Download and install the forwarder binary from here.
Log in here and note the URL of your Splunk instance:
In the above picture, assume the URL is https://prd-p-jxxxxxxxx.splunk6.splunktrial.com.
Make sure your instances can connect to port tcp/9997 on your input host. Your input host is the hostname from above with “input-” prepended to it. So in our example, the input host is input-prd-p-jxxxxxxxx.splunk6.splunktrial.com. To ensure you can connect, try telnet input-prd-p-jxxxxxxxx.splunk6.splunktrial.com 9997. If it can’t connect you may need to adjust your firewall rules / Security groups to allow outbound tcp/9997
Below are the actual commands I used to get data into our Splunk Cloud trial instance:
$ curl -O http://download.splunk.com/products/splunk/releases/6.2.0/universalforwarder/linux/splunkforwarder-6.2.0-237341-linux-2.6-amd64.deb
$ sudodpkg-i splunkforwarder-6.2.0-237341-linux-2.6-amd64.deb
$ sudo/opt/splunkforwarder/bin/splunk add forward-server input-prd-p-jxxxxxxxx.splunk6.splunktrial.com:9997
This appears to be your first time running this version of Splunk.
Added forwarding to: input-prd-p-jxxxxxxxx.splunk6.splunktrial.com:9997.
$ sudo/opt/splunkforwarder/bin/splunk add monitor '/var/log/postgresql/*.log'
Added monitor of '/var/log/postgresql/*.log'.
$ sudo/opt/splunkforwarder/bin/splunk list forward-server
Splunk username: admin
Configured but inactive forwards:
$ sudo/opt/splunkforwarder/bin/splunk list monitor
[No directories monitored.]
$ sudo/opt/splunkforwarder/bin/splunk restart
Upload the CSR to your SSL vendor (in this case, DigiCert) and obtain the signed SSL certificate.
Create a PEM-encoded version of the signing key. This is required for AWS/IAM certs. To check if your key is already PEM-encoded, just “head -1 site.key”. If the first line says “—–BEGIN PRIVATE KEY—–” then it’s NOT PEM-encoded. The first line should be “—–BEGIN RSA PRIVATE KEY—–“.
Once the above steps are complete, you can go into the web console (EC2 -> Load Balancers), select the ELB whose cert you want to change, click the “Listeners” tab, click the SSL port (443) and select the new cert from the dropdown.
mysql> grant replication slave on *.* to 'ec2-slave'@'%';
ERROR 1045(28000): Access denied for user 'rds_root'@'%'(using password: YES)
mysql> update mysql.user setRepl_slave_priv='Y' WHERE user='rds_root' AND host='%';
ERROR 1054(42S22): Unknown column 'ERROR (RDS): REPLICA SLAVE PRIVILEGE CANNOT BE GRANTED OR MAINTAINED'in'field list'
Note: this is for MySQL 5.5, which is unfortunately what I’m currently stuck with.
I stopped playing WoW in 2008, and since I didn’t need Windows for gaming, I ended up putting Fedora (and ultimately Ubuntu) on my old Core 2 Duo desktop. After years of fighting with slow computers, I recently bit the bullet and bought the 13″ Retina Macbook Pro (MGX82LL/A). Even though I hadn’t played WoW in years – or any other PC games, for that matter – the gamer in me was still reluctant to go with a computer with no dedicated video card. I’d read up extensively on the Intel Iris 5100 chipset in the Macbook but I couldn’t find anything about its performance in WoW, which was the least-taxing game I could think of.
Well, as fate would have it, Blizzard recently announced they’d be purging the names of characters who hadn’t logged in for 5+ years. Since I had a new computer and I didn’t want to lose my beloved Undead Rogue it seemed like a good time to rejoin. After a couple days of playing, I figured I’d write this post as a service to any other would-be Macbook Pro purchasers curious about its performance in WoW.
This isn’t a detailed benchmarking post – I’m not Anandtech. The short version is that the performance of WoW on the MGX82LL/A is very good. I get 30-60 frames per second basically everywhere, though with settings only set to “fair.” The main thing I wanted to report here is heat. The laptop gets HOT when playing WoW. I installed iStat Menus to get the sensor data – see below.
The CPU sensors show temperature increases of over 100ºF. That’s pretty darn hot. I’ll play with the settings to see if I can get the temperature to something more reasonable.
I’ve been doing some testing of various instance types in our staging environment, originally just to see if Amazon’s t2.* line of instances is usable in a real-world scenario. In the end, I found that not only are the t2.mediums viable for what I want them to do, but they’re far better suited than the m3.medium, which I wouldn’t use for anything that you ever expect to reach any load.
Here are the conditions for my test:
Rails application (unicorn) fronted by nginx.
The number of unicorn processes is controlled by chef, currently set to (CPU count * 2), so a 2 CPU instance has 4 unicorn workers.
All instances are running Ubuntu 14.04 LTS (AMI ami-864d84ee for HVM, ami-018c9568 for paravirtual) with kernel 3.13.0-29-generic #53-Ubuntu SMP Wed Jun 4 21:00:20 UTC 2014 x86_64.
The test used loader.io to simulate 65 concurrent clients hitting the API (adding products to cart) as fast as possible for 600 seconds (10 minutes).
The instances were all behind an Elastic Load Balancer, which routes traffic based on its own algorithm (supposedly the instances with the lowest CPU always gets the next request).
The below charts summarize the findings.
This chart shows each server’s performance as reported by nginx. The values are the average time to service each request and the standard deviation. While I expected the m3.large to outperform the m3.medium, I didn’t expect the difference to be so dramatic. The performance of the t2.medium is the real surprise, however.
These charts show the CPU activity for each instance during the test (data as per CopperEgg).
The m3.medium has a huge amount of CPU steal, which I’m guessing accounts for its horrible performance. Anecdotally, in my own experience m3.medium far more prone to CPU steal than other instance types. Moving from m3.medium to c3.large (essentially the same instance with 2 cpus) eliminates the CPU steal issue. However, since the t2.medium performs as well as the c3.large or m3.large and costs half of the c3.large (or nearly 1/3 of the m3.large) I’m going to try running most of my backend fleet on t2.medium.
I haven’t mentioned the credits system the t2.* instances use for burstable performance, and that’s because my tests didn’t make much of a dent in the credit balance for these instances. The load test was 100x what I expect to see in normal traffic patterns, so the t2.medium with burstable performance seems like an ideal candidate. I might add a couple c3.large to the mix as a backstop in case the credits were depleted, but I don’t think that’s a major risk – especially not in our staging environment.
I didn’t include the numbers, but the performance seemed to be the consistent whether on hvm or paravirtual instances.