Compute
Elastic Cloud Server
Huawei Cloud Flexus
Bare Metal Server
Auto Scaling
Image Management Service
Dedicated Host
FunctionGraph
Cloud Phone Host
Huawei Cloud EulerOS
Networking
Virtual Private Cloud
Elastic IP
Elastic Load Balance
NAT Gateway
Direct Connect
Virtual Private Network
VPC Endpoint
Cloud Connect
Enterprise Router
Enterprise Switch
Global Accelerator
Management & Governance
Cloud Eye
Identity and Access Management
Cloud Trace Service
Resource Formation Service
Tag Management Service
Log Tank Service
Config
OneAccess
Resource Access Manager
Simple Message Notification
Application Performance Management
Application Operations Management
Organizations
Optimization Advisor
IAM Identity Center
Cloud Operations Center
Resource Governance Center
Migration
Server Migration Service
Object Storage Migration Service
Cloud Data Migration
Migration Center
Cloud Ecosystem
KooGallery
Partner Center
User Support
My Account
Billing Center
Cost Center
Resource Center
Enterprise Management
Service Tickets
HUAWEI CLOUD (International) FAQs
ICP Filing
Support Plans
My Credentials
Customer Operation Capabilities
Partner Support Plans
Professional Services
Analytics
MapReduce Service
Data Lake Insight
CloudTable Service
Cloud Search Service
Data Lake Visualization
Data Ingestion Service
GaussDB(DWS)
DataArts Studio
Data Lake Factory
DataArts Lake Formation
IoT
IoT Device Access
Others
Product Pricing Details
System Permissions
Console Quick Start
Common FAQs
Instructions for Associating with a HUAWEI CLOUD Partner
Message Center
Security & Compliance
Security Technologies and Applications
Web Application Firewall
Host Security Service
Cloud Firewall
SecMaster
Anti-DDoS Service
Data Encryption Workshop
Database Security Service
Cloud Bastion Host
Data Security Center
Cloud Certificate Manager
Edge Security
Situation Awareness
Managed Threat Detection
Blockchain
Blockchain Service
Web3 Node Engine Service
Media Services
Media Processing Center
Video On Demand
Live
SparkRTC
MetaStudio
Storage
Object Storage Service
Elastic Volume Service
Cloud Backup and Recovery
Storage Disaster Recovery Service
Scalable File Service Turbo
Scalable File Service
Volume Backup Service
Cloud Server Backup Service
Data Express Service
Dedicated Distributed Storage Service
Containers
Cloud Container Engine
SoftWare Repository for Container
Application Service Mesh
Ubiquitous Cloud Native Service
Cloud Container Instance
Databases
Relational Database Service
Document Database Service
Data Admin Service
Data Replication Service
GeminiDB
GaussDB
Distributed Database Middleware
Database and Application Migration UGO
TaurusDB
Middleware
Distributed Cache Service
API Gateway
Distributed Message Service for Kafka
Distributed Message Service for RabbitMQ
Distributed Message Service for RocketMQ
Cloud Service Engine
Multi-Site High Availability Service
EventGrid
Dedicated Cloud
Dedicated Computing Cluster
Business Applications
Workspace
ROMA Connect
Message & SMS
Domain Name Service
Edge Data Center Management
Meeting
AI
Face Recognition Service
Graph Engine Service
Content Moderation
Image Recognition
Optical Character Recognition
ModelArts
ImageSearch
Conversational Bot Service
Speech Interaction Service
Huawei HiLens
Video Intelligent Analysis Service
Developer Tools
SDK Developer Guide
API Request Signing Guide
Terraform
Koo Command Line Interface
Content Delivery & Edge Computing
Content Delivery Network
Intelligent EdgeFabric
CloudPond
Intelligent EdgeCloud
Solutions
SAP Cloud
High Performance Computing
Developer Services
ServiceStage
CodeArts
CodeArts PerfTest
CodeArts Req
CodeArts Pipeline
CodeArts Build
CodeArts Deploy
CodeArts Artifact
CodeArts TestPlan
CodeArts Check
CodeArts Repo
Cloud Application Engine
MacroVerse aPaaS
KooMessage
KooPhone
KooDrive

Basic Concepts

Updated on 2024-05-22 GMT+08:00

Topology

A topology graphically displays call and dependency relationships between applications. It is composed of circles, lines with arrows, and resources. Each circle represents a service, and each section in the circle represents an instance. The fraction in each circle indicates number of active instance/total number of instances. The values below the fraction separately indicate the service latency, number of calls, and number of errors. Each line with an arrow represents a call relationship. Thicker lines indicate more calls. The values next to each line respectively indicate the throughput and overall latency. Throughput is the number of calls in a specified time range. Application Performance Index (Apdex) is used to quantify user satisfaction with application performance. Different colors indicate different Apdex value ranges, helping you quickly detect and locate performance problems.

