-rwxr-xr--

chmod [permissions] [file]

chmod 644 example.txt

chmod u=rwx example.txt
chmod g=rw example.txt
chmod o=rw example.txt

chmod u=rwx,g=rw,o=rw example.txt

chmod u=rwx,go=rw example.txt

chmod u+x example.txt

chmod o-wx example.txt

chmod -R 755 example_directory

via MakeUseOf.com
The Chmod Command and Linux File Permissions Explained

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15 Fun Websites for Instantly Beating Boredom Online

As companies move more of their workloads into the cloud, too many of them are doing a poor job securing that data. Amazon Web Services launched several new security services Wednesday that aim to provide them with tools that are easier to use, and easier to understand.

AWS Secrets Manager is a new console that brings together several existing AWS security features as well as a few new ones, and it “allows us to build systems that are way more secure than we ever could in the past,” said Werner Vogels, Amazon chief technology officer, during a keynote address at the AWS Summit in San Francisco. The console is designed to help administrators manage credentials, such as passwords to external services that often have to be manually entered, in a much more secure and centralized fashion, AWS said in a blog post.

Vogels bemoaned how data breaches have become a near-daily part of our lives over the past few years. “Most of these data breaches have been happening because we’ve been building security in our applications as an afterthought,” he said. “Today, security is everybody’s job. … And it’s our responsibility to protect our customers.”

Credentials are often a weak link in even the best information security strategies. Earlier this year security researchers discovered that hackers used an unprotected Kubernetes cluster running on Tesla’s infrastructure that led them to security credentials for Tesla’s AWS account, which they used to set up a cryptocurrency mining operation on Tesla’s dime. AWS Secrets Manager will allow customers to exert more control over who is allowed to access certain credentials, and it does that by using AWS Lambda, the company’s serverless computing service.

AWS also launched a new service called AWS Firewall Manager, which is designed to make it easier to use other AWS security services from a central dashboard. A lot of cloud security problems arise because a lot of cloud computing efforts started out as decentralized experiments on new applications by a small group of developers at a given company, and as that company starts to take advantage of more and more cloud services, security policies can differ from application to application based on how they were originally conceived.

And customers who need private certificates for securing web applications can now get those through AWS, thanks to the addition of the Private Security Certificate feature to the AWS Certificate Manager.

via GeekWire
Amazon Web Services launches AWS Secrets Manager and other new tools, as cloud customers continue to prove they need security help

Tile improved on its ultra-popular device trackers by adding waterproofing, customizable ring tones, increased range, and a more durable design to its new Pro series. At just $18 each, you can get four Tile Sports, while they last.

via Lifehacker
Never Lose Your Keys Again With A Great Deal on Tile’s Newly Upgraded Tracker

Or How ProxySQL Out-performs Native Aurora Cluster Endpoints

In this blog post, I’ll look at how you can use ProxySQL with AWS Aurora to further leverage database performance. My previous article described how easy is to replace the native Aurora connector with ProxySQL. In this article, you will see WHY you should do that. It is important to understand that aside from the basic optimization in the connectivity and connection management, ProxySQL also provides you with a new set of features that currently are not available in Aurora. Just think:

• Better caching
• Query filtering
• Sharding
• Query substitution
• Firewalling
• … and more

We will cover areas like scalability, security and performance. In short, I think is more than worth it to spend some time and give ProxySQL with AWS Aurora a try.

The tests

I will show you the results from two different kinds of tests. One is sysbench-oriented, the other simulates a more complex application using Java, data object utilization and a Hikari connection pool in the middle as well. For the EC2 and Aurora platform I used:

• Application/ProxySQL T2.xlarge eu-central-1a
• 2 Aurora MySQL 5.7.12 db.t2.medium eu-central-1a
• 1 Aurora MySQL 5.7.12 db.t2.medium eu-central-1b for AZ redundancy

The code for the application is available here, and for sysbench tests here. All the data and configurations for the application are available here. I ran three tests using both bench apps, obviously with Aurora as it comes and with ProxySQL. For the ProxySQL configuration see my previous article. The tests were read_only / Write_only / read_write. For Aurora, I only increased the number of connections and kept the how it comes out of the box approach. Note each test was run at least three times at different moments of the day, and on a different day. The data reported as final is the BEST performing result for each one.

The Results

For the impatient among us, here is a summary table of the tests: Sysbench:

Java App:

Now if this is enough for you, you can go to the conclusion and start to use ProxySQL with AWS Aurora. If you would like to know a bit more, continue reading. Aside from any discussion on the benchmark tool and settings, I really focused on identifying the differences between the two “connectors”. Given the layer below was exactly the same, any difference is due to the simple substitution of the endpoint.

