Isp Load Balancing Pdf ViewerI want achieve a load balancing of ISP like the one below. Only 2 subnet should go through ISP 2, and rest of the traffic should go to ISP 1. Isp Load Balancing Pdf To JpgLoad Balancing in General Load Balance with Masquerade Network on RouterOS Prepared by. ECMP load balancing with masquerade. Load Balancing is method aiming to spread traffic across multiple links to get better link usage. This can be done one per-packet or per-connection basis. Load balancing (computing) - Wikipedia, the free encyclopedia. User requests to the Wikimedia Elasticsearch server cluster are routed via load balancing. In computing, load balancing improves the distribution of workloads across multiple computing resources, such as computers, a computer cluster, network links, central processing units, or disk drives. Using multiple components with load balancing instead of a single component may increase reliability and availability through redundancy. Load balancing usually involves dedicated software or hardware, such as a multilayer switch or a Domain Name System server process. Load balancing differs from channel bonding in that load balancing divides traffic between network interfaces on a network socket (OSI model layer 4) basis, while channel bonding implies a division of traffic between physical interfaces at a lower level, either per packet (OSI model Layer 3) or on a data link (OSI model Layer 2) basis with a protocol like shortest path bridging. Internet- based services. Commonly load- balanced systems include popular web sites, large Internet Relay Chat networks, high- bandwidth File Transfer Protocol sites, Network News Transfer Protocol (NNTP) servers, Domain Name System (DNS) servers, and databases. Round- robin DNS. In this technique, multiple IP addresses are associated with a single domain name; clients are expected to choose which server to connect to. Unlike the use of a dedicated load balancer, this technique exposes to clients the existence of multiple backend servers. The technique has other advantages and disadvantages, depending on the degree of control over the DNS server and the granularity of load balancing desired. DNS Delegation. This technique works particularly well where individual servers are spread geographically on the Internet. For example. one. A 1. 92. 0. 2. 1. A 2. 03. 0. 1. 13. NS one. example. org. NS two. example. org. However, the zone file for www. IP Address as the A- record. If the line to one server is congested, the unreliability of DNS ensures less HTTP traffic reaches that server. Furthermore, the quickest DNS response to the resolver is nearly always the one from the network's closest server, ensuring geo- sensitive load- balancing. A short TTL on the A- record helps to ensure traffic is quickly diverted when a server goes down. Consideration must be given the possibility that this technique may cause individual clients to switch between individual servers in mid- session. Client- Side Random Load Balancing. It has been claimed that client- side random load balancing tends to provide better load distribution than round- robin DNS; this has been attributed to caching issues with round- robin DNS, which in case of large DNS caching servers, tend to skew the distribution for round- robin DNS, while client- side random selection remains unaffected regardless of DNS caching. The load balancer forwards requests to one of the . This allows the load balancer to reply to the client without the client ever knowing about the internal separation of functions. It also prevents clients from contacting back- end servers directly, which may have security benefits by hiding the structure of the internal network and preventing attacks on the kernel's network stack or unrelated services running on other ports. Some load balancers provide a mechanism for doing something special in the event that all backend servers are unavailable. This might include forwarding to a backup load balancer, or displaying a message regarding the outage. It is also important that the load balancer itself does not become a single point of failure. Usually load balancers are implemented in high- availability pairs which may also replicate session persistence data if required by the specific application. Simple algorithms include random choice or round robin. More sophisticated load balancers may take additional factors into account, such as a server's reported load, least response times, up/down status (determined by a monitoring poll of some kind), number of active connections, geographic location, capabilities, or how much traffic it has recently been assigned. Persistence. If this information is stored locally on one backend server, then subsequent requests going to different backend servers would not be able to find it. This might be cached information that can be recomputed, in which case load- balancing a request to a different backend server just introduces a performance issue. Ideally the cluster of servers behind the load balancer should be session- aware, so that if a client connects to any backend server at any time the user experience is unaffected. This is usually achieved with a shared database or an in- memory session database, for example Memcached. One basic solution