Skip to main content

Home/ Larvata/ Group items tagged redis

Rss Feed Group items tagged

Filter: All | Bookmarks | Topics Simple Middle
crazylion lee

GitHub - joyieldInc/predixy: A high performance and full features proxy for redis, supp... - 0 views

github.com/predixy

redis proxy

shared by crazylion lee on 29 Aug 17 - No Cached
  • crazylion lee on 29 Aug 17
     
    "A high performance and full features proxy for redis, support redis sentinel and redis cluster"
張 旭

Queues - Laravel - The PHP Framework For Web Artisans - 0 views

laravel.com/queues

php programming laravel queue worker framework

shared by 張 旭 on 02 Mar 19 - No Cached
  • Laravel queues provide a unified API across a variety of different queue backends, such as Beanstalk, Amazon SQS, Redis, or even a relational database.
  • The queue configuration file is stored in config/queue.php
  • a synchronous driver that will execute jobs immediately (for local use)
  • ...56 more annotations...
  • A null queue driver is also included which discards queued jobs.
  • In your config/queue.php configuration file, there is a connections configuration option.
  • any given queue connection may have multiple "queues" which may be thought of as different stacks or piles of queued jobs.
  • each connection configuration example in the queue configuration file contains a queue attribute.
  • if you dispatch a job without explicitly defining which queue it should be dispatched to, the job will be placed on the queue that is defined in the queue attribute of the connection configuration
  • pushing jobs to multiple queues can be especially useful for applications that wish to prioritize or segment how jobs are processed
  • specify which queues it should process by priority.
  • If your Redis queue connection uses a Redis Cluster, your queue names must contain a key hash tag.
  • ensure all of the Redis keys for a given queue are placed into the same hash slot
  • all of the queueable jobs for your application are stored in the app/Jobs directory.
  • Job classes are very simple, normally containing only a handle method which is called when the job is processed by the queue.
  • we were able to pass an Eloquent model directly into the queued job's constructor. Because of the SerializesModels trait that the job is using, Eloquent models will be gracefully serialized and unserialized when the job is processing.
  • When the job is actually handled, the queue system will automatically re-retrieve the full model instance from the database.
  • The handle method is called when the job is processed by the queue
  • The arguments passed to the dispatch method will be given to the job's constructor
  • delay the execution of a queued job, you may use the delay method when dispatching a job.
  • dispatch a job immediately (synchronously), you may use the dispatchNow method.
  • When using this method, the job will not be queued and will be run immediately within the current process
  • specify a list of queued jobs that should be run in sequence.
  • Deleting jobs using the $this->delete() method will not prevent chained jobs from being processed. The chain will only stop executing if a job in the chain fails.
  • this does not push jobs to different queue "connections" as defined by your queue configuration file, but only to specific queues within a single connection.
  • To specify the queue, use the onQueue method when dispatching the job
  • To specify the connection, use the onConnection method when dispatching the job
  • defining the maximum number of attempts on the job class itself.
  • to defining how many times a job may be attempted before it fails, you may define a time at which the job should timeout.
  • using the funnel method, you may limit jobs of a given type to only be processed by one worker at a time
  • using the throttle method, you may throttle a given type of job to only run 10 times every 60 seconds.
  • If an exception is thrown while the job is being processed, the job will automatically be released back onto the queue so it may be attempted again.
  • dispatch a Closure. This is great for quick, simple tasks that need to be executed outside of the current request cycle
  • When dispatching Closures to the queue, the Closure's code contents is cryptographically signed so it can not be modified in transit.
  • Laravel includes a queue worker that will process new jobs as they are pushed onto the queue.
  • once the queue:work command has started, it will continue to run until it is manually stopped or you close your terminal
  • queue workers are long-lived processes and store the booted application state in memory.
  • they will not notice changes in your code base after they have been started.
  • during your deployment process, be sure to restart your queue workers.
  • customize your queue worker even further by only processing particular queues for a given connection
  • The --once option may be used to instruct the worker to only process a single job from the queue
  • The --stop-when-empty option may be used to instruct the worker to process all jobs and then exit gracefully.
  • Daemon queue workers do not "reboot" the framework before processing each job.
  • you should free any heavy resources after each job completes.
  • Since queue workers are long-lived processes, they will not pick up changes to your code without being restarted.
  • restart the workers during your deployment process.
  • php artisan queue:restart
  • The queue uses the cache to store restart signals
  • the queue workers will die when the queue:restart command is executed, you should be running a process manager such as Supervisor to automatically restart the queue workers.
  • each queue connection defines a retry_after option. This option specifies how many seconds the queue connection should wait before retrying a job that is being processed.
  • The --timeout option specifies how long the Laravel queue master process will wait before killing off a child queue worker that is processing a job.
  • When jobs are available on the queue, the worker will keep processing jobs with no delay in between them.
  • While sleeping, the worker will not process any new jobs - the jobs will be processed after the worker wakes up again
  • the numprocs directive will instruct Supervisor to run 8 queue:work processes and monitor all of them, automatically restarting them if they fail.
  • Laravel includes a convenient way to specify the maximum number of times a job should be attempted.
  • define a failed method directly on your job class, allowing you to perform job specific clean-up when a failure occurs.
  • a great opportunity to notify your team via email or Slack.
  • php artisan queue:retry all
  • php artisan queue:flush
  • When injecting an Eloquent model into a job, it is automatically serialized before being placed on the queue and restored when the job is processed
張 旭