Sysbench

Read Only

The first image reports the number of events achieved at the time of the test. It is quite clear that when using ProxySQL, sysbench ran more events.
In this graph, higher is better:

In this graph, lower is better:

As we can see, the latency when using an Aurora cluster entry point is higher. True, we are talking about milliseconds, but it is not just the value that matters, but also the distribution:

Aurora cluster endpoint	ProxySQL

An image is worth a thousand words! We can see, the behavior stays constant in analyzing the READS executed, with ProxySQL performing better.

  In this graph, higher is better:

  In this graph, higher is better:

Closing with the number of total queries performed, in which ProxySQL surpassed the Cluster endpoint by ~ 4K queries.

Write Only

For writing, things go a bit different. We see that all lines intersect, and the values are very close one to the other.

I will let the images speak for themselves:

In this graph, higher is better:

In this graph, lower is better:

Latency spiked in each ProxySQL test, and it may require additional investigation and tuning.

 In this graph, higher is better:

While the rates of writes/sec intersect with each other frequently, in the end ProxySQL resulted in more writes than the native endpoint.

In this graph, higher is better:

In the end, a difference exists and is consistent across the different test iterations, but is minimal. We are talking a range of 25 – 50 entries in total.

This result is not surprising, and it will be clear why later in the article.

Read and Write

As expected in the read and write test, we see a different situation.

ProxySQL is still performing better than the default entry point, but not by such a big margin as in read-only tests.

In this graph, higher is better:

In this graph, lower is better

Latency and events are following the expected trend, where read operations are executed more efficiently with ProxySQL and writes are close, but NOT the same as in the write only test. 

As a result, the number of queries in ProxySQL is approximately 13% better than the default entry point.

Java Application Tests

What about the Java application? First of all, we need to remember that the application used a connection pool mechanism (Hikari), and the connection pool was present in all cases (for both Aurora cluster endpoint or ProxySQL). Given that a small delay in establishing the first connection was expected, you can easily see this in the MAX value of the connection latency. In this graph, lower is better.

The connection latency reported here is expressed in nanoseconds and is the measure of the time taken by the connection provider to return an active connection to the application from the moment the application requested it. In other words, how long the HikariCP is taking to choose/check/return an open connection. As you can see, the MAX value is drastically higher, and this was expected since it is the connection initialization. While not really interesting in terms of performance, this value is interesting because it gives us the dimension of the cost in the CP to open a new connection, which in the worse case is 25 milliseconds. As the graphs show, ProxySQL manages both cases (first call, reassignment) more efficiently.
In this graph, higher is better.

In the CRUD summary table, we can see the number of SQL commands executed per second for each CRUD action and for each test. Once more we can see that when using ProxySQL, the application performed much better and significantly executed more operations (especially in the R/W test).

  In this graph, higher is better.

This graph represents the total number of events run at the time of the test. An event is a full application cycle, which sees the application generate the data needed to fill the SQL (no matter if it is for read/write), create the SQL, request the connection, push the SQL, get and read the resultset returned and give back the connection. Once more, ProxySQL shows better performance.
In this graph, lower is better.

The execution time reported in this graph is the time taken by the application to run a whole event. This is it, execution time is the time of a full cycle. The faster the cycle is executed, the better the application is performing. The time is express in milliseconds and it goes from a very fast read, which probably accesses the cache in Aurora, to almost two seconds taken to insert a batch of rows. Needless to say, the tests using ProxySQL performed better.

But Why?

Why do the tests using ProxySQL perform better? After all, it is just an additional step in the middle, which also has a cost in intercepting the queries and managing the connections.

So why the better performance? The answer is simple and can be found in the Aurora manual: https://docs.aws.amazon.com/AmazonRDS/latest/UserGuide/Aurora.Overview.html#Aurora.Overview.Endpoints.
The Cluster endpoint is an endpoint for an Aurora DB cluster that connects to the current primary instance for that DB cluster. Each Aurora DB cluster has a cluster endpoint and one primary instance.

That endpoint receives the read and write request and sends them to the same instance.The main use for it is to perform failover if needed. At the same time, the Reader endpoint is an endpoint for an Aurora DB cluster that connects to one of the available Aurora Replicas for that DB cluster.

Each Aurora DB cluster has a reader endpoint. If there is more than one Aurora Replica, the reader endpoint directs each connection request to one of the Aurora Replicas. The reader endpoint only load balances connections to available Aurora Replicas in an Aurora DB cluster. It does not load balance specific queries.

If you want to load balance queries to distribute the read workload for a DB cluster, you need to manage that in your application and use instance endpoints to connect directly to Aurora Replicas to balance the load.
This means that to perform a Read/Write split, your application must manage two entry points and you will NOT have much control over how the queries are handled or to which replica instance they are directed.

