Using OpsCenter OpenSource version 5.2.1 on Ubuntu 14.04.
I cannot see the "Data Size" Metric in Node Ring or List view however, if I click on a single node I can see it's disk usage. I'm not having any luck getting information from datastax agent logs or from opscenterd logs.
I suspect that perhaps this is an enterprise only feature?
Can provide additional information as requested.
Screenshots for clarity can be found here. (sorry, I need more "reputation" to post them directly to this thread)
OpsCenter doesn't have full C* 2.2 support. I am, unfortunately using C* 2.2.
Related
I am using Apache Ignite 2.8.0
GridGain web console is used to monitor the live performance of Ignite.
Is there possible to Monitor the history records?
Example, I need view the performance of last week, is there possible by GridGain web console?
Initially when i downloaded that the size is 77MB, but now size is 256MB. So i got doubt as whether it will store the data anywhere?
GridGain Control Center, the next monitoring tool from GridGain that will substitute Web Console, supports tracing capabilities and more advanced monitoring dashboards that can work with historical data: https://www.gridgain.com/docs/control-center/latest/overview
Used the template provided here :- https://github.com/3scale/3scale-amp-openshift-templates/blob/master/amp/amp.yml
Under integration tab , i am unable to see the option for APICast self managed gateway option.
From the graphics I would assume the version you installed is 2.3 or lower.
My suggestion is to try with the latest stable template (2.8)
I know this question has been asked before, but it was asked back in 2014. The proposed solution was running Microsoft's port of Redis. However, that port hasn't been touched since 2016.
OK... that answer is Good and Official but this one is the future.
Windows Linux Subsystem supports fork (the reason they say it is not recommended) and I was able to run the RQ tutorial on my Windows 10 laptop.
https://learn.microsoft.com/en-us/windows/wsl/install-win10
As far as I can tell, "Not Recommended" is the official answer:
https://redislabs.com/ebook/appendix-a/a-3-installing-on-windows/
Before we get into how to install Redis on Windows, I’d like to point
out that running Redis on Windows isn’t recommended, for a variety of
reasons. In this section we’ll cover these points:
Reasons why you shouldn’t be running Redis on Windows. How to
download, install, and run a precompiled Windows binary. How to
download and install Python for Windows. How to install the Redis
client library.
But even that ebook page (next page) points to the now archived MSFT Redis project.
I would go with running Redis in Docker
https://hub.docker.com/r/_/redis/
I am trying to run a Spark cluster with some Windows instances on an Amazon EC2 infrastructure, but I am facing some issues with extremely high deploying times.
My project needs to be run on a Windows environment, and therefore I am using an alternative AMI by indicating it with the -a flag provided by Spark's spark-ec2 script. When I run the script, the process keeps stuck waiting for the instances to be up and running, with the following message:
Waiting for all instances in cluster to enter 'ssh-ready' state.............
When I use the default AMI, instead, the cluster launches normally after very few minutes of waiting.
I have searched for similar problems with other users, and so far I have only been able to find this statement about long deploying time with custom AMI-s (see Josh Rosen's answer).
I am using the version 1.2.0 of Spark. The call that launches the cluster looks something like the following:
./spark-ec2 -k MyKeyPair
-i MyKeyPair.pem
-s 10
-a ami-905fe9e7
--instance-type=t1.micro
--region=eu-west-1
--spark-version=1.2.0
launch MyCluster
The AMI indicated above refers to:
Microsoft Windows Server 2012 R2 Base - ami-905fe9e7
Desc: Microsoft Windows 2012 R2 Standard edition with 64-bit architecture. [English]
Any help or acclaration abouth this issue would be greatly appreciated.
I think I have figured out the problem. It seems Spark does not support the creation of clusters on a Windows environment with its default scripts. I think it is still possible to create a cluster with some manual tweaking, but it goes out of my limited knowledge. Here is the official post that explains it.
Instead, as a temporal solution, I am considering the usage of a Microsoft Azure cluster, which has just released an experimental tool that makes able to use a variant of Apache Hadoop (Spark) on their HDinsight clusters. Here is the article that explains it better.
Many times, I get:
-Frozen, load goes to 5.0. Can't use my box.
