Upstream C1 Pdf

[Rashawn Devegowda]

Bydefault, requests are distributed between the servers using aweighted round-robin balancing method.In the above example, each 7 requests will be distributed as follows:5 requests go to backend1.example.comand one request to each of the second and third servers.If an error occurs during communication with a server, the request willbe passed to the next server, and so on until all of the functioningservers will be tried.If a successful response could not be obtained from any of the servers,the client will receive the result of the communication with the last server.

If the service name contains one or more dots, then the name is constructedby joining the service prefix and the server name.For example, to look up the _http._tcp.backend.example.comand server1.backend.example.com SRV records,it is necessary to specify the directives:

Highest-priority SRV records(records with the same lowest-number priority value)are resolved as primary servers,the rest of SRV records are resolved as backup servers.If the backup parameter is specified for the server,high-priority SRV records are resolved as backup servers,the rest of SRV records are ignored.

Additionally,as part of our commercial subscription,such groups allow changing the group membershipor modifying the settings of a particular serverwithout the need of restarting nginx.The configuration is accessible via theAPI module (1.13.3).

The state is currently limited to the list of servers with their parameters.The file is read when parsing the configuration and is updated each timethe upstream configuration ischanged.Changing the file content directly should be avoided.The directive cannot be usedalong with the server directive.

Specifies a load balancing method for a server groupwhere the client-server mapping is based on the hashed key value.The key can contain text, variables, and their combinations.Note that adding or removing a server from the groupmay result in remapping most of the keys to different servers.The method is compatible with theCache::MemcachedPerl library.

If the consistent parameter is specified,the ketamaconsistent hashing method will be used instead.The method ensures that only a few keyswill be remapped to different serverswhen a server is added to or removed from the group.This helps to achieve a higher cache hit ratio for caching servers.The method is compatible with theCache::Memcached::FastPerl library with the ketama_points parameter set to 160.

Specifies that a group should use a load balancing method where requestsare distributed between servers based on client IP addresses.The first three octets of the client IPv4 address, or the entire IPv6 address,are used as a hashing key.The method ensures that requests from the same client will always bepassed to the same server except when this server is unavailable.In the latter case client requests will be passed to another server.Most probably, it will always be the same server as well.

The connections parameter sets the maximum number ofidle keepalive connections to upstream servers that are preserved inthe cache of each worker process.When this number is exceeded, the least recently used connectionsare closed.

Specifies that a group should use a load balancing method where a requestis passed to the server with the least number of active connections,taking into account weights of servers.If there are several such servers, they are tried in turn using aweighted round-robin balancing method.

Specifies that a group should use a load balancing method where a requestis passed to the server with the least average response time andleast number of active connections, taking into account weights of servers.If there are several such servers, they are tried in turn using aweighted round-robin balancing method.

If the header parameter is specified,time to receive theresponse header is used.If the last_byte parameter is specified,time to receive the full responseis used.If the inflight parameter is specified (1.11.6),incomplete requests are also taken into account.

If an upstream server cannot be selected immediatelywhile processing a request,the request will be placed into the queue.The directive specifies the maximum number of requeststhat can be in the queue at the same time.If the queue is filled up,or the server to pass the request to cannot be selected withinthe time period specified in the timeout parameter,the 502 (Bad Gateway)error will be returned to the client.

The optional two parameterinstructs nginx to randomly selecttwoservers and then choose a serverusing the specified method.The default method is least_connwhich passes a request to a serverwith the least number of active connections.

The least_time method passes a request to a serverwith the least average response time and least number of active connections.If least_time=header is specified, the time to receive theresponse header is used.If least_time=last_byte is specified, the time to receive thefull response is used.

A request that comes from a client not yet bound to a particular serveris passed to the server selected by the configured balancing method.Further requests with this cookie will be passed to the designated server.If the designated server cannot process a request, the new server isselected as if the client has not been bound yet.

The parameters create and lookupspecify variables that indicate how new sessions are created and existingsessions are searched, respectively.Both parameters may be specified more than once, in which case the firstnon-empty variable is used.

Sessions are stored in a shared memory zone, whose name andsize are configured by the zone parameter.One megabyte zone can store about 4000 sessions on the 64-bit platform.The sessions that are not accessed during the time specified by thetimeout parameter get removed from the zone.By default, timeout is set to 10 minutes.

When talking about an upstream, it's usually the precursor to other projects and products. One of the best-known examples is the Linux kernel, which is an upstream project for many Linux distributions. Distributors like Red Hat take the unmodified (often referred to as "vanilla") kernel source and then add patches, add an opinionated configuration, and build the kernel with the options they want to offer their users.

In some cases, a project or product might have more than one upstream. Red Hat Enterprise Linux (RHEL) releases are based on Fedora Linux releases. The Fedora Project, in turn, pulls from many upstream projects to create Fedora Linux, like the Linux kernel, GNOME, systemd, Podman, various GNU utilities and projects, the Wayland and X.org display servers, and many more.

The Fedora Project releases a new version of Fedora roughly every six months. Periodically, Red Hat will take a Fedora Linux release and base a RHEL release on that. Rather than starting from scratch with the vanilla sources for the Linux kernel, GNOME, systemd, and the rest Red Hat starts with the Fedora sources for these projects and utilities, which makes Fedora an upstream of RHEL--with a further upstream of the originating projects. Fedora is downstream of these projects and RHEL is downstream of Fedora.

The upstream is the focal point where collaborators do the work. It's far better if all the contributors work together rather than, say, contributors from different companies working on features behind closed doors and then trying to integrate them later.

The reasons for this are many. First, it's just good open source citizenship to do the work side-by-side with the rest of the community and share our work with the communities from which we're benefitting.

By working upstream first, you have the opportunity to vet ideas with the larger community and work together to build new features, releases, content, etc. The features or changes you want to make may have an impact on other parts of the project. It's good to find these things out early and give the rest of the community an opportunity to weigh in.

Secondly, it's a better choice pragmatically to do the work upstream first. Sometimes it can be faster to implement a feature in a downstream project or product--especially if there are competing ideas about the direction of a project--but it's usually more work in the long run to carry those patches back to the project. By the time it's been shipped in a downstream, there's a good chance that the upstream code has changed, making it harder to integrate patches developed against an older version of the project.

If the features or patches aren't accepted upstream for some reason, then a vendor can carry those separately. That's one of the benefits of open source, you can modify and distribute your own version (within the terms of the license, of course) that meets your needs. It's possible that will be more work in the long run, but sometimes there's a good reason to diverge from upstream. But if there isn't, there's no point in incurring more work than needed.

Those days are pretty much behind us. Sure, you can compile code and tweak software configurations if you want to--but most of the time, users don't want to. Organizations generally don't want to, they want to rely on certified products that they can vet for their environment and get support for. This is why enterprise open source exists. Users and organizations count on vendors to turn upstreams into coherent downstream products that meet their needs.

In turn, vendors like Red Hat learn from customer requests and feedback about what features they need and want. That, then, benefits the upstream project in the form of new features and bugfixes, etc., and ultimately finds its way into products and the cycle continues.

Brockmeier joined Red Hat in 2013 as part of the Open Source and Standards (OSAS) group, now the Open Source Program Office (OSPO). Prior to Red Hat, Brockmeier worked for Citrix on the Apache OpenStack project, and was the first OpenSUSE community manager for Novell between 2008-2010.

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