gke-opt-demo's People
gke-opt-demo's Issues
Workload reliability risk
Provisioning Assessment:
Based on the provided workload structure, it appears that the workload is currently over-provisioned in terms of both CPU and memory resources.
-
CPU: The workload's average CPU utilization is only around 1.9%, indicating that the allocated CPU resources are not being fully utilized. The recommended CPU request is 8 mCores, while the recommended CPU limit is 12 mCores. This suggests that the workload could potentially run effectively with a smaller CPU allocation.
-
Memory: Similarly, the workload's maximum memory utilization is around 48% of the allocated memory. The recommended memory request is 109 MiB, while the recommended memory limit is also 109 MiB. This indicates that the workload could potentially run effectively with a smaller memory allocation.
Compute Instance Recommendation:
Given the workload's resource requirements and the image type ("nginx"), a suitable compute instance recommendation would be an A2 instance type. The A2 instance type provides 2 vCPUs and 8 GiB of memory, which should be sufficient to accommodate the workload's resource needs.
Note: The specific compute instance recommendation may vary depending on the actual application requirements and workload characteristics. It is always advisable to conduct performance testing and monitoring to fine-tune the resource allocation and ensure optimal performance.
**Please update the container: main resources request **
apiVersion: apps/v1
kind: Deployment
metadata:
name: loadgenerator
spec:
selector:
matchLabels:
app: loadgenerator
...
containers:
- name: main
resources:
requests:
cpu: 8m
memory: 109Mi
limits:
cpu: 12m
memory: 109Mi
BLANK
ISUEE
blue
LAST ISSUE
test
blue
r
remove
serious last issue
tst
NEW ISSUE
this is a test
purple
yello
gre
workload with reliability risks
Provisioning Assessment:
Based on the provided workload structure, it appears that the workload is currently over-provisioned in terms of both CPU and memory resources.
-
CPU: The workload's average CPU utilization is only around 1.9%, indicating that the allocated CPU resources are not being fully utilized. The recommended CPU request is 8 mCores, while the recommended CPU limit is 12 mCores. This suggests that the workload could potentially run effectively with a smaller CPU allocation.
-
Memory: Similarly, the workload's maximum memory utilization is around 48% of the allocated memory. The recommended memory request is 109 MiB, while the recommended memory limit is also 109 MiB. This indicates that the workload could potentially run effectively with a smaller memory allocation.
Compute Instance Recommendation:
Given the workload's resource requirements and the image type ("nginx"), a suitable compute instance recommendation would be an A2 instance type. The A2 instance type provides 2 vCPUs and 8 GiB of memory, which should be sufficient to accommodate the workload's resource needs.
Note: The specific compute instance recommendation may vary depending on the actual application requirements and workload characteristics. It is always advisable to conduct performance testing and monitoring to fine-tune the resource allocation and ensure optimal performance.
**Please update the container: main resources request **
apiVersion: apps/v1
kind: Deployment
metadata:
name: loadgenerator
spec:
selector:
matchLabels:
app: loadgenerator
...
containers:
- name: main
resources:
requests:
cpu: 8m
memory: 109Mi
limits:
cpu: 12m
memory: 109Mi
workload at risk
Provisioning Assessment:
Based on the provided workload structure, it appears that the workload is currently over-provisioned in terms of both CPU and memory resources.
-
CPU: The workload's average CPU utilization is only around 1.9%, indicating that the allocated CPU resources are not being fully utilized. The recommended CPU request is 8 mCores, while the recommended CPU limit is 12 mCores. This suggests that the workload could potentially run effectively with a smaller CPU allocation.
-
Memory: Similarly, the workload's maximum memory utilization is around 48% of the allocated memory. The recommended memory request is 109 MiB, while the recommended memory limit is also 109 MiB. This indicates that the workload could potentially run effectively with a smaller memory allocation.
Compute Instance Recommendation:
Given the workload's resource requirements and the image type ("nginx"), a suitable compute instance recommendation would be an E2 instance type. The E2 instance type should be sufficient to accommodate the workload's resource needs.
Note: The specific compute instance recommendation may vary depending on the actual application requirements and workload characteristics. It is always advisable to conduct performance testing and monitoring to fine-tune the resource allocation and ensure optimal performance.
**Please update the container: main resources request **
apiVersion: apps/v1
kind: Deployment
metadata:
name: loadgenerator
spec:
selector:
matchLabels:
app: loadgenerator
...
containers:
- name: main
resources:
requests:
cpu: 8m
memory: 109Mi
limits:
cpu: 12m
memory: 109Mi
workload still is bad
nonono
TEST API
XTZ
tst
red
Ameenah
burhan
banker
4
green
please
work
test
plse
workload not rightsized
the workload isn't rightsized
broken link
test this
new
new description
pink
last?
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
๐ Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. ๐๐๐
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google โค๏ธ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.