redis cluster管理工具redis-trib.rb详解 | 魏子珺的博客 - 0 views

weizijun.cn/...edis-trib-rb%E8%AF%A6%E8%A7%A3

linux redis cache cluster

shared by 張 旭 on 26 Feb 18 - No Cached
  • reshard命令可以在线把集群的一些slot从集群原来slot负责节点迁移到新的节点，利用reshard可以完成集群的在线横向扩容和缩容。
張 旭

Replication - Redis - 0 views

redis.io/replication

redis replication HA cache

shared by 張 旭 on 25 Jun 19 - No Cached
  • leader follower (master-slave) replication
  • slave Redis instances to be exact copies of master instances.
  • The slave will automatically reconnect to the master every time the link breaks, and will attempt to be an exact copy of it regardless of what happens to the master.
  • ...2 more annotations...
  • the master keeps the slave updated by sending a stream of commands to the slave
  • When a partial resynchronization is not possible, the slave will ask for a full resynchronization.
張 旭

phusion/passenger-docker: Docker base images for Ruby, Python, Node.js and Meteor web apps - 0 views

github.com/...passenger-docker

docker ruby rails

shared by 張 旭 on 14 Jan 22 - No Cached
  • Ubuntu 20.04 LTS as base system
  • 2.7.5 is configured as the default.
  • Python 3.8
  • ...23 more annotations...
  • A build system, git, and development headers for many popular libraries, so that the most popular Ruby, Python and Node.js native extensions can be compiled without problems.
  • Nginx 1.18. Disabled by default
  • production-grade features, such as process monitoring, administration and status inspection.
  • Redis 5.0. Not installed by default.
  • The image has an app user with UID 9999 and home directory /home/app. Your application is supposed to run as this user.
  • running applications without root privileges is good security practice.
  • Your application should be placed inside /home/app.
  • COPY --chown=app:app
  • Passenger works like a mod_ruby, mod_nodejs, etc. It changes Nginx into an application server and runs your app from Nginx.
  • placing a .conf file in the directory /etc/nginx/sites-enabled
  • The best way to configure Nginx is by adding .conf files to /etc/nginx/main.d and /etc/nginx/conf.d
  • files in conf.d are included in the Nginx configuration's http context.
  • any environment variables you set with docker run -e, Docker linking and /etc/container_environment, won't reach Nginx.
  • To preserve these variables, place an Nginx config file ending with *.conf in the directory /etc/nginx/main.d, in which you tell Nginx to preserve these variables.
  • By default, Phusion Passenger sets all of the following environment variables to the value production
  • Setting these environment variables yourself (e.g. using docker run -e RAILS_ENV=...) will not have any effect, because Phusion Passenger overrides all of these environment variables.
  • PASSENGER_APP_ENV environment variable
  • passenger-docker autogenerates an Nginx configuration file (/etc/nginx/conf.d/00_app_env.conf) during container boot.
  • The configuration file is in /etc/redis/redis.conf. Modify it as you see fit, but make sure daemonize no is set.
  • You can add additional daemons to the image by creating runit entries.
  • The shell script must be called run, must be executable
  • the shell script must run the daemon without letting it daemonize/fork it.
  • We use RVM to install and to manage Ruby interpreters.
張 旭

