horizontal-scaling

Docker swarm scaling behaviour on port mapping

由 徘徊边缘 提交于 2019-12-13 18:20:02
问题 I have a swarm composed of three nodes: $ sudo docker node ls ID HOSTNAME STATUS AVAILABILITY MANAGER STATUS i12s3zxsn4vu1c98bv3i5idr8 node03 Ready Active i2ckxvsju4tmommxim3dbfq7l node02 Ready Active wak4isl46dn7pbo39drrhphju * node01 Ready Active Leader Then I run 1 replica of nginx on that swarm and map his port to 8080: $ sudo docker service create --replicas 1 --publish 8080:80 --name nginx nginx $ sudo docker service ls ID NAME MODE REPLICAS IMAGE PORTS neahnb9mvi1i nginx replicated 1/1

why is sql vertically scalable and nosql horizontally

由 自古美人都是妖i 提交于 2019-12-13 08:09:54
问题 I am new to NoSQL and trying to understand it's meaning. I have seen many articles in many different websites that repeat the fact that "SQL DataBases are scaled vertically (by adding CPU/memory) whereas NoSQL DataBases are scaled horizontally (by adding more machines that can perform distributed calculations)". For example these articles: http://dataconomy.com/sql-vs-nosql-need-know/ http://www.thegeekstuff.com/2014/01/sql-vs-nosql-db/ The thing is that I can't understand why. As far as I am

How does TensorFlow cluster distribute load across machines if not specified explicitly?

由 房东的猫 提交于 2019-12-12 01:39:24
问题 I took "Distributed TensorFlow" how-to and tried to apply it to the "MNIST For ML Beginners" tutorial. I started three TensorFlow worker nodes locally (there are 8 cores in the PC) and ran the training script with replacing this line: sess = tf.InteractiveSession() with the following: sess = tf.InteractiveSession("grpc://localhost:12345") where 12346 is a port where node 0 is listening (e.g. master session is created on node 0). Note that I did not specify explicitly where computations should

SPRING BATCH : How to configure remote chunking for multiple jobs running in a task executor

由 时光毁灭记忆、已成空白 提交于 2019-12-11 06:12:45
问题 I am new to spring batch processing. I am using remote chunking where there is a master , multiple slaves and ActiveMQ for messaging. Master has a job and a job launcher and the job launcher has a task-executor which is having following configuration <task:executor id="batchJobExecutor" pool-size="2"queue-capacity="100" /> . Chunk configuration is <bean id="chunkWriter" class="org.springframework.batch.integration.chunk.ChunkMessageChannelItemWriter" scope="step"> <property name=

Horizontally scaling Scrapyd

由 拟墨画扇 提交于 2019-12-07 05:37:15
问题 What tool or set of tools would you use for horizontally scaling scrapyd adding new machines to a scrapyd cluster dynamically and having N instances per machine if required. Is not neccesary for all the instances to share a common job queue, but that would be awesome. Scrapy-cluster seems promising for the job but I want a Scrapyd based solution so I listen to other alternatives and suggestions. 回答1: I scripted my own load balancer for Scrapyd using its API and a wrapper. from random import

Some requests fails during autoscaling in kubernetes

由 ⅰ亾dé卋堺 提交于 2019-12-05 11:31:44
I set up a k8s cluster on microk8s and I ported my application to it. I also added a horizontal auto-scaler which adds pods based on the cpu load. The auto-scaler works fine and it adds pods when there is load beyond the target and when I remove the load after some time it will kill the pods. The problem is I noticed at the exact same moments that the auto-scaler is creating new pods some of the requests fail: POST Response Code : 200 POST Response Code : 200 POST Response Code : 200 POST Response Code : 200 POST Response Code : 200 POST Response Code : 502 java.io.IOException: Server returned

Horizontally scaling Scrapyd

由 旧街凉风 提交于 2019-12-05 10:21:42
What tool or set of tools would you use for horizontally scaling scrapyd adding new machines to a scrapyd cluster dynamically and having N instances per machine if required. Is not neccesary for all the instances to share a common job queue, but that would be awesome. Scrapy-cluster seems promising for the job but I want a Scrapyd based solution so I listen to other alternatives and suggestions. I scripted my own load balancer for Scrapyd using its API and a wrapper . from random import shuffle from scrapyd_api.wrapper import ScrapydAPI class JobLoadBalancer(object): @classmethod def get_less

HighCharts: Logarithmic Scale for Horizontal Bar Charts

由 ╄→尐↘猪︶ㄣ 提交于 2019-12-02 06:45:44
问题 I am working with HighCharts to produce a bar chart. My values can range from as minimal as 0 to as high as 100k (example). Therefore, one bar of the graph can be very small and the other can be very long. HighCharts has introduced the feature of "Logarithmic Scaling". The example of which can be seen HERE My js code is written in this jsfiddle file. I want to display my horizontal axis (x-Axis) logarithmically. I have inserted the key type as shown in the example but the script goes into an

HighCharts: Logarithmic Scale for Horizontal Bar Charts

由 元气小坏坏 提交于 2019-12-02 01:48:28
I am working with HighCharts to produce a bar chart. My values can range from as minimal as 0 to as high as 100k (example). Therefore, one bar of the graph can be very small and the other can be very long. HighCharts has introduced the feature of "Logarithmic Scaling". The example of which can be seen HERE My js code is written in this jsfiddle file. I want to display my horizontal axis (x-Axis) logarithmically. I have inserted the key type as shown in the example but the script goes into an infinite loop which has to be stopped. What is the flaw in the execution or is logarithmic scaling for
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