-Just doesn't work.
Do following steps:
1.rabbitmq-plugins enable rabbitmq_management
2.service rabbitmq-server restart
3.browse to http://rabbitmq-server-ip:15672
4.login with
username: guest
password: guest
Dont forget to change your password later.
As sheki notes, rabbitmqctl is your first port of call for diagnostics, and for building monitoring on top of, but it's not suitable for actual monitoring directly being a manual command line.
I've found DataDog very good to monitor both the MQ details, plus the host platform in parallel. e.g. you can watch the queue levels and set alerts on queues backing-up, while also watching the CPU/memory/IO inflicted by these queue levels. It really helps to get ratios of resource usage, and the alerts are good. Having a uniform platform for both infrastructure and application level monitoring is surprisingly rare, but speeds up diagnoses of production issues hugely.
NewRelic is similar and also has a RabbitMQ plugin, although I've not used this plugin specifically, I've used NR for years and found it invaluable in diagnosing operational issues.
AppDynamics is another example. Similarly this allows you to drill down into your app from a high-level dashboard, and visually navigate from problems to causes. It's especially good with visualising the network of a distributed application across various services/servers. I've used this, for example, to find complex problems in .NET applications and SQL Server clusters using 3rd party Web Services (e.g. latency and its consequences to your app over chatty protocols). These things are very difficult to diagnose, especially for developers who are limited to checking their code. Diagnosing operational issues requires a much broader picture.
I gave up trying to even install and configure Nagios. I know it's the 'best' but it's the best of an old breed of self-configured beasts which we don't have time to manage. I didn't even get it going... and eventually turned to the more 'modern' cloud approach. Once you get over the trust factor, it's pretty liberating.
I'm using these APM platforms together* to aggregate data from:
Windows O/S level Event Logs/Services
Linux O/S level
AWS console level
RDS, EC2
Apache
MySQL
App integrations / custom NR plugins I've written
Rabbit MQ
*NewRelic can feed into Datadog! So if you are already using NR you don't need to install DD on those hosts as well.
Being able to view all these levels together gives you a view on the publishers, middleware, MQ servers, workers and front-end app - all in one dashboard.
I would highly recommend an approach like this, because just looking at one server alone leads you to a lot of head-scratching. Seeing an entire stack in one customisable dashboard is just so illuminating it takes most of the guesswork out of it.
Worried about installing these things? I found New Relic to be especially light-weight and unobtrusive. AppDynamics seemed to stress the host a bit more, but mostly that's because you had to run the visualisation tools on the host! (this may have changed). DataDog seems performant, but creates a lot of control panels/icons on the target host (perhaps just a visual impression).
To a four year old question - this answer probably wasn't available in 2011, but in 2015 these once 'startup' style APM services are just tens or hundred dollars a month for an unbelievably rich enterprise-level solution.
There are bunch of RabbitMQ monitoring plugins available for different monitoring systems like Nagios, Zabbix etc.
Look at http://www.rabbitmq.com/how.html#management
Using rabbitmqctl is the most straight forward solution to check the status of the node.
$ rabbitmqctl status
This should tell you the status of the RabbitMQ node.
If you have PRTG (or any probe system with a HTTP sensor check), you can check the server status described at the following page:
https://blog.cdemi.io/monitoring-rabbitmq-in-prtg/
In particular you have to
Enable Management Plugin
The rabbitmq-management plugin provides an HTTP-based API for management and monitoring of your RabbitMQ
server, along with a browser-based UI and a command line tool,
rabbitmqadmin. The management plugin is included in the RabbitMQ
distribution. To enable it, we need to run: rabbitmq-plugins enable
rabbitmq_management on the RabbitMQ nodes. For more details on the
Management plugin refer to RabbitMQ Documentation.
The web UI is located at: http://server-name:15672/ The HTTP API and
its documentation are both located at: http://server-name:15672/api/
Once done, you can check the overview of your server with the API:
http://server-name:15672/api/overview
Where you have a JSON with all details about the server, active connections, queues, etc.
This cmd will help you service rabbitmq-server status
OR try theseservice rabbitmq-server stop and service rabbitmq-server start then service rabbitmq-server status.