to the session data issue is to send all requests in a user session consistently to the same backend server. This is known as persistence or stickiness. A significant downside to this technique is its lack of automatic failover: if a backend server goes down, its per- session information becomes inaccessible, and any sessions depending on it are lost. The same problem is usually relevant to central database servers; even if web servers are . Because of changes of the client's perceived address resulting from DHCP, network address translation, and web proxies this method may be unreliable. Random assignments must be remembered by the load balancer, which creates a burden on storage. If the load balancer is replaced or fails, this information may be lost, and assignments may need to be deleted after a timeout period or during periods of high load to avoid exceeding the space available for the assignment table. The random assignment method also requires that clients maintain some state, which can be a problem, for example when a web browser has disabled storage of cookies. Sophisticated load balancers use multiple persistence techniques to avoid some of the shortcomings of any one method. Another solution is to keep the per- session data in a database. Generally this is bad for performance because it increases the load on the database: the database is best used to store information less transient than per- session data. To prevent a database from becoming a single point of failure, and to improve scalability, the database is often replicated across multiple machines, and load balancing is used to spread the query load across those replicas. Microsoft's ASP. net State Server technology is an example of a session database. All servers in a web farm store their session data on State Server and any server in the farm can retrieve the data. In the very common case where the client is a web browser, a simple but efficient approach is to store the per- session data in the browser itself. One way to achieve this is to use a browser cookie, suitably time- stamped and encrypted. Another is URL rewriting. Storing session data on the client is generally the preferred solution: then the load balancer is free to pick any backend server to handle a request. However, this method of state- data handling is poorly suited to some complex business logic scenarios, where session state payload is big and recomputing it with every request on a server is not feasible. URL rewriting has major security issues, because the end- user can easily alter the submitted URL and thus change session streams. Yet another solution to storing persistent data is to associate a name with each block of data, and use a distributed hash table to pseudo- randomly assign that name to one of the available servers, and then store that block of data in the assigned server. Load balancer features. The fundamental feature of a load balancer is to be able to distribute incoming requests over a number of backend servers in the cluster according to a scheduling algorithm. Most of the following features are vendor specific: Asymmetric load: A ratio can be manually assigned to cause some backend servers to get a greater share of the workload than others. This is sometimes used as a crude way to account for some servers having more capacity than others and may not always work as desired. Priority activation: When the number of available servers drops below a certain number, or load gets too high, standby servers can be brought online. SSL Offload and Acceleration: Depending on the workload, processing the encryption and authentication requirements of an SSL request can become a major part of the demand on the Web Server's CPU; as the demand increases, users will see slower response times, as the SSL overhead is distributed among Web servers. To remove this demand on Web servers, a balancer can terminate SSL connections, passing HTTPS requests as HTTP requests to the Web servers. If the balancer itself is not overloaded, this does not noticeably degrade the performance perceived by end users. The downside of this approach is that all of the SSL processing is concentrated on a single device (the balancer) which can become a new bottleneck. Some load balancer appliances include specialized hardware to process SSL. Instead of upgrading the load balancer, which is quite expensive dedicated hardware, it may be cheaper to forgo SSL offload and add a few Web servers. Also, some server vendors such as Oracle/Sun now incorporate cryptographic acceleration hardware into their CPUs such as the T2. F5 Networks incorporates a dedicated SSL acceleration hardware card in their local traffic manager (LTM) which is used for encrypting and decrypting SSL traffic. One clear benefit to SSL offloading in the balancer is that it enables it to do balancing or content switching based on data in the HTTPS request. Distributed Denial of Service (DDo. S) attack protection: load balancers can provide features such as SYN cookies and delayed- binding (the back- end servers don't see the client until it finishes its TCP handshake) to mitigate SYN flood attacks and generally offload work from the servers to a more efficient platform.
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