Monitoring HOWTOs

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This document discusses various tools that can help provide precise information about application health and anomalies, alert the right people, and enable automation. It describes how Sensu can query Nginx to check application status and meet SLAs. Anodot detects anomalies in metrics over time for backend services. Storm and Esper enable real-time anomaly detection from streaming data for frontend services. BigPanda provides a central place for alerts and change management. The goal is to quickly identify issues, see their potential causes, and ensure the right people are notified.

Precise information
Alert the right person
Automation

Service is alive
•
Is my application alive on the minimum
number required by my SLA?
•
2 out of 5 instances of my-app are not
responding to isAlive
•
my-app requires a minimum of 3
instances to meet the SLA

Alert
Sensu
Queries Nginx
Alert & SLA
ZooKeeper
Planned
Configuration
Service owner
Nginx
Service Load
Balancer
Is-alive

Alert
Sensu
Queries Nginx
Alert & SLA
ZooKeeper
Planned
Configuration
Service owner
Nginx
Service Load
Balancer
Is-alive
Alert the right
person
Precise
information
Automation

Service anomalies
BECKEND
•
Identify unhealthy KPIs per end-points
•
Abnormal increase in error rate for
class.method.get
•
Abnormal increase in performance or
decrease in RPM

Anomaly Alert
Anodot
Time series
anomaly
detection
Alerts & graphs
statsd
Stats
aggregation
Forwarding
metrics
JVM servers
Metrics library
metrics / 1m
Graphs

Service anomalies
FRONTEND
•
Users effected or not? How and where?
•
Success event count is low
•
Client error increased in Canada from
Chrome

Anomaly
Alert
STORM &
ESPER
Realtime
streaming
processing
Metrics / 1m
Client
flume
events Graphs
Client
flume
events
Anodot
Time series
anomaly
detection
Alerts &
graphs

Anomaly
Alert
STORM &
ESPER
Realtime
streaming
processing
Metrics / 1m
Client
flume
events Graphs
Client
flume
events
Precise
information
Alert the right
person
Automation
Anodot
Time series
anomaly
detection
Alerts &
graphs

Alerts management
•
Which active alerts do I have?
•
What changes could cause the problem?
•
I have 2 active alerts on MySql and 2
deployments in the last hour

Alert
BigPanda
Central alerts &
changes
Alerts &
Changes
Changes
Integrations
Deployments
Chef uploads
Alerts
integrations
NewRelic
Sensu
Nagios
PingDom Web UI

Feeling the pressure to keep up with customers and competitive demand in the market? Or the squeeze to deliver more business value at an increasingly fast pace? While the cloud, containerization, and microservices offer efficiency and scaling, many organizations aren’t quite prepared for that additional complexity of cloud native technologies and demands. AI, automation and monitoring facilitate the management of complex modern delivery platforms and help build resiliency into your deployment to enable better performance. In the context of software delivery pipelines.

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SAP License Audit Report SAP License Audit Report uses the the Transaction Audit Logs for capturing the transaction used by the SAP User in the SAP ECC System The SAP License Audit Report for user license manager analyzes all the users in the system and identifies the amount of time each user spends in the system. From this data, the tool recommends the right type of license classification for each user. The audit procedure also highlights the users who are not assigned to right license type. The tool models the reclassified user licenses as per the suggestions and highlights the cost savings for the company. The main benefits have come from what he calls 'software harvesting' -- recovering licenses from users who no longer use an application • SAP Audit Procedure for User License Saver Benefits: • Gives the company real time access to actual license usage • Identifies the most optimal license type • Easily changes user license type classification • SAP Audit procedure for User License manager will give the company cost savings.

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Netflix strives to provide an amazing experience to each member. To accomplish this, Netflix needs to maintain very high availability across our systems. However, at a certain scale, humans can no longer scale their ability to monitor the status of all systems, making it critical for Netflix to build tools and platforms that can automatically monitor their production environments and make intelligent real-time operational decisions to remedy the problems they identify. In this session, we discuss how Netflix uses data mining and machine learning techniques to automate decisions in real-time with the goal of supporting operational availability, reliability, and consistency. We review how we got to the current states, the lessons we learned, and the future of real-time analytics at Netflix. While Netflix's scale is larger than most other companies, we believe the approaches and technologies we discuss are highly relevant to other production environments, and audience members should come away with actionable ideas that are implementable in, and benefit, most other environments.