Best Practices · mperham/sidekiq Wiki - 0 views

github.com/...Best-Practices

rails ruby background job sidekiq programming

shared by 張 旭 on 08 Feb 17 - No Cached
  • Don't save state to Sidekiq, save simple identifiers.
  • Look up the objects once you actually need them in your perform method.
  • The Sidekiq client API uses JSON.dump to send the data to Redis
  • ...6 more annotations...
  • The Sidekiq server pulls that JSON data from Redis and uses JSON.load to convert the data back into Ruby types to pass to your perform method
  • Idempotency means that your job can safely execute multiple times
  • use a database transaction to ensure data changes are rolled back if there is an error
  • Sidekiq will execute your job at least once.
  • Sidekiq is designed for parallel execution so design your jobs so you can run lots of them in parallel
  • Sidekiq will not provide features which hack around a lack of concurrency in your jobs.
crazylion lee

Swoole®: PHP的异步、并行、高性能网络通信引擎 - 0 views

www.swoole.com

php framework

shared by crazylion lee on 10 Jun 17 - No Cached
  • crazylion lee on 10 Jun 17
     
    " PHP的异步、并行、高性能网络通信引擎，使用纯C语言编写，提供了PHP语言的异步多线程服务器，异步TCP/UDP网络客户端，异步MySQL，异步Redis，数据库连接池，AsyncTask，消息队列，毫秒定时器，异步文件读写，异步DNS查询。 Swoole内置了Http/WebSocket服务器端/客户端、Http2.0服务器端。"
張 旭

Scalable architecture without magic (and how to build it if you're not Google) - DEV Co... - 0 views

dev.to/...ld-it-if-youre-not-google-336a

development architecture system google

shared by 張 旭 on 24 Feb 19 - No Cached
  • Don’t mess up write-first and read-first databases.
  • keep them stateless.
  • you should know how to make a scalable setup on bare metal.
  • ...29 more annotations...
  • Different programming languages are for different tasks.
  • Go or C which are compiled to run on bare metal.
  • To run NodeJS on multiple cores, you have to use something like PM2, but since this you have to keep your code stateless.
  • Python have very rich and sugary syntax that’s great for working with data while keeping your code small and expressive.
  • SQL is almost always slower than NoSQL
  • databases are often read-first or write-first
  • write-first, just like Cassandra.
  • store all of your data to your databases and leave nothing at backend
  • Functional code is stateless by default
  • It’s better to go for stateless right from the very beginning.
  • deliver exactly the same responses for same requests.
  • Sessions? Store them at Redis and allow all of your servers to access it.
  • Only the first user will trigger a data query, and all others will be receiving exactly the same data straight from the RAM
  • never, never cache user input
  • Only the server output should be cached
  • Varnish is a great cache option that works with HTTP responses, so it may work with any backend.
  • a rate limiter – if there’s not enough time have passed since last request, the ongoing request will be denied.
  • different requests blasting every 10ms can bring your server down
  • Just set up entry relations and allow your database to calculate external keys for you
  • the query planner will always be faster than your backend.
  • Backend should have different responsibilities: hashing, building web pages from data and templates, managing sessions and so on.
  • For anything related to data management or data models, move it to your database as procedures or queries.
  • a distributed database.
  • your code has to be stateless
  • Move anything related to the data to the database.
  • For load-balancing a database, go for cluster.
  • DB is balancing requests, as well as your backend.
  • Users from different continents are separated with DNS.
  • Keep is scalable, keep is stateless.
  • 張 旭 on 24 Feb 19
     