This could lead to unexpected results and delays. Needless to say, ProxySQL does all that by default (as described in my previous article). Now that we’ve clarified how Aurora entry points behave, let’s see about the performance difference.

How do we read this graph? From left to right:

• read_only test with an Aurora cluster endpoint
• read_only test with ProxySQL
• write_only with an Aurora cluster endpoint
• write_only with ProxySQL
• read and write with an Aurora cluster endpoint
• read and write with ProxySQL

Here we go! As we can see, the tests with ProxySQL used the two configured instances, splitting R/W without the need to do anything on the application side. I purposely avoided the AZ replica because I previously identified it as having higher latency, so I can exclude it and use it ONLY in the case of an emergency.

The effects are clear in the next graph.

When using the cluster endpoint, given all the load was on a single instance, the CPU utilization is higher and that became a bottleneck. When using ProxySQL, the load is spread across the different instances, allowing real read scalability. This has immediate benefits in read and read/write operations, allowing better load distribution that results in better performance.

Conclusions

Aurora is a very interesting technology and can be a very good solution for read scaling.
But at the moment, the way AWS offers data connectivity with the Cluster endpoints and Reader endpoints can negatively affect performance.

The lack of configuration and the limitation of using different endpoints lead to confusion and less optimized utilization.

The introduction of ProxySQL, which now supports (from version 2) Aurora, allows an architect, SA or DBA to properly configure the environment. You can very granularly choose how to use each instance, without the need to have the application modify how it works. This helps keep the data layer solution separate from the application layer. Even better, this additional set of flexibility does not come with a cost.

On the contrary, it improves resource utilization and brings higher performance using less powerful instances. Given the cost of Aurora, this is not a secondary benefit.

  I suggest you try installing ProxySQL v2 (or higher) in front of your Aurora cluster. If you don’t feel confident and prefer to have us help you, contact us and we will be more than happy to support you!

via Planet MySQL
Leveraging ProxySQL with AWS Aurora to Improve Performance

via The Truth About Guns
Gear Review: CompMag California Compliant AR-15 Magazine

In this blog post, we’ll show that you can plot MySQL data in real time using Percona Monitoring and Management (PMM).

In my previous blog post, I showed how we could load into any metrics, benchmarks into MySQL and visualize it with PMM. But that’s not all! We can even visualize most any kind of data from MySQL in real time. I am falling in love with the MySQL plugin for Grafana — it just makes things so easy and smooth.

This graph shows us the number of visitors to a website in real time (refreshing in every 5 seconds).

We have the following table in MySQL:

CREATE TABLE `page_stats` (
  `id` int(10) unsigned NOT NULL AUTO_INCREMENT,
  `time` timestamp NOT NULL DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
  `visitors` int(11) unsigned DEFAULT NULL,
  PRIMARY KEY (`id`),
  KEY `time` (`time`)
) ENGINE=InnoDB AUTO_INCREMENT=9232 DEFAULT CHARSET=latin1

We store the number of visitors every second. I am not saying you have to update this table hundreds or thousands of times, it depends on how many visitors you have. You could use the example of Redis to store and increase this counter and save it into MySQL every second. Here are my metrics:

mysql> select * from page_stats order by id desc limit 10;
+------+---------------------+----------+
| id   | time                | visitors |
+------+---------------------+----------+
| 9446 | 2018-02-27 21:44:12 |      744 |
| 9445 | 2018-02-27 21:44:11 |      703 |
| 9444 | 2018-02-27 21:44:10 |      791 |
| 9443 | 2018-02-27 21:44:09 |      734 |
| 9442 | 2018-02-27 21:44:08 |      632 |
| 9441 | 2018-02-27 21:44:07 |      646 |
| 9440 | 2018-02-27 21:44:06 |      656 |
| 9439 | 2018-02-27 21:44:05 |      678 |
| 9438 | 2018-02-27 21:44:04 |      673 |
| 9437 | 2018-02-27 21:44:03 |      660 |
+------+---------------------+----------+

We can easily add my MySQL query to Grafana, and it will visualize it for us:

You might ask “what is $__timeFilter?” I discussed that in the previous post, but let me copy the manual here as well:

Time series:
- return column named time_sec (UTC in seconds), use UNIX_TIMESTAMP(column)
- return column named value for the time point value
- return column named metric to represent the series name
Table:
- return any set of columns
Macros:
- $__time(column) -> UNIX_TIMESTAMP(column) as time_sec
- $__timeFilter(column) ->  UNIX_TIMESTAMP(time_date_time) ≥ 1492750877 AND UNIX_TIMESTAMP(time_date_time) ≤ 1492750877
- $__unixEpochFilter(column) ->  time_unix_epoch > 1492750877 AND time_unix_epoch < 1492750877
- $__timeGroup(column,'5m') -> (extract(epoch from "dateColumn")/extract(epoch from '5m'::interval))::int
Or build your own conditionals using these macros which just return the values:
- $__timeFrom() ->  FROM_UNIXTIME(1492750877)
- $__timeTo() ->  FROM_UNIXTIME(1492750877)
- $__unixEpochFrom() ->  1492750877
- $__unixEpochTo() ->  1492750877

What can I visualize?

