboration software like Microsoft Teams is a chat-based workspace ..  Threaded conversations (some stats:  employees can save about one hour per day after three years of implementation ** 2015, IDC ) ... Yammer - cross-company discussions. Employees can also crowd source ideas and share best practices

Lower costs and reduce complexity - hidden costs of the collaboration tools : licensing costs, service fees, IT resources, and employee downtime . Cost-saving by installing a set of collaboration tools from a single suite (stats  On average, total costs only reach $3.2 million over three years, resulting in a net present value (NPV) of $5.6 million. ** 2015, Forrester Research - Case study 2015 https://customers.microsoft.com/en-US/story/air-canada-soars-into-the-cloud-to-speed-processes-and)

Ensure end-to-end security and compliance -  You’ll know where your organization’s data is stored, which employees have access to it, and what methods of security and compliance are protecting it,

Scale at your own pace -  Implementing a new suite of tools can seem overwhelming.

1. Absorb information in new and more constructive ways.

2. Visualize relationships and patterns between operational and business activities.

3. Identify and act on emerging trends faster.

4. Manipulate and interact directly with data.

SNAT - A secure network address translation (SNAT) is a BIG-IP® Local Traffic ManagerTM

💡 Get an idea.

🖊 Write it down.- spec is a MUST

🔨 Build a prototype

💃 Enter into the dance between design and development until something comes out of it.

The Chi-square test is intended to test how likely it is that an observed distribution is due to chance. It is also called a "goodness of fit" statistic, because it measures how well the observed distribution of data fits with the distribution that is expected if the variables are independent. 

In general, the chi-square test statistic is of the form . If the computed test statistic is large, then the observed and expected values are not close and the model is a poor fit to the data.

A chi square (X2) statistic is used to investigate whether distributions of categorical variables differ from one another. Basically categorical variable yield data in the categories and numerical variables yield data in numerical form.

.. the high and unpredictable latency of EBS storage means that if

the active set of data stops fitting in memory,

or if a lot of transnational writes are required,

then performance takes a severe hit.