    "Don't mess up write-first and read-first databases."
張 旭

Logstash Alternatives: Pros & Cons of 5 Log Shippers [2019] - Sematext - 0 views

sematext.com/...logstash-alternatives

log monitor system logstash fluentd

shared by 張 旭 on 05 Nov 19 - No Cached
  • In this case, Elasticsearch. And because Elasticsearch can be down or struggling, or the network can be down, the shipper would ideally be able to buffer and retry
  • Logstash is typically used for collecting, parsing, and storing logs for future use as part of log management.
  • Logstash’s biggest con or “Achille’s heel” has always been performance and resource consumption (the default heap size is 1GB).
  • ...37 more annotations...
  • This can be a problem for high traffic deployments, when Logstash servers would need to be comparable with the Elasticsearch ones.
  • Filebeat was made to be that lightweight log shipper that pushes to Logstash or Elasticsearch.
  • differences between Logstash and Filebeat are that Logstash has more functionality, while Filebeat takes less resources.
  • Filebeat is just a tiny binary with no dependencies.
  • For example, how aggressive it should be in searching for new files to tail and when to close file handles when a file didn’t get changes for a while.
  • For example, the apache module will point Filebeat to default access.log and error.log paths
  • Filebeat’s scope is very limited,
  • Initially it could only send logs to Logstash and Elasticsearch, but now it can send to Kafka and Redis, and in 5.x it also gains filtering capabilities.
  • Filebeat can parse JSON
  • you can push directly from Filebeat to Elasticsearch, and have Elasticsearch do both parsing and storing.
  • You shouldn’t need a buffer when tailing files because, just as Logstash, Filebeat remembers where it left off
  • For larger deployments, you’d typically use Kafka as a queue instead, because Filebeat can talk to Kafka as well
  • The default syslog daemon on most Linux distros, rsyslog can do so much more than just picking logs from the syslog socket and writing to /var/log/messages.
  • It can tail files, parse them, buffer (on disk and in memory) and ship to a number of destinations, including Elasticsearch.
  • rsyslog is the fastest shipper
  • Its grammar-based parsing module (mmnormalize) works at constant speed no matter the number of rules (we tested this claim).
  • use it as a simple router/shipper, any decent machine will be limited by network bandwidth
  • It’s also one of the lightest parsers you can find, depending on the configured memory buffers.
  • rsyslog requires more work to get the configuration right
  • the main difference between Logstash and rsyslog is that Logstash is easier to use while rsyslog lighter.
  • rsyslog fits well in scenarios where you either need something very light yet capable (an appliance, a small VM, collecting syslog from within a Docker container).
  • rsyslog also works well when you need that ultimate performance.
  • syslog-ng as an alternative to rsyslog (though historically it was actually the other way around).
  • a modular syslog daemon, that can do much more than just syslog
  • Unlike rsyslog, it features a clear, consistent configuration format and has nice documentation.
  • Similarly to rsyslog, you’d probably want to deploy syslog-ng on boxes where resources are tight, yet you do want to perform potentially complex processing.
  • syslog-ng has an easier, more polished feel than rsyslog, but likely not that ultimate performance
  • Fluentd was built on the idea of logging in JSON wherever possible (which is a practice we totally agree with) so that log shippers down the line don’t have to guess which substring is which field of which type.
  • Fluentd plugins are in Ruby and very easy to write.
  • structured data through Fluentd, it’s not made to have the flexibility of other shippers on this list (Filebeat excluded).
  • Fluent Bit, which is to Fluentd similar to how Filebeat is for Logstash.
  • Fluentd is a good fit when you have diverse or exotic sources and destinations for your logs, because of the number of plugins.
  • Splunk isn’t a log shipper, it’s a commercial logging solution
  • Graylog is another complete logging solution, an open-source alternative to Splunk.
  • everything goes through graylog-server, from authentication to queries.
  • Graylog is nice because you have a complete logging solution, but it’s going to be harder to customize than an ELK stack.
  • it depends
1 - 15 of 15
Showing 20▼ items per page