It’s true! Basically, if you can write a query, you can graph it. For example, let’s count all the visitors in every minute. Here is the query:

select
      UNIX_TIMESTAMP(ps.time) as time_sec,
      sum(visitors) as value,
      'visitors' as metric
   from
   page_stats as ps
   WHERE $__timeFilter(time)
   GROUP BY DATE_FORMAT(`time`, '%Y-%m-%d %H:%i')
    ORDER BY ps.time ASC;

And it gives us the following graph:

See, it’s easy!

Conclusion

There is no more excuse why you can not visualize your data! Percona Monitoring and Management lets you plot MySQL data in real time. You do not have to move it anywhere or change anything! Just grant read access from PMM, and you can start to create your own graphs!

The post Plot MySQL Data in Real Time Using Percona Monitoring and Management (PMM) appeared first on Percona Database Performance Blog.

via Planet MySQL
Plot MySQL Data in Real Time Using Percona Monitoring and Management (PMM)

In this episode of TFBTV, James gives the Sig Sauer P365 in 9mm a thorough rundown. On paper, the P365 looks like the ultimate carry 9mm: it’s as thin and light as most single stack 9mm pistols that only carry 6 or 7 rounds, while it can hold up to 11 (or 13 rounds with […]

Read More …

The post Sig Sauer P365 500 Round Review: Is it a Game Changing 9mm CCW? appeared first on The Firearm Blog.

via The Firearm Blog
Sig Sauer P365 500 Round Review: Is it a Game Changing 9mm CCW?

It was a dangerous week for some of the biggest names in technology as they they were forced to face off against these new things called "consequences" which have come about due to their ongoing "actions." It’s all so very unfair. Ashley Madison is still super duper sorry about the whole exposing of America’s least competent infidelitors thing, Reddit is saying "sayonara" to bitcoin (but not its resident racists), and the government of Ecuador went and changed up the Wi-Fi password on poor Julian Assange. But hey, at least Zuck won’t be out of a job anytime soon. Numbers, because how else will we know whether she’ll sink or float?

18 years: The wheels of justice turn slowly, even when they’ve gone off the rails. Adnan Syed spent nearly two decades in a cell for a crime he reportedly didn’t commit. But, thanks to some sterling reporting from the producers of the Serial podcast, Mr. Syed has been awarded a new trial by the state of Maryland.

136,000 data points, I mean "people": In the wake of the Cambridge Analytica scandal, the data collection company promised that it would "delete" all of the data it had acquired. Yeah, just like I’m going to "stop drinking" and "get my shit together". Channel 4 just discovered a cache of data from 136,000 Colorado residents, including their personality profiles, which is just wow. So, if you haven’t deleted your Facebook profile yet, now would probably be a good time to do so before that information leaks and the internet gets to play head shrinker with your most personal of datas.

30 million exposed accounts: The team behind the voluntary adultery site, Ashley Madison, is somehow back, having clearly not learned their lesson. After being fined more than $12 million, the site is still online and attracting a new crop of philanderers with its new slogan, "Find your moment". That has such a nicer ring than "Life is short. Have an affair," doesn’t it.

5 years: Reddit, at least they’re not 4Chan.

1,099,511,627,776 combinations: So the Ecuadorian embassy has apparently had enough of Julian Assange’s shenanigans and has revoked his internet access. All Big Jules has to do is guess the right 16-digit character combination and he can get right back to helping subvert US elections. Granted, it’s going to potentially take slightly more than a trillion tries, but what else are you going to do while trapped in a downtown London closet with nothing but time on your hands?

0 repercussions: Mark Zuckerberg has built a global data mining operation and somehow convinced us all that it’s worthwhile. His company has facilitated meddling with the US political system and given the Winklevoss twins 14 minutes more spotlight than they deserve. His penance for these sins, of course, will be to remain one of the richest people on Earth.

4/22: I’ve never actually watched "Westworld" so I’m going to go ahead and just assume its just robotic witches fighting robosamurai like from this trailer for the second season which I also didn’t watch.

via Engadget
After Math: This is a witch hunt