Transaction

A transaction is usually an HTTP request (complete process: user request > web server > database > web server > user request). In real life, a transaction is a one-time task. A user completes a task by using an application. In the example of an e-commerce application, querying a product is a transaction, and making a payment is also a transaction.

Tracing

APM traces and records service calls, and visually presents the execution tracks and statuses of service requests in distributed systems, so that you can quickly locate performance bottlenecks and faults.

Application

An application is a group of the same or similar services categorized based on service requirements. You can put services that fulfill the same function into one application for performance management. For example, you can put accounts, products, and payment services into the Mall application.

Apdex

Apdex is an open standard developed by the Apdex alliance. It defines a standard method to measure application performance. The Apdex standard converts the application response time into user satisfaction with application performance in the range of 0 to 1.

  • Apdex principle

Apdex defines the optimal threshold (T) for the application response time. T is determined by the performance evaluation personnel based on performance expectations. Based on the actual response time and T, user experience can be categorized as follows:

Satisfied: indicates that the actual response time is shorter than or equal to T. For example, if T is 1.5s and the actual response time is 1s, user experience is satisfied.

Tolerating: indicates that the actual response time is greater than T, but shorter than or equal to 4T. For example, if T is 1s, the tolerable upper threshold for the response time is 4s.

Frustrated: indicates that the actual response time is greater than 4T.

  • Apdex calculation method

    In APM, the Apdex threshold is the value configured in Setting Apdex Thresholds. The application response latency is the service latency. The Apdex value ranges from 0 to 1 and is calculated as follows:

    Apdex = (Number of satisfied samples + Number of tolerating samples x 0.5)/Total number of samples

Apdex indicates application performance status, that is, user satisfaction with application performance. Different colors indicate different Apdex ranges, as shown in Table 1.

Table 1 Apdex description

Apdex

Color

Description

0.75 ≤ Apdex ≤ 1

Green

Fast response; good user experience

0.3 ≤ Apdex < 0.75

Yellow

Slow response; fair user experience

0 ≤ Apdex < 0.3

Red

Very slow response; poor user experience

-

Black

No application, instance, or transaction is invoked.

  • Configuring an Apdex threshold

You can configure an Apdex threshold according to Setting Apdex Thresholds.

TP99 Latency

TP99 latency is the minimum time meeting requirements of 99% requests. In APM, latency refers to TP99 latency.

Example: Assume that there are 100 requests, and the time consumed by the requests is 1s, 2s, 3s, 4s...98s, 99s, and 100s. To meet the requirements of 99% requests, at least 99s is required. Therefore, TP99 latency is 99s.

Calculation: Sort all requests by the consumed time in ascending order. TP99 latency = Time consumed by the Nth request. N is the rounded value of 99% x Total number of requests.

Overall Latency/Service Latency

Latency refers to the period from initiating a request to getting a response. In APM, the overall latency refers to the total time consumed by a request, and the service latency refers to the time consumed by a service. The relationship is as follows: Service latency = Overall latency – Latency for calling other services. For example, assume that service A calls service B, and service B calls service C, as shown in the following figure:

  • Service A: Overall latency = Ta; Service latency = Ta – Tb1 – Tb2 – Tc
  • Service B: Overall latency = Tb1 + Tb2 + Tc; Service latency = Tb1 + Tb2
  • Service C: Overall latency = Tc; Service latency =Tc

Probes

Probes use the bytecode enhancement technology to track calls and generate data. The data will be collected by the ICAgent and then displayed on the UI. If the memory detection mechanism is enabled and the instance memory is too large, probes enter the hibernation state, that is, stop collecting data. How Does APM Collect Probe Data?

Mesh

The Istio mesh obtains input and output application program data in non-intrusive mode. Then, the ICAgent and Cloud Container Engine (CCE) Istio mixer obtain and process the mesh data, and report it to APM. You can enable the Istio to collect mesh data. How Does APM Collect Mesh Data?

ICAgent

ICAgent is a collection agent of APM. It runs on the server where applications are deployed to collect the data obtained by probes in real time. For details about the data collection and purposes, see APM Service Agreement. Installing the ICAgent is prerequisite for using APM.

We use cookies to improve our site and your experience. By continuing to browse our site you accept our cookie policy. Find out more

Feedback

Feedback

Feedback

0/500

Selected Content

Submit selected content with the feedback