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Added routing optimization content to 4.0
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‎_topic_map.yml

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File: network-optimization
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- Name: Optimizing storage
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File: optimizing-storage
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#---
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#Name: Storage
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#Dir: storage
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#Distros: openshift-*
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#Topics:
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#- Name: Persistent Storage Using AWS
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# File: persistent-storage-aws
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- Name: Routing optimization
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File: routing-optimization
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---
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Name: Nodes
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Dir: nodes

‎backup_and_restore/PLACEHOLDER

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‎modules/baseline-router-performance.adoc

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[id='baseline-router-performance-{context}']
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= Baseline router performance
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The {product-title} router is the ingress point for all external traffic
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destined for {product-title} services.
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When evaluating a single HAProxy router performance in terms of
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HTTP requests handled per second, the performance varies depending
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on many factors. In particular:
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* HTTP keep-alive/close mode
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* route type
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* TLS session resumption client support
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* number of concurrent connections per target route
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* number of target routes
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* back end server page size
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* underlying infrastructure (network/SDN solution, CPU, and so on)
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////
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COMMENTING OUT METRICS UNTIL WE GET NEW DATA
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While performance in your specific environment will vary, Red Hat lab
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tests on a public cloud instance of size 4 vCPU/16GB RAM, a single
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HAProxy router handling 100 routes terminated by backends serving
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1kB static pages is able to handle the following number of transactions
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per second.
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In HTTP keep-alive mode scenarios:
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[cols="3",options="header"]
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|===
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|*Encryption* |*ROUTER_THREADS unset*|*ROUTER_THREADS=4*
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|none |23681|24327
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|edge |14981|22768
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|passthrough |34358|34331
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|re-encrypt |13288|24605
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|===
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In HTTP close (no keep-alive) scenarios:
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[cols="3",options="header"]
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|===
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|*Encryption* |*ROUTER_THREADS unset*|*ROUTER_THREADS=4*
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|none |3245|4527
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|edge |1910|3043
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|passthrough |3408|3922
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|re-encrypt |1333|2239
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|===
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TLS session resumption was used for encrypted routes. With HTTP
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keep-alive, a single HAProxy router is capable of saturating 1 Gbit
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NIC at page sizes as small as 8 kB.
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When running on bare metal with modern processors, you can expect roughly
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twice the performance of the public cloud instance above. This
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overhead is introduced by the virtualization layer in place on public clouds and
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holds mostly true for private cloud-based virtualization as well. The following
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table is a guide on how many applications to use behind the router:
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[cols="2,4",options="header"]
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|===
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|*Number of applications* |*Application type*
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|5-10 |static file/web server or caching proxy
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|100-1000 |applications generating dynamic content
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|===
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In general, HAProxy can support routes for 5 to 1000 applications, depending on
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the technology in use. Router performance might be limited by the
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capabilities and performance of the applications behind it, such as language or
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static versus dynamic content.
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////
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Router sharding should be used to serve more routes towards applications and
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help horizontally scale the routing tier.

‎modules/router-performance-optimizations.adoc

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[id='router-performance-optimizations-{context}']
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= Router performance optimizations
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*Setting the maximum number of connections*
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One of the most important tunable parameters for HAProxy scalability is the
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`maxconn` parameter, which sets the maximum per-process number of concurrent
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connections to a given number. Adjust this parameter by editing the
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`ROUTER_MAX_CONNECTIONS` environment variable in the {product-title} HAProxy
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router's deployment configuration file.
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[NOTE]
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====
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A connection includes the front end and internal back end. This counts as two
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connections. Be sure to set `ROUTER_MAX_CONNECTIONS` to double than the number
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of connections you intend to create.
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====
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*CPU and interrupt affinity*
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In {product-title}, the HAProxy router runs as a single process. The
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{product-title} HAProxy router typically performs better on a system with fewer
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but high frequency cores, rather than on an symmetric multiprocessing (SMP)
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system with a high number of lower frequency cores.
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Pinning the HAProxy process to one CPU core and the network interrupts to
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another CPU core tends to increase network performance. Having processes and
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interrupts on the same non-uniform memory access (NUMA) node helps avoid memory
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accesses by ensuring a shared L3 cache. However, this level of control is
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generally not possible on a public cloud environment. On bare metal hosts,
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`irqbalance` automatically handles peripheral component interconnect (PCI)
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locality and NUMA affinity for interrupt request lines (IRQs). On a cloud
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environment, this level of information is generally not provided to the
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operating system.
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CPU pinning is performed either by `taskset` or by using HAProxy's `cpu-map`
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parameter. This directive takes two arguments: the process ID and the CPU core
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ID. For example, to pin HAProxy process `1` onto CPU core `0`, add the following
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line to the global section of HAProxy's configuration file:
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----
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cpu-map 1 0
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----
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*Increasing the number of threads*
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The HAProxy router comes with support for multithreading in {product-title}. On
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a multiple CPU core system, increasing the number of threads can help the
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performance, especially when terminating SSL on the router.
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*Impacts of buffer increases*
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The {product-title} HAProxy router request buffer configuration limits the size
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of headers in incoming requests and responses from applications. The HAProxy
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parameter `tune.bufsize` can be increased to allow processing of larger headers
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and to allow applications with very large cookies to work, such as those
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accepted by load balancers provided by many public cloud providers. However,
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this affects the total memory use, especially when large numbers of connections
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are open. With very large numbers of open connections, the memory usage will be
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nearly proportionate to the increase of this tunable parameter.
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*Optimizations for HAProxy reloads*
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Long-lasting connections, such as WebSocket connections, combined with
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long client/server HAProxy timeouts and short HAProxy
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reload intervals, can cause instantiation of many HAProxy processes.
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These processes must handle old connections, which were started
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before the HAProxy configuration reload. A large number of these processes is
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undesirable, as it will exert unnecessary load on the system and can
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lead to issues, such as out of memory conditions.
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Router environment variables affecting this
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behavior are `ROUTER_DEFAULT_TUNNEL_TIMEOUT`, `ROUTER_DEFAULT_CLIENT_TIMEOUT`,
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`ROUTER_DEFAULT_SERVER_TIMEOUT`, and `RELOAD_INTERVAL` in particular.

‎scalability_and_performance/routing-optimization.adoc

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[id='routing-optimization']
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= Routing optimization
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include::modules/common-attributes.adoc[]
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:context: routing-optimization
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toc::[]
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The {product-title} HAProxy router scales to optimize performance.
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include::modules/baseline-router-performance.adoc[leveloffset=+1]
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include::modules/router-performance-optimizations.adoc[leveloffset=+1]

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