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In the age where applications reign supreme, your organizations must be agile in application performance management and app development in order to meet the market demands and stay competitive. Even with mature APM solutions, developer, test and operations teams are strained by operational complexity, accelerated release schedules, and big data challenges to quickly find the root cause of issues affecting end user experience. The power of advanced analytics and data science can help us make the most of the vast cache of APM data we collect and help our DevOps teams supercharge user experience. It’s time to take some of the load off of our humans and let technology make it easier to focus on meaningful changes in user, application and system behavior. Analytics are becoming a valuable component of APM solutions to redefine triage, improve application quality, and delight the end-user. In a webcast on August 7th, 2014, Ken Godskind, Chief blogger and Analyst, APMExaminer.com shared how the big data of APM can supercharge your DevOps transformation. Chris Kline, Senior Director, CA Technologies followed Ken and discussed how the Advanced Behavior Analytics capability of CA APM can assist in this journey. Ken and Chris used this slide set during the webcast which can be viewed at http://goo.gl/TZYEuq

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Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...

Dr.Costas Sachpazis

Terzaghi's soil bearing capacity theory, developed by Karl Terzaghi, is a fundamental principle in geotechnical engineering used to determine the bearing capacity of shallow foundations. This theory provides a method to calculate the ultimate bearing capacity of soil, which is the maximum load per unit area that the soil can support without undergoing shear failure. The Calculation HTML Code included.

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在线办理(ANU毕业证书)澳洲国立大学毕业证录取通知书一模一样

Sachpazis:Terzaghi Bearing Capacity Estimation in simple terms with Calculati...

Monitoring HOWTOs

1. Precise information Alert the right person Automation

2. Service is alive • Is my application alive on the minimum number required by my SLA? • 2 out of 5 instances of my-app are not responding to isAlive • my-app requires a minimum of 3 instances to meet the SLA

3. Alert Sensu Queries Nginx Alert & SLA ZooKeeper Planned Configuration Service owner Nginx Service Load Balancer Is-alive

4. Alert Sensu Queries Nginx Alert & SLA ZooKeeper Planned Configuration Service owner Nginx Service Load Balancer Is-alive Alert the right person Precise information Automation

5. Service anomalies BECKEND • Identify unhealthy KPIs per end-points • Abnormal increase in error rate for class.method.get • Abnormal increase in performance or decrease in RPM

6. Anomaly Alert Anodot Time series anomaly detection Alerts & graphs statsd Stats aggregation Forwarding metrics JVM servers Metrics library metrics / 1m Graphs

7. Anomaly Alert Anodot Time series anomaly detection Alerts & graphs statsd Stats aggregation Forwarding metrics JVM servers Metrics library metrics / 1m Graphs Precise information Alert the right person Automation

8. Service anomalies FRONTEND • Users effected or not? How and where? • Success event count is low • Client error increased in Canada from Chrome

9. Anomaly Alert STORM & ESPER Realtime streaming processing Metrics / 1m Client flume events Graphs Client flume events Anodot Time series anomaly detection Alerts & graphs

10. Anomaly Alert STORM & ESPER Realtime streaming processing Metrics / 1m Client flume events Graphs Client flume events Precise information Alert the right person Automation Anodot Time series anomaly detection Alerts & graphs

11. Alerts management • Which active alerts do I have? • What changes could cause the problem? • I have 2 active alerts on MySql and 2 deployments in the last hour

12. Alert BigPanda Central alerts & changes Alerts & Changes Changes Integrations Deployments Chef uploads Alerts integrations NewRelic Sensu Nagios PingDom Web UI

13. Alert BigPanda Central alerts & changes Alerts & Changes Changes Integrations Deployments Chef uploads Alerts integrations NewRelic Sensu Nagios PingDom Precise information Alert the right person Automation Precise information Web UI

14. Questions?

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