datadog vs appdynamics

in line with user expectations, so as not only to fill the domestic Docker monitoring gap, it will truly become a partner of many Docker users and enterprises to solve the Docker O M and monitoring problems that really have a headache for everyone. Q: What are the differences and advantages between docker monitoring and datadog? A: The installation and deployment of DataDog is too cumbersome. At that time

Modified a line of unnoticeable code in PostgreSQL to (ANY (ARRAY [...]) change to ANY (VALUES (...))), the result query time changes from 20 s to 0.2 s. At first, we learned to use EXPLANANALYZE to optimize the code. Later on, the Postgres community has become a good helper for us to learn and improve, and our performance has been greatly improved. This is because Datadog specifically modifies a line of non-obvious code in PostgreSQL, putting (ANY (A

following command: nginx -t Open the listed master configuration file and search for rows starting with include near the end of the http block, for example: include /etc/nginx/conf.d/*.conf; In one of the contained configuration files, you should find the main server block. You can configure the NGINX metric output as shown above. After changing any configuration, run the following command to reload the configuration file: nginx -s reload Now you can view your metrics on the status

: Flink's historyserver now allows you to query the status and statistics of completed jobs JobManager archived, see FLINK-1579 for details. in the Web front-end monitoring watermark: To make it easier to diagnose watermark related issues, the Flink JobManager front end now provides a new tab to track the watermark of each operator. See FLINK-3427 for details. Datadog HTTP Metrics Reporter: Datadog

://github.com/ coreos/), [blog] (https://blog.gopheracademy.com/birthday-bash-2014/go-at-coreos/) DataDog-[Go at DataDog] (https:// blog.gopheracademy.com/birthday-bash-2014/go-at-datadog/) Digitalocean-[Let your development team start using go] (https:// blog.digitalocean.com/get-your-development-team-started-with-go/) Docker-[Why we decided to write Docker in g

This is a creation in Article, where the information may have evolved or changed. Go Performance Tales This entry was cross-posted on the Datadog blog. If you want to learn more about Datadog or what we deal with the mountain of data we receive, check it out! The last few months I ' ve had the pleasure of working on a new bit of intake processing at Datadog. It w

crashes, connection timeout, and memory leakage during use. As far as I know, tingyun is an SaaS-based service platform of the tone network. It provides an overall solution for the mobile App client-Network-Server. After the author's test, the mAPM design idea is very clear, and the SDK is only about 10 K, the advantage of similar products in foreign countries is also very obvious. In addition to listening to the cloud, the following describes several foreign solutions that require a ladder, wh

@> '{blah}'::text[]) AND (c.x_id = 1)) Buffers: shared hit=44963Total runtime: 263.639 ms The query time is reduced from 200 ms to 100 ms, and the efficiency of changing only one line of code is increased by times. New query used in production Code to be released:It makes the database look more beautiful and easy. Third-party tools Postgres slow query does not exist. But who would like to be tortured by the 0.1% unfortunate minority. To immediately verify the impact of the modification qu

;Importorg.springframework.beans.factory.annotation.Autowired;ImportOrg.springframework.stereotype.Service; @Service Public classDogservice {@AutowiredPrivatedogrepository dogrepository; /*** Add two records at the same time*/ Public voidAddtwodog () {//simulate two data linesDog dog1=NewDog (); Dog1.setage (2); Dog1.setname ("Little Black 1"); //simulate the second piece of dataDog dog2=NewDog (); Dog2.setage (2); Dog2.setname ("Little Black 2");

the field of surveillance has been from the Zabbix of this 1.0 era, into the Integrated Monitoring solution of the 2.0 era. They began to choose a monitoring tool or solution based on STATSD technology. such as Datadog, boundary and other third-party monitoring service providers.The idea of these companies is to provide an integrated solution: how to integrate different operating systems, databases, middleware monitoring problems, you don't have to w

over one million prepares a day Each prepare takes, on average, around 300ms Each prepare is highly concurrent and network I/O intensive (what @kevrone wrote here should give you a hint of the scale of how much data we deal with) Each machine runs prepares concurrently We have 4 c3.large machines We use DataDog as our primary monitoring tool for our AWS cloudformation stacks Everything is fine (for a while) As we went over ten mi

) (actual time=0.015..0.016 Rows=1 Loo ps=11215) Index Cond: (C.key = "*values*". Column1) Filter: ((c.tags @> ' {blah} ':: text[]) and (c.x_id = 1)) Buffers:shared hit=44963 Total runtime:263.639 ms Query time from 22000ms to 200ms, only one line of code change efficiency increased by 100 times times. New queries for use in productionA piece of code that is about to be released: It makes the database look more beautiful and relaxed. Third-party toolsPostgres slow query does not exis

:263.639 ms Query time from 22000ms to 200ms, only one line of code change efficiency increased by 100 times times. New queries for use in production A piece of code that is about to be released:It makes the database look more beautiful and relaxed. Third-party tools Postgres slow query does not exist. But who is willing to be tortured by the 0.1% unfortunate few. To immediately verify the impact of the Modify query, you need to Datadog to help

fastest. But this situation is often impossible, let alone easy to achieve.If you can not reduce the complexity of the algorithm, you can also find the key points in the algorithm and improve the method, to play a role in improving performance. Suppose we have the following algorithm:The overall time complexity of the algorithm is O (N3), and the complexity is O (N x O x P) if calculated in individual access order. But anyway, when we analyze this code, we find some